Echo voltage reflected by turtle on various angles

IJAIN_vol1_vol4_no1.enl

Sunardi, SunardiYudhana, AntonMahfurdz, AzrulMohamed, Sharipah SalwaEcho voltage reflected by turtle on various angles

International Journal of Advances in Intelligent Informatics

48-56112015

10.26555/ijain.v1i1.9

http://ijain.org/index.php/IJAIN/article/view/9

This research proposes the acoustic measurement by using echo sounder for green turtle detection of 1 year, 12 and 18 years. Various positions or angles of turtles are head, tail, shell, lung, left and right side. MATLAB software and echo sounder are used to analyse the frequency and the response of the turtle as echo voltage and target strength parameter. Based on the experiment and analysis have been conducted, the bigger size of the turtle, the higher echo voltage and target strength. The target strength of turtle for lung and shell for all ages are -26.52 dB and –26.17 dB respectively. The target strength of turtles in this research is different with target strength of fish in our previous research. Therefore, for future research, the repellant system based on differences of target strength the turtle and fish for avoided the turtle trapping in the net can be implemented to protect the population of turtle from extinctionIJAIN_vol1_vol4_no1.enl

Aribowo, Agus SasmitoCahyana, Nur HeriFeasibility study for banking loan using association rule mining classifier

International Journal of Advances in Intelligent Informatics

41-47112015

10.26555/ijain.v1i1.8

http://ijain.org/index.php/IJAIN/article/view/8

The problem of bad loans in the koperasi can be reduced if the koperasi can detect whether member can complete the mortgage debt or decline. The method used for identify characteristic patterns of prospective lenders in this study, called Association Rule Mining Classifier. Pattern of credit member will be converted into knowledge and used to classify other creditors. Classification process would separate creditors into two groups: good credit and bad credit groups. Research using prototyping for implementing the design into an application using programming language and development tool. The process of association rule mining using Weighted Itemset Tidset (WIT)–tree methods. The results shown that the method can predict the prospective customer credit. Training data set using 120 customers who already know their credit history. Data test used 61 customers who apply for credit. The results concluded that 42 customers will be paying off their loans and 19 clients are declineIJAIN_vol1_vol4_no1.enl

Mulyodiputro, Muhammad DermawanSubanar, SubanarSimulation of queue with cyclic service in signalized intersection system

International Journal of Advances in Intelligent Informatics

30-40112015

10.26555/ijain.v1i1.15

http://ijain.org/index.php/IJAIN/article/view/15

The simulation was implemented by modeling the queue with cyclic service in the signalized intersection system. The service policies used in this study were exhaustive and gated, the model was the M/M/1 queue, the arrival rate used was Poisson distribution and the services rate used was Exponential distribution. In the gated service policy, the server served only vehicles that came before the green signal appears at an intersection. Considered that there were 2 types of exhaustive policy in the signalized intersection system, namely normal exhaustive (vehicles only served during the green signal was still active), and exhaustive (there was the green signal duration addition at the intersection, when the green signal duration at an intersection finished). The results of this queueing simulation program were to obtain characteristics and performance of the system, i.e. average number of vehicles and waiting time of vehicles in the intersection and in the system, as well as system utilities. Then from these values, it would be known which of the cyclic service policies (normal exhaustive, exhaustive and gated) was the most suitable when applied to a signalized intersection systemIJAIN_vol1_vol4_no1.enl

Megasari, RaniKuspriyanto, KuspriyantoMauludi Husni, EmirWidyantoro, Dwi HendratmoTowards host-to-host meeting scheduling negotiation

International Journal of Advances in Intelligent Informatics

23-29112015

10.26555/ijain.v1i1.6

http://ijain.org/index.php/IJAIN/article/view/6

This paper presents a different scheme of meeting scheduling negotiation among a large number of personnel in a heterogeneous community. This scheme, named Host-to-Host Negotiation, attempts to produce a stable schedule under uncertain personnel preferences. By collecting information from hosts’ inter organizational meeting, this study intends to guarantee personnel availability. As a consequence, personnel’s and meeting’s profile in this scheme are stored in a centralized manner. This study considers personnel preferences by adapting the Clarke Tax Mechanism, which is categorized as a non manipulated mechanism design. Finally, this paper introduces negotiation strategies based on the conflict handling mode. A host-to-host scheme can give notification if any conflict exist and lead to negotiation process with acceptable disclosed information. Nevertheless, a complete negotiation process will be more elaborated in the future works.IJAIN_vol1_vol4_no1.enl

Haviluddin, HaviluddinJawahir, AhmadComparing of ARIMA and RBFNN for short-term forecasting

International Journal of Advances in Intelligent Informatics

15-22112015

10.26555/ijain.v1i1.10

http://ijain.org/index.php/IJAIN/article/view/10

Based on a combination of an autoregressive integrated moving average (ARIMA) and a radial basis function neural network (RBFNN), a time-series forecasting model is proposed. The proposed model has examined using simulated time series data of tourist arrival to Indonesia recently published by BPS Indonesia. The results demonstrate that the proposed RBFNN is more competent in modelling and forecasting time series than an ARIMA model which is indicated by mean square error (MSE) values. Based on the results obtained, RBFNN model is recommended as an alternative to existing method because it has a simple structure and can produce reasonable forecasts.IJAIN_vol1_vol4_no1.enl

Abidin, ZaenalAlamsyah, AlamsyahWavelet based approach for facial expression recognition

International Journal of Advances in Intelligent Informatics

7-14112015

10.26555/ijain.v1i1.7

http://ijain.org/index.php/IJAIN/article/view/7

Facial expression recognition is one of the most active fields of research. Many facial expression recognition methods have been developed and implemented. Neural networks (NNs) have capability to undertake such pattern recognition tasks. The key factor of the use of NN is based on its characteristics. It is capable in conducting learning and generalizing, non-linear mapping, and parallel computation. Backpropagation neural networks (BPNNs) are the approach methods that mostly used. In this study, BPNNs were used as classifier to categorize facial expression images into seven-class of expressions which are anger, disgust, fear, happiness, sadness, neutral and surprise. For the purpose of feature extraction tasks, three discrete wavelet transforms were used to decompose images, namely Haar wavelet, Daubechies (4) wavelet and Coiflet (1) wavelet. To analyze the proposed method, a facial expression recognition system was built. The proposed method was tested on static images from JAFFE database.IJAIN_vol1_vol4_no1.enl

Yousefi, MiladYousefi, MoslemHooshyar, DanialAtaide de Souza Oliveira, JeffersonAn evolutionary approach for solving the job shop scheduling problem in a service industry

International Journal of Advances in Intelligent Informatics

1-6112015

10.26555/ijain.v1i1.5

http://ijain.org/index.php/IJAIN/article/view/5

In this paper, an evolutionary-based approach based on the discrete particle swarm optimization (DPSO) algorithm is developed for finding the optimum schedule of a registration problem in a university. Minimizing the makespan, which is the total length of the schedule, in a real-world case study is considered as the target function. Since the selected case study has the characteristics of job shop scheduling problem (JSSP), it is categorized as a NP-hard problem which makes it difficult to be solved by conventional mathematical approaches in relatively short computation time.IJAIN_vol1_vol4_no1.enl

Jawahir, AhmadHaviluddin, HaviluddinAn audio encryption using transposition method

International Journal of Advances in Intelligent Informatics

98-106122015

10.26555/ijain.v1i2.24

http://ijain.org/index.php/IJAIN/article/view/24

Encryption is a technique to secure sounds data from attackers. In this study, transposition technique that corresponds to a WAV file extension is used. The performance of the transposition technique is measured using the mean square error (MSE). In the test, the value of MSE of the original and encrypted audio files were compared; the original and decrypted audio files used the correct password is ‘SEMBILAN’ and the incorrect password is ‘DELAPAN’. The experimental results showed that the original and encrypted audio files, and the original and decrypted audio files used the correct password that has a value of MSE = 0, and with the incorrect one with a value of MSE 0.00000428 or ≠ 0. In other words, the transposition technique is able to ensure the security of audio data files.IJAIN_vol1_vol4_no1.enl

Thobirin, ArisYanto, Iwan Tri RiyadiAutomatic differentiation based for particle swarm optimization Steepest descent direction

International Journal of Advances in Intelligent Informatics

90-97122015

10.26555/ijain.v1i2.29

http://ijain.org/index.php/IJAIN/article/view/29

Particle swam optimization (PSO) is one of the most effective optimization methods to find the global optimum point. In other hand, the descent direction (DD) is the gradient based method that has the local search capability. The combination of both methods is promising and interesting to get the method with effective global search capability and efficient local search capability. However, In many application, it is difficult or impossible to obtain the gradient exactly of an objective function. In this paper, we propose Automatic differentiation (AD) based for PSODD. we compare our methods on benchmark function. The results shown that the combination methods give us a powerful tool to find the solution.IJAIN_vol1_vol4_no1.enl

Jayadianti, HerlinaNugroho, Lukito EdiSantosa, Paulus InsapWidayat, WahyuAdding synonyms to concepts in ontology to solve the problem of semantic heterogeneity

International Journal of Advances in Intelligent Informatics

84-89122015

10.26555/ijain.v1i2.19

http://ijain.org/index.php/IJAIN/article/view/19

Nowadays many department (community) are thinking how to get more knowledges and metadata by linking more systems from other community. There are great challenges to make all systems organizing knowledge and sharing metadata – to make it easy searched, indexed and used in different context. In this paper we will focus on metadata in specific domain - ‘Poverty’2. Regardless of the various definitions of poverty, in this paper we will focus on managing metadata in “Poverty” with many different terms therein. Ontology Mapping is the process of relating similar concepts or relations from different sources through some equivalence relation. Mapping allows finding correspondences between the concepts of two ontologies. If two concepts correspond, then they mean the same thing or closely related things. Currently, the mapping process is regarded as a promise to solve the problem between ontologies since it attempts to find correspondences between semantically related entities that belong to different ontologies. It takes as input two ontologies, each consisting of a set of components (classes, instances, properties, rules and axioms). Based on the presented reasons, we believe that ontologies with common terms and common concepts are very important in a metadata sharing process.IJAIN_vol1_vol4_no1.enl

Hamdani, HamdaniWardoyo, RetantyoA review on fuzzy multi-criteria decision making land clearing for oil palm plantation

International Journal of Advances in Intelligent Informatics

75-83122015

10.26555/ijain.v1i2.26

http://ijain.org/index.php/IJAIN/article/view/26

Our review paper research categorize the methods in the method of Fuzzy Multi-Criteria Decision Making (FMCDM) to find the method is widely used in the case of land clearing for plantation. Model FMCDM is used to assess the parameter in multi-criteria-based decision making. The dominant percentage of the result was obtained using Fuzzy Analytic Hierarchy Process (FAHP) method. While the application of other methods for the same problem are Fuzzy Ordered Weighted Averaging (FOWA), Fuzzy Elimination Et Choix Traduisant la Realite or Elimination and Choice Translating Reality (FELECTRE), Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), Fuzzy, Artificial Neural Networks (FANNs) has less. Some the research result also implemented hybrid in FMCDM Method to give some weight in the assessment of decision making. There was also a paper which integrates FMCDM to the GIS method on the land clearing. Therefore, it is concluded that the issue on the land clearing can be done through collaboration of several models of FMCDM, so that it can be developed by involving the decision model using multi-stakeholder modelIJAIN_vol1_vol4_no1.enl

Azimirad, EhsanHaddadnia, JavadTarget threat assessment using fuzzy sets theory

International Journal of Advances in Intelligent Informatics

57-74122015

10.26555/ijain.v1i2.18

http://ijain.org/index.php/IJAIN/article/view/18

The threat evaluation is significant component in target classification process and is significant in military and non military applications. Small errors or mistakes in threat evaluation and target classification especial in military applications can result in huge damage of life and property. Threat evaluation helps in case of weapon assignment, and intelligence sensor support system. It is very important factor to analyze the behavior of enemy tactics as well as our surveillance. This paper represented a precise description of the threat evaluation process using fuzzy sets theory. A review has been carried out regarding which parameters that have been suggested for threat value calculation. For the first time in this paper, eleven parameters are introduced for threat evaluation so that this parameters increase the accuracy in designed system. The implemented threat evaluation system has been applied to a synthetic air defense scenario and four real time dynamic air defense scenarios. The simulation results show the correctness, accuracy, reliability and minimum errors in designing of threat evaluation systemIJAIN_vol1_vol4_no1.enl

Muhajir, MuhammadEfanna, Berky RianAssociation Rule Algorithm Sequential Pattern Discovery using Equivalent Classes (SPADE) to Analyze the Genesis Pattern of Landslides in Indonesia

International Journal of Advances in Intelligent Informatics

158-164132015

10.26555/ijain.v1i3.50

http://ijain.org/index.php/IJAIN/article/view/50

Landslide is one of movement of soil, rock, soil creep, and rock debris that occurred the move of the slopes. It is caused by steep slopes, high rainfall, deforestation, mining activities, and erosion. The impacts of the landslide are loss of property, damage to facilities such as homes and buildings, casualties, psychological trauma, disrupted economic and environmental damage. Based on the impacts of landslide, mitigation required to take early precautions are to know how the pattern of association between the sequence of events landslides and to know how the associative relationship pattern of earthquakes. Based on the impacts, the results of this research is associative relationship pattern is obtained from data flood that occurs in Indonesia, namely in case of heavy rain will occur labile soil structure to support the value of 0.37, confidence level of 41% and the power of formed ruled is 1.02.IJAIN_vol1_vol4_no1.enl

Prahara, AdhiPranolo, AndriDreżewski, RafałGPU Accelerated Number Plate Localization in Crowded Situation

International Journal of Advances in Intelligent Informatics

150-157132015

10.26555/ijain.v1i3.46

http://ijain.org/index.php/IJAIN/article/view/46

Number Plate Localization (NPL) has been widely used as part of Automatic Number Plate Recognition (ANPR) system. NPL method determines the accuracy of ANPR system. Although it is a mature research, the challenge stills persist especially in crowded situation where many vehicles present. Therefore, a method is proposed to localize number plate in crowded situation. The proposed NPL method uses vertical edge density to extract potential region of number plate then detect the number plate using combination of Histogram of Oriented Gradients (HOG) and Support Vector Machine (SVM). The method employs GPU to deal with multiple number plate detection, to handle multi-scale detection window, and to perform real time detection. The test result shows good results, 0.9883 value of AUC (Area Under Curve), and 0.9362 of BAC (Balance Accuracy). Moreover, potential real time detection is foreseen because total process is executed in less than 50 ms. Errors are mainly caused by background that contain letters, non-standard number plate and highly covered number plateIJAIN_vol1_vol4_no1.enl

Yousefi, MoslemHooshyar, DanialRemezani, AmirSahari, Khairul Salleh MohamedKhaksar, WeriaAlnaimi, Firas B. IsmailShort-term wind speed forecasting by an adaptive network-based fuzzy inference system (ANFIS): an attempt towards an ensemble forecasting method

International Journal of Advances in Intelligent Informatics

140-149132015

10.26555/ijain.v1i3.45

http://ijain.org/index.php/IJAIN/article/view/45

Accurate Wind speed forecasting has a vital role in efficient utilization of wind farms. Wind forecasting could be performed for long or short time horizons. Given the volatile nature of wind and its dependent on many geographical parameters, it is difficult for traditional methods to provide a reliable forecast of wind speed time series. In this study, an attempt is made to establish an efficient adaptive network-based fuzzy interference (ANFIS) for short-term wind speed forecasting. Using the available data sets in the literature, the ANFIS network is constructed, tested and the results are compared with that of a regular neural network, which has been forecasted the same set of dataset in previous studies. To avoid trial-and-error process for selection of the ANFIS input data, the results of autocorrelation factor (ACF) and partial auto correlation factor (PACF) on the historical wind speed data are employed. The available data set is divided into two parts. 50% for training and 50% for testing and validation. The testing part of data set will be merely used for assessing the performance of the neural network which guarantees that only unseen data is used to evaluate the forecasting performance of the network. On the other hand, validation data could be used for parameter-setting of the network if required. The results indicate that ANFIS could not outperform ANN in short-term wind speed forecasting though its results are competitive. The two methods are hybridized, though simply by weightage, and the hybrid methods shows slight improvement comparing to both ANN and ANFIS results. Therefore, the goal of future studies could be implementing ANFIS and ANNs in a more comprehensive ensemble method which could be ultimately more robust and accurateIJAIN_vol1_vol4_no1.enl

Hidayat, Erwin YudiFirdausillah, FahriHastuti, KhafiizhDewi, Ika NovitaAzhari, AzhariAutomatic Text Summarization Using Latent Drichlet Allocation (LDA) for Document Clustering

International Journal of Advances in Intelligent Informatics

132-139132015

10.26555/ijain.v1i3.43

http://ijain.org/index.php/IJAIN/article/view/43

In this paper, we present Latent Drichlet Allocation in automatic text summarization to improve accuracy in document clustering. The experiments involving 398 data set from public blog article obtained by using python scrapy crawler and scraper. Several steps of clustering in this research are preprocessing, automatic document compression using feature method, automatic document compression using LDA, word weighting and clustering algorithm The results show that automatic document summarization with LDA reaches 72% in LDA 40%, compared to traditional k-means method which only reaches 66%.IJAIN_vol1_vol4_no1.enl

Lenin, KanagasabaiReddy, Bhumanapally RavindhranathKalavathi, Munagala SuryaProgressive Particle Swarm Optimization Algorithm for Solving Reactive Power Problem

International Journal of Advances in Intelligent Informatics

125-131132015

10.26555/ijain.v1i3.42

http://ijain.org/index.php/IJAIN/article/view/42

In this paper a Progressive particle swarm optimization algorithm (PPS) is used to solve optimal reactive power problem. A Particle Swarm Optimization algorithm maintains a swarm of particles, where each particle has position vector and velocity vector which represents the potential solutions of the particles. These vectors are modernized from the information of global best (Gbest) and personal best (Pbest) of the swarm. All particles move in the search space to obtain optimal solution. In this paper a new concept is introduced of calculating the velocity of the particles with the help of Euclidian Distance conception. This new-fangled perception helps in finding whether the particle is closer to Pbest or Gbest and updates the velocity equation consequently. By this we plan to perk up the performance in terms of the optimal solution within a rational number of generations. The projected PPS has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss with control variables are within the limits.IJAIN_vol1_vol4_no1.enl

Ramezani Dooraki, AmirA survey on computer vision technology in Camera Based ETA devices

International Journal of Advances in Intelligent Informatics

115-124132015

10.26555/ijain.v1i3.40

http://ijain.org/index.php/IJAIN/article/view/40

Electronic Travel Aid systems are expected to make impaired persons able to perform their everyday tasks such as finding an object and avoiding obstacles easier. Among ETA devices, Camera Based ETA devices are the new one and with a high potential for helping Visually Impaired Persons. With recent advances in computer science and specially computer vision, Camera Based ETA devices used several computer vision algorithms and techniques such as object recognition and stereo vision in order to help VIP to perform tasks such as reading banknotes, recognizing people and avoiding obstacles. This paper analyses and appraises a number of literatures in this area with focus on stereo vision technique. Finally, after discussing about the methods and techniques used in different literatures, it is concluded that the stereo vision is the best technique for helping VIP in their everyday navigation.IJAIN_vol1_vol4_no1.enl

Nurdiyanto, HeriHermanto, HermantoSignature recognition using neural network probabilistic

International Journal of Advances in Intelligent Informatics

46-53212016

10.26555/ijain.v2i1.53

http://ijain.org/index.php/IJAIN/article/view/53

The signature of each person is different and has unique characteristics. Thus, this paper discusses the development of a personal identification system based on it is unique digital signature. The process of preprocessing used gray scale method, while Shannon Entropy and Probabilistic Neural Network are used respectively for feature extraction and identification. This study uses five signature types with five signatures in every type. While the test results compared to actual data compared to real data, the proposed system performance was only 40%.IJAIN_vol1_vol4_no1.enl

Ismi, Dewi PramudiPanchoo, ShireenMurinto, MurintoK-means clustering based filter feature selection on high dimensional data

International Journal of Advances in Intelligent Informatics

38-45212016

10.26555/ijain.v2i1.54

http://ijain.org/index.php/IJAIN/article/view/54

With hundreds or thousands of features in high dimensional data, computational workload is challenging. In classification process, features which do not contribute significantly to prediction of classes, add to the computational workload. Therefore the aim of this paper is to use feature selection to decrease the computation load by reducing the size of high dimensional data. Selecting subsets of features which represent all features were used. Hence the process is two-fold; discarding irrelevant data and choosing one feature that representing a number of redundant features. There have been many studies regarding feature selection, for example backward feature selection and forward feature selection. In this study, a k-means clustering based feature selection is proposed. It is assumed that redundant features are located in the same cluster, whereas irrelevant features do not belong to any clusters. In this research, two different high dimensional datasets are used: 1) the Human Activity Recognition Using Smartphones (HAR) Dataset, containing 7352 data points each of 561 features and 2) the National Classification of Economic Activities Dataset, which contains 1080 data points each of 857 features. Both datasets provide class label information of each data point. Our experiment shows that k-means clustering based feature selection can be performed to produce subset of features. The latter returns more than 80% accuracy of classification result.IJAIN_vol1_vol4_no1.enl

Hastuti, KhafiizhMustafa, KhabibA method for automatic gamelan music composition

International Journal of Advances in Intelligent Informatics

26-37212016

10.26555/ijain.v2i1.57

http://ijain.org/index.php/IJAIN/article/view/57

Aim of this study is designing a method for automatic gamelan music composition using rule-base expert system approach. The program is designed for non-expert user in order to help them composing gamelan music or analyzing their composition to achieve explanation and recommendation of ideal composition. There are 2 essential components in this method, which are knowledge and inference. Knowledge is represented into basic knowledge and melodic knowledge. Basic knowledge contains rules that control the structure of gamelan song, and melodic knowledge supports system in composing or analyzing notations sequence that fit the characteristics of melody in gamelan music. Basic knowledge represents basic rules of gamelan music that have quantitative value, so deterministic approach is used for basic knowledge acquisition. Melodic knowledge consists of dynamic data, so stochastic approach is used to create the melodic knowledge base. The rules of composing and analyzing a composition are defined based on basic knowledge and melodic knowledge. The inference engine is designed to compose and analyze a composition. Automatic composition for gamelan music is proposed using Generate and Test method (GAT) with random technique, and composition analysis is proposed using backward chaining methodIJAIN_vol1_vol4_no1.enl

Karimimalayer, MehdiSaibani, NizaroyaniImplementation of fuzzy logic to measure supply chain agility

International Journal of Advances in Intelligent Informatics

18-25212016

10.26555/ijain.v2i1.32

http://ijain.org/index.php/IJAIN/article/view/32

In our age of perennial changing environment, supply chain agility is a crucial factor having a great impact on the company's competitiveness. For transforming supply chain into an agile supply chain, first it is necessary to comprehend the meaning of agile supply chain, since agility has wide range of meanings and various dimensions which covers different aspects of an organization. Generally, however, there have been many researches on agility, proportionally; the concept of agility in supply chain has not been much surveyed. The circumstance unveils the necessity of a technique to measure the supply chain agility. The purpose of the article is to propose a technique, using fuzzy logic which supply chain agility be measured.IJAIN_vol1_vol4_no1.enl

Mittal, VikasSingh, DharmendraSaini, Lalit MohanCritical analysis of classification techniques for polarimetric synthetic aperture radar data

International Journal of Advances in Intelligent Informatics

7-17212016

10.26555/ijain.v2i1.52

http://ijain.org/index.php/IJAIN/article/view/52

Full polarimetry SAR data known as PolSAR contains information in terms of microwave energy backscattered through different scattering mechanisms (surface-, double- and volume-scattering) by the targets on the surface of land. These scattering mechanisms information is different in different features. Similarly, different classifiers have different capabilities as far as identification of the targets corresponding to these scattering mechanisms. Extraction of different features and the role of classifier are important for the purpose of identifying which feature is the most suitable with which classifier for land cover classification. Selection of suitable features and their combinations have always been an active area of research for the development of advanced classification algorithms. Fully polarimetric data has its own advantages because its different channels give special scattering feature for various land cover. Therefore, first hand statistics HH, HV and VV of PolSAR data along with their ratios and linear combinations should be investigated for exploring their importance vis-à-vis relevant classifier for land management at the global scale. It has been observed that individually first hand statistics yield low accuracies. And their ratios are also not improving the results either. However, improved accuracies are achieved when these natural features are stacked together.IJAIN_vol1_vol4_no1.enl

Sulaiman, SarinaRahim, Nor Amalina AbdulPranolo, AndriGenerated rules for AIDS and e-learning classifier using rough set approach

International Journal of Advances in Intelligent Informatics

103-122222016

10.26555/ijain.v2i2.74

http://ijain.org/index.php/IJAIN/article/view/74

The emergence and growth of internet usage has accumulated an extensive amount of data. These data contain a wealth of undiscovered valuable information and problems of incomplete data set may lead to observation error. This research explored a technique to analyze data that transforms meaningless data to meaningful information. The work focused on Rough Set (RS) to deal with incomplete data and rules derivation. Rules with high and low left-hand-side (LHS) support value generated by RS were used as query statements to form a cluster of data. The model was tested on AIDS blog data set consisting of 146 bloggers and E-Learning@UTM (EL) log data set comprising 23105 URLs. 5-fold and 10-fold cross validation were used to split the data. Naïve algorithm and Boolean algorithm as discretization techniques and Johnson’s algorithm (Johnson) and Genetic algorithm (GA) as reduction techniques were employed to compare the results. 5-fold cross validation tended to suit AIDS data well while 10-fold cross validation was the best for EL data set. Johnson and GA yielded the same number of rules for both data sets. These findings are significant as evidence in terms of accuracy that was achieved using the proposed modelIJAIN_vol1_vol4_no1.enl

Mittal, AnupamAggarwal, RuchiKaur, SapinderAnalysis of energy efficient connected target coverage algorithm for static and dynamic nodes in IWSNs

International Journal of Advances in Intelligent Informatics

94-102222016

10.26555/ijain.v2i2.65

http://ijain.org/index.php/IJAIN/article/view/65

Today breakthroughs in wireless technologies have greatly spurred the emergence of industrial wireless sensor networks (IWSNs).To facilitate the adaptation of IWSNs to industrial applications, concerns about networks full coverage and connectivity must be addressed to fulfill reliability and real time requirements. Although connected target coverage algorithms have been studied notice both limitations and applicability of various coverage areas from an industry viewpoint. In this paper is discuss the two energy efficiency connected target coverage (CTC) algorithms CWGC(Communication Weighted Greedy Cover) and OTTC(Overlapped Target and Connected Coverage) algorithm based on dynamic node to resolve the problem of Coverage improvement. This paper uses the simulation in MATLAB represent the performance of two CTC algorithms with Dynamic node to improve network lifetime and low energy consumption and quality of service. Compare the dynamic nodes results with static nodes resultsIJAIN_vol1_vol4_no1.enl

Sasikaladevi, NSLA based cloud service composition using genetic algorithm

International Journal of Advances in Intelligent Informatics

77-87222016

10.26555/ijain.v2i2.58

http://ijain.org/index.php/IJAIN/article/view/58

Cloud computing tends to provide high quality on-demand services to the users. Numerous services are evolving today. Functionally similar services are having different non-functional properties such as reliability, availability, accessibility, response time and cost. A single service is inadequate for constructing the business process. Such business process is modeled as composite service. Composite service consists of several atomic services connected by workflow patterns. Selecting services for service composition with the constraints specified in Service Level Agreement is the NP-hard problem. Such a cloud service composition problem is modeled in this paper. Genetic based cloud service composition algorithm (GCSC) is proposed. Proposed algorithm is compared with the existing genetic based cloud service composition algorithm based on average utility rate and convergence time. It is proved that the proposed algorithm provides better performance as compared to the existing cloud service composition algorithm.IJAIN_vol1_vol4_no1.enl

Devadoss, Michael KamarajGanesan, BalakrishnanComparative analysis of multiple target tracking methods

International Journal of Advances in Intelligent Informatics

65-76222016

10.26555/ijain.v2i2.55

http://ijain.org/index.php/IJAIN/article/view/55

Many applications such as intelligent transportation, video surveillance, robotics of computer vision mainly depend on task of multiple object tracking. It includes the process of detection, classifications and tracking. The main focus of the study is to develop an efficient and effective multiple target tracking methods to solve the issues of illumination changes, occlusions and affinity matching. Accordingly, the various multiple target tracking methods are tested and evaluated using the metrics on publicly available datasets from which it is obvious that the outcome of the global energy minimization and optimization techniques is comparatively better than any other existing techniques in all aspects. This comparative study work will also help in better understanding of the problem, knowledge of the methods and experimental evaluation skill for further research works.IJAIN_vol1_vol4_no1.enl

Azimirad, EhsanHaddadnia, JavadA new model for threat assessment in data fusion based on fuzzy evidence theory

International Journal of Advances in Intelligent Informatics

54-64222016

10.26555/ijain.v2i2.56

http://ijain.org/index.php/IJAIN/article/view/56

In this paper a new method for threat assessment is proposed based on Fuzzy Evidence Theory. The most widely classical and intelligent methods used for threat assessment systems will be Evidence or Dempster Shafer and Fuzzy Sets Theories. The disadvantage of both methods is failing to calculate of uncertainty in the data from the sensors and the poor reliability of system. To fix this flaw in the system of dynamic targets threat assessment is proposed fuzzy evidence theory as a combination of both Dempster- Shafer and Fuzzy Sets Theories. In this model, the uncertainty in input data from the sensors and the whole system is measured using the best measure of the uncertainty. Also, a comprehensive comparison is done between the uncertainty of fuzzy model and fuzzy- evidence model (proposed method). This method applied to a real time scenario for air threat assessment. The simulation results show that this method is reasonable, effective, accuracy and reliability.IJAIN_vol1_vol4_no1.enl

Azhari, AhmadHernandez, LeonelBrainwaves feature classification by applying K-Means clustering using single-sensor EEG

International Journal of Advances in Intelligent Informatics

167-173232016

10.26555/ijain.v2i3.86

http://ijain.org/index.php/IJAIN/article/view/86

The use of brainwave signal is a step in the introduction of the individual identity using biometric technology based on characteristics of the body. Brainwave signal has unique characteristics and different on each individual because the brainwave cannot be read or copied by people so it is not possible to have a similarity of one person with another person. To be able to process the identification of individual characteristics, which obtained from the signal brainwave, required a pattern of brain activity that is prominent and constant. Cognitive activity testing using a single-sensor EEG (Electroencephalogram) divided into two categories, called the activity of cognitive involving the ability of the right brain (creativity, imagination, holistic thinking, intuition, arts, rhythms, nonverbal, feelings, visualization, tune of songs, daydreaming) and the left brain (logic, analysis, sequences, linear, mathematics, language, facts, think in words, word of songs, computation) give a different cluster based on two times the test on mathematical activities (no cluster slices of experiment 1 and experiment 2). The result showed that cognitive activity based on math activity can provide a signal characteristic that can be used as the basis for a brain-computer interface applications development by utilizing EEG single-sensor.IJAIN_vol1_vol4_no1.enl

Yunianta, ArdaYusof, NorazahBramantoro, ArifHaviluddin, HaviluddinOthman, Mohd ShahizanDengen, NatanielData mapping process to handle semantic data problem on student grading system

International Journal of Advances in Intelligent Informatics

157-166232016

10.26555/ijain.v2i3.84

http://ijain.org/index.php/IJAIN/article/view/84

Many applications are developed on education domain. Information and data for each application are stored in distributed locations with different data representations on each database. This situation leads to heterogeneity at the level of integration data. Heterogeneity data may cause many problems. One major issue is about the semantic relationships data among applications on education domain, in which the learning data may have the same name but with a different meaning, or learning data that has a different name with same meaning. This paper discusses on semantic data mapping process to handle semantic relationships problem on education domain. There are two main parts in the semantic data mapping process. The first part is the semantic data mapping engine to produce data mapping language with turtle (.ttl) file format as a standard XML file schema, that can be used for Local Java Application using Jena Library and Triple Store. The Turtle file contains detail information about data schema of every application inside the database system. The second part is to provide D2R Server that can be accessed from outside environment using HTTP Protocol. This can be done using SPARQL Clients, Linked Data Clients (RDF Formats) and HTML Browser. To implement the semantic data process, this paper focuses on the student grading system in the learning environment of education domain. By following the proposed semantic data mapping process, the turtle file format is produced as a result of the first part of the process. Finally, this file is used to be combined and integrated with other turtle files in order to map and link with other data representation of other applications.IJAIN_vol1_vol4_no1.enl

Purwaningsih, TutiMachmud, BaharudinInfluence of overweight and obesity on the diabetes in the world on adult people using spatial regression

International Journal of Advances in Intelligent Informatics

149-156232016

10.26555/ijain.v2i3.72

http://ijain.org/index.php/IJAIN/article/view/72

This research discussed about the case of diabetes, overweight, and obesity which aimed to determine the factors that most affect the number of adult people with Diabetes from Obesity and Overweight in the world and looking for the best spatial model to make predictions in the next period. This research based on data WHO in 2015 from The 2016 Global Nutrition Report. At 5% level of significance for 2015, factor that influence diabetes is obesity and the most excellent spatial model used in the analysis is Spatial Error Model (SEM) that use Weight Level Order 1 and has R2 value 81.82%.IJAIN_vol1_vol4_no1.enl

Sulandari, WinitaSubanar, SubanarSuhartono, SuhartonoUtami, HerniForecasting electricity load demand using hybrid exponential smoothing-artificial neural network model

International Journal of Advances in Intelligent Informatics

131-139232016

10.26555/ijain.v2i3.69

http://ijain.org/index.php/IJAIN/article/view/69

Short-term electricity load demand forecast is a vital requirements for power systems. This research considers the combination of exponential smoothing for double seasonal patterns and neural network model. The linear version of Holt-Winter method is extended to accommodate a second seasonal component. In this work, the Fourier with time varying coefficient is presented as a means of seasonal extraction. The methodological contribution of this paper is to demonstrate how these methods can be adapted to model the time series data with multiple seasonal pattern, correlated non stationary error and nonlinearity components together. The proposed hybrid model is started by implementing exponential smoothing state space model to obtain the level, trend, seasonal and irregular components and then use them as inputs of neural network. Forecasts of future values are then can be obtained by using the hybrid model. The forecast performance was characterized by root mean square error and mean absolute percentage error. The proposed hybrid model is applied to two real load series that are energy consumption in Bawen substation and in Java-Bali area. Comparing with other existing models, results show that the proposed hybrid model generate the most accurate forecastIJAIN_vol1_vol4_no1.enl

Sasikaladevi, NRETRACTED: Minimum makespan task scheduling algorithm in cloud computing

International Journal of Advances in Intelligent Informatics

123-130232016

10.26555/ijain.v2i3.59

http://ijain.org/index.php/IJAIN/article/view/59

RETRACTEDFollowing a rigorous, carefully concerns and considered review of the article published in International Journal of Advances in Intelligent Informatics to article entitled “Minimum makespan task scheduling algorithm in cloud computing” Vol 2, No 3, pp. 123-130, November 2016, DOI: http://dx.doi.org/10.26555/ijain.v2i3.59.This paper has been found to be in violation of the International Journal of Advances in Intelligent Informatics Publication principles and has been retracted.The article contained redundant material, the editor investigated and found that the paper published in International Journal of Grid and Distributed Computing, Vol. 9, No. 11, pp. 61-70, 2016, DOI: http://dx.doi.org/10.14257/ijgdc.2016.9.11.05.The document and its content has been removed from International Journal of Advances in Intelligent Informatics, and reasonable effort should be made to remove all references to this article.IJAIN_vol1_vol4_no1.enl

Latah, MajdHuman action recognition using support vector machines and 3D convolutional neural networks

International Journal of Advances in Intelligent Informatics

47-55312017

10.26555/ijain.v3i1.89

http://ijain.org/index.php/IJAIN/article/view/89

Recently, deep learning approach has been used widely in order to enhance the recognition accuracy with different application areas. In this paper, both of deep convolutional neural networks (CNN) and support vector machines approach were employed in human action recognition task. Firstly, 3D CNN approach was used to extract spatial and temporal features from adjacent video frames. Then, support vector machines approach was used in order to classify each instance based on previously extracted features. Both of the number of CNN layers and the resolution of the input frames were reduced to meet the limited memory constraints. The proposed architecture was trained and evaluated on KTH action recognition dataset and achieved a good performance.IJAIN_vol1_vol4_no1.enl

Prahara, AdhiAzhari, AhmadMurinto, MurintoVehicle pose estimation for vehicle detection and tracking based on road direction

International Journal of Advances in Intelligent Informatics

35-46312017

10.26555/ijain.v3i1.88

http://ijain.org/index.php/IJAIN/article/view/88

Vehicle has several types and each of them has different color, size, and shape. The appearance of vehicle also changes if viewed from different viewpoint of traffic surveillance camera. This situation can create many possibilities of vehicle poses. However, the one in common, vehicle pose usually follows road direction. Therefore, this research proposes a method to estimate the pose of vehicle for vehicle detection and tracking based on road direction. Vehicle training data are generated from 3D vehicle models in four-pair orientation categories. Histogram of Oriented Gradients (HOG) and Linear-Support Vector Machine (Linear-SVM) are used to build vehicle detectors from the data. Road area is extracted from traffic surveillance image to localize the detection area. The pose of vehicle which estimated based on road direction will be used to select a suitable vehicle detector for vehicle detection process. To obtain the final vehicle object, vehicle line checking method is applied to the vehicle detection result. Finally, vehicle tracking is performed to give label on each vehicle. The test conducted on various viewpoints of traffic surveillance camera shows that the method effectively detects and tracks vehicle by estimating the pose of vehicle. Performance evaluation of the proposed method shows 0.9170 of accuracy and 0.9161 of balance accuracy (BAC).IJAIN_vol1_vol4_no1.enl

Lastomo, DwiSetiadi, HerlambangDjalal, Muhammad RuswandiOptimization pitch angle controller of rocket system using improved differential evolution algorithm

International Journal of Advances in Intelligent Informatics

27-34312017

10.26555/ijain.v3i1.83

http://ijain.org/index.php/IJAIN/article/view/83

Pitch angle of rocket system is the important parts of the rocket. This part corresponds to the movement of the rocket system. Rocket system is fell into multi-input and multi-output (MIMO) system. The most challenge factor in MIMO system is designing the controller, if the design is not appropriate, it may lead to the unstable condition. Hence, appropriate and robust control design is inevitable. This paper introduces PID controller as pitch angle control of rocket system. Furthermore, PID controller parameter is optimized using improved differential evolution algorithm (IDEA). To analyze the performance of rocket system, time domain simulation is implemented. From the simulation result, it is found by using PID controller based on IDEA, the performance of pitch angle of rocket system is enhanced.IJAIN_vol1_vol4_no1.enl

Jayadianti, HerlinaSolving problem of semantic terminology in digital library

International Journal of Advances in Intelligent Informatics

20-26312017

10.26555/ijain.v3i1.70

http://ijain.org/index.php/IJAIN/article/view/70

Effective information access involves the semantic interaction between users in searching activity to diverse information in the Digital Library. This is the focus of this research. The weakness of the online library system that is running is the difficulty of users looking for data collection library. There are many different perceptions that have the same meaning (synonym) in in terms of library collections such as Author and Writer. Therefore, in this research will focus on mapping between terminologies that supports to detect different meaning of perceptions .This technique can be considered as an attempt to understand the difference between perceptions in the interaction between users and information in digital libraries.IJAIN_vol1_vol4_no1.enl

Giachos, IoannisPapakitsos, Evangelos C.Chorozoglou, GeorgiosExploring natural language understanding in robotic interfaces

International Journal of Advances in Intelligent Informatics

10-19312017

10.26555/ijain.v3i1.81

http://ijain.org/index.php/IJAIN/article/view/81

Natural Language Understanding is a major aspect of the intelligence of robotic systems. A main goal of improving their artificial intelligence is to allow a robot to ask questions, whenever the given instructions are not complete, and also by using implicit information. These enhanced communicational abilities can be based on the voids of an output data structure that corresponds to a systemic-semantic model of language communication, as grammar formalism. In addition, the enhancing process also improves the learning abilities of a robot. Accordingly, the presented herein experimental project was conducted by using a simulated (by a plain PC) robot and a simple constructed language that facilitated semantic orientation.IJAIN_vol1_vol4_no1.enl

Martono, Galih HendroSN, AzhariReview implementation of linguistic approach in schema matching

International Journal of Advances in Intelligent Informatics

1-9312017

10.26555/ijain.v3i1.75

http://ijain.org/index.php/IJAIN/article/view/75

Research related schema matching has been conducted since last decade. Few approach related schema matching has been conducted with various methods such as neuron network, feature selection, constrain based, instance based, linguistic, and so on. Some field used schema matching as basic model such as e-commerce, e-business and data warehousing. Implementation of linguistic approach itself has been used a long time with various problem such as to calculated entity similarity values in two or more schemas. The purpose of this paper was to provide an overview of previous studies related to the implementation of the linguistic approach in the schema matching and finding gap for the development of existing methods. Futhermore, this paper focused on measurement of similarity in linguistic approach in schema matching.IJAIN_vol1_vol4_no1.enl

Nurhab, Muhamad IrpanNurhab, BadaruddinPurwaningsih, TutiTeng, Ming FoeyCircular(2)-linear regression analysis with iteration order manipulation

International Journal of Advances in Intelligent Informatics

107-116322017

10.26555/ijain.v3i2.90

http://ijain.org/index.php/IJAIN/article/view/90

The selection of statistical analysis techniques to be used must be adjusted to the data. Data in the form of time cycle or point position to the angle of possibility is no longer suitable to be analyzed using classical linear statistic method because the direction and the angle influence the position between one data with other data. This paper aims to examine the comparison of Linear Regression Analysis with Circular Regression Analysis. The writing method used is literature review using simulation data. Simulation of data and analysis is done with the help of R program. The results showed that circular data is better in Circular Regression Analysis than Classical Linear Regression Analysis, so the conclusion is Selection of statistical analysis techniques to be used must be adjusted with the data that already held. Data in the form of time cycles or position of the point to the angle of probability is no longer suitable to be analyzed using classical linear statistic method because the direction and the angle influence the position between one data with other data.IJAIN_vol1_vol4_no1.enl

Purwaningsih, TutiGhosh, AnusuaChumairoh, ChumairohSpatial data modeling in disposable income per capita in china using nationwide spatial autoregressive (SAR)

International Journal of Advances in Intelligent Informatics

98-106322017

10.26555/ijain.v3i2.93

http://ijain.org/index.php/IJAIN/article/view/93

China as a country became the economic center of the world. However, with a population of 1.3 billion, China's per capita income is still at number 80 in the world. In the world, considering the imbalance between town and country with 100 million people still living in poverty. Thus, to address this imbalance, it is necessary to study the condition in depth, because income per capita is often used as a benchmark to measure the prosperity of a country. With greater and equitable income per capita, the country will be judged increasingly affluent. Two factors, mainly industry and tourism, play an important role in the economic progress in China. These are include Per capita Disposable Income Nationwide (yuan), Total Value of Exports of operating units (1,000 USD), Registered Unemployed Person in Urban Area (10000 person), Foreign Exchange Earning from International tourism(in millions USD) and Number of Overseas Visitor Arrivals (million person/time). Thus, it is necessary to investigate the influence of these factors to increase per capita income. Since the economic development of a region usually affect the surrounding area, this study aims to include spatial effects, using Spatial Autoregressive (SAR) Model. The results suggest that the per capita income affected by the Tourism factor is about 58.65% (R-squared).IJAIN_vol1_vol4_no1.enl

Editya, Arda SuryaSumpeno, SuryaPratomo, IstasPerformance IEEE 802.14.5 and zigbee protocol on realtime monitoring augmented reality based wireless sensor network system

International Journal of Advances in Intelligent Informatics

90-97322017

10.26555/ijain.v3i2.99

http://ijain.org/index.php/IJAIN/article/view/99

The internet of Thing (IoT)technology has much development in this era. It has various wireless media transmission systems such as ESP and XBEE. Some IoT device can monitor website or application. On the other hand, Augmented Reality (AR) is a technology that used more on the entertainment sector. Here, we try to use AR to monitor the xbee based IoT device. As a result, there is the different result between Zigbee Protocol and IEEE 802.14.5 real time monitoring system. The optimum estimation of realtime time tolerance of those monitoring systems is >1500 ms (IEEE 804.14.5) and > 50 ms (Zigbee protocol).IJAIN_vol1_vol4_no1.enl

Novianti, PepiSetyorini, DyahRafflesia, UlfasariK-Means cluster analysis in earthquake epicenter clustering

International Journal of Advances in Intelligent Informatics

81-89322017

10.26555/ijain.v3i2.100

http://ijain.org/index.php/IJAIN/article/view/100

Bengkulu Province, Indonesia, which lies in two active faults, Semangko fault and Mentawai fault, is an area that has high seismic activity. As earthquake-prone area, the characteristic of each earthquake in Bengkulu Province needs to be studied. This paper presents the earthquake epicenter clustering in Bengkulu Province. Tectonic earthquake data at Bengkulu Province and surrounding areas from January 1970 to December 2015 are used. The data is taken from single-station Agency Meteorology, Climatology and Geophysics (BMKG) Kepahiang Bengkulu. K-Means clustering using Euclidean distance method is used in this analysis. The variables are latitude, longitude and magnitude. The optimum number of cluster is determined using Krzanowski and Lai (KL) index which is 7. The analysis for each clustering experiment with variation number of cluster is presented.IJAIN_vol1_vol4_no1.enl

Munandar, DeviWavelet discrete transform, ANFIS and linear regression for short-term time series prediction of air temperature

International Journal of Advances in Intelligent Informatics

68-80322017

10.26555/ijain.v3i2.101

http://ijain.org/index.php/IJAIN/article/view/101

This paper investigates the ability of Discrete Wavelet Transform and Adaptive Network-Based Fuzzy Inference System in time-series data modeling of weather parameters. Plotting predicted data results on Linear Regression is used as the baseline of the statistical model. Data were tested in every 10 minutes interval on weather station of Bungus port in Padang, Indonesia. Mean absolute errors (MAE), the coefficient of determination (R2), Pearson correlation coefficient (r) and root mean squared error (RMSE) are used as performance indicators. The result of Plotting ANFIS data against linear regression using 1-input data is the optimal values combination of output predictions.IJAIN_vol1_vol4_no1.enl

Hashim, Ummi RabaahMohd Hashim, Siti ZaitonMuda, Azah KamilahKanchymalay, KasturiAbd Jalil, Intan ErmahaniOthman, Muhammad HakimSystematic feature analysis on timber defect images

International Journal of Advances in Intelligent Informatics

56-67322017

10.26555/ijain.v3i2.94

http://ijain.org/index.php/IJAIN/article/view/94

Feature extraction is unquestionably an important process in a pattern recognition system. A defined set of features makes the identification task more efficiently. This paper addresses the extraction and analysis of features based on statistical texture to characterize images of timber defects. A series of procedures including feature extraction and feature analysis was executed to construct an appropriate feature set that could significantly separate amongst defects and clear wood classes. The feature set aimed for later use in a timber defect detection system. For Accessing the discrimination capability of the features extracted, visual exploratory analysis and confirmatory statistical analysis were performed on defect and clear wood images of Meranti (Shorea spp.) timber species. Results from the analysis demonstrated that there was a significant distinction between defect classes and clear wood utilizing the proposed set of texture features.IJAIN_vol1_vol4_no1.enl

Yunianta, ArdaBarukab, Omar MohammedYusof, NorazahDengen, NatanielHaviluddin, HaviluddinOthman, Mohd ShahizanSemantic data mapping technology to solve semantic data problem on heterogeneity aspect

International Journal of Advances in Intelligent Informatics

161-172332017

10.26555/ijain.v3i3.131

http://ijain.org/index.php/IJAIN/article/view/131

The diversity of applications developed with different programming languages, application/data architectures, database systems and representation of data/information leads to heterogeneity issues. One of the problem challenges in the problem of heterogeneity is about heterogeneity data in term of semantic aspect. The semantic aspect is about data that has the same name with different meaning or data that has a different name with the same meaning. The semantic data mapping process is the best solution in the current days to solve semantic data problem. There are many semantic data mapping technologies that have been used in recent years. This research aims to compare and analyze existing semantic data mapping technology using five criteria’s. After comparative and analytical process, this research provides recommendations of appropriate semantic data mapping technology based on several criteria’s. Furthermore, at the end of this research we apply the recommended semantic data mapping technology to be implemented with the real data in the specific application. The result of this research is the semantic data mapping file that contains all data structures in the application data source. This semantic data mapping file can be used to map, share and integrate with other semantic data mapping from other applications and can also be used to integrate with the ontology language.IJAIN_vol1_vol4_no1.enl

Riyadi, Mohammad Alfan AlfianPratiwi, Dian SukmaIrawan, Aldho RiskiFithriasari, KartikaClustering stationary and non-stationary time series based on autocorrelation distance of hierarchical and k-means algorithms

International Journal of Advances in Intelligent Informatics

154-160332017

10.26555/ijain.v3i3.98

http://ijain.org/index.php/IJAIN/article/view/98

Observing large dimension time series could be time-consuming. One identification and classification approach is a time series clustering. This study aimed to compare the accuracy of two algorithms, hierarchical cluster and K-Means cluster, using ACF’s distance for clustering stationary and non-stationary time series data. This research uses both simulation and real datasets. The simulation generates 7 stationary data models and another 7 of non-stationary data models. On the other hands, the real dataset is the daily temperature data in 34 cities in Indonesia. As a result, K-Means algorithm has the highest accuracy for both data models.IJAIN_vol1_vol4_no1.enl

Hoar Siki, Yovinia CarmenejaMamulak, Natalia Magdalena RafuTime-frequency analysis on gong timor music using short-time fourier transform and continuous wavelet transform

International Journal of Advances in Intelligent Informatics

146-153332017

10.26555/ijain.v3i3.114

http://ijain.org/index.php/IJAIN/article/view/114

Time-Frequency Analysis on Gong Timor Music has an important role in the application of signal-processing music such as tone tracking and music transcription or music signal notation. Some of Gong characters is heard by different ways of forcing Gong himself, such as how to play Gong based on the Player’s senses, a set of Gong, and by changing the tempo of Gong instruments. Gong's musical signals have more complex analytical criteria than Western music instrument analysis. This research uses a Gong instrument and two notations; frequency analysis of Gong music frequency compared by the Short-time Fourier Transform (STFT), Overlap Short-time Fourier Transform (OSTFT), and Continuous Wavelet Transform (CWT) method. In the STFT and OSTFT methods, time-frequency analysis Gong music is used with different windows and hop size while CWT method uses Morlet wavelet. The results show that the CWT is better than the STFT methods.IJAIN_vol1_vol4_no1.enl

Hussien, Nur SyahelaSulaiman, SarinaShamsuddin, Siti MariyamUsability testing on intelligent mobile web pre-fetching of cloud storage scheme

International Journal of Advances in Intelligent Informatics

134-145332017

10.26555/ijain.v3i3.129

http://ijain.org/index.php/IJAIN/article/view/129

Mobile device and Cloud Storage (CS) represent the trends of technology usage of the last few years. However, the difficulty in managing the data when there are too many simultaneous uses of cloud storage services at the same time that can cause latency or delayed time. This paper evaluates mobile cloud storage services using usability testing, which is intended to access by multiple of Cloud Storage Services (CSS) with the proposed Intelligent Mobile Web Pre-fetching of Cloud Storage Scheme (MOBICS). The results show most of the respondents with 95.65% agreeing that MOBICS system was very practical and has enhanced the speed in accessing and storing data by Mobile Cloud Storage (MCS). Besides, MOBICS reduces time of interaction up to 19.28% for the local pre-fetching and 18.80% for the intelligent pre-fetching.IJAIN_vol1_vol4_no1.enl

Azhari, AhmadMardhia, Murein MiksaPrincipal component analysis implementation for brainwave signal reduction based on cognitive activity

International Journal of Advances in Intelligent Informatics

125-133332017

10.26555/ijain.v3i3.118

http://ijain.org/index.php/IJAIN/article/view/118

Human has the ability to think that comes from the brain. Electrical signals generated by brain and represented in wave form. To record and measure the activity of brainwaves in the form of electrical potential required electroencephalogram (EEG). In this study a cognitive task is applied to trigger a specific human brain response arising from the cognitive aspect. Stimulation is given by using nine types of cognitive tasks including breath, color, face, finger, math, object, password thinking, singing, and sports. Principal component analysis (PCA) is implemented as a first step to reduce data and to get the main component of feature extraction results obtained from EEG acquisition. The results show that PCA succeeded reducing 108 existing datasets to 2 prominent factors with a cumulative rate of 65.7%. Factor 1 (F1) includes mean, standard deviation, and entropy, while factor 2 (F2) includes skewness and kurtosis.IJAIN_vol1_vol4_no1.enl

Voliansky, RomanTransformation of the generalized chaotic system into canonical form

International Journal of Advances in Intelligent Informatics

117-124332017

10.26555/ijain.v3i3.113

http://www.ijain.org/index.php/IJAIN/article/view/113

The paper deals with the developing of the numerical algorithms for transformation of generalized chaotic system into canonical form. Such transformation allows us to simplify control algorithm for chaotic system. These algorithms are defined by using Lie derivatives for output variable and solution of nonlinear equations. Usage of proposed algorithm is one of the ways for discovering of new chaotic attractors. These attractors can be obtained by transformation of known chaotic systems into various state spaces. Transformed attractors depend on both parameters of chaotic system and sample time of its discrete model.IJAIN_vol1_vol4_no1.enl

Apriani, AniTri Riyadi Yanto, IwanFathurrohmah, SeptianaHaryatmi, SriDanardono, DanardonoVariable precision rough set model for attribute selection on environment impact dataset

International Journal of Advances in Intelligent Informatics

70-75412018

10.26555/ijain.v4i1.109

http://ijain.org/index.php/IJAIN/article/view/109

The investigation of environment impact have important role to development of a city. The application of the artificial intelligence in form of computational models can be used to analyze the data. One of them is rough set theory. The utilization of data clustering method, which is a part of rough set theory, could provide a meaningful contribution on the decision making process. The application of this method could come in term of selecting the attribute of environment impact. This paper examine the application of variable precision rough set model for selecting attribute of environment impact. This mean of minimum error classification based approach is applied to a survey dataset by utilizing variable precision of attributes. This paper demonstrates the utilization of variable precision rough set model to select the most important impact of regional development. Based on the experiment, The availability of public open space, social organization and culture, migration and rate of employment are selected as a dominant attributes. It can be contributed on the policy design process, in term of formulating a proper intervention for enhancing the quality of social environment.IJAIN_vol1_vol4_no1.enl

Prasetya, Didik DwiPrasetya Wibawa, AjiHirashima, TsukasaThe performance of text similarity algorithms

International Journal of Advances in Intelligent Informatics

63-69412018

10.26555/ijain.v4i1.152

http://ijain.org/index.php/IJAIN/article/view/152

Text similarity measurement compares text with available references to indicate the degree of similarity between those objects. There have been many studies of text similarity and resulting in various approaches and algorithms. This paper investigates four majors text similarity measurements which include String-based, Corpus-based, Knowledge-based, and Hybrid similarities. The results of the investigation showed that the semantic similarity approach is more rational in finding substantial relationship between texts.IJAIN_vol1_vol4_no1.enl

Sunardi, SunardiMahfurdz, AzrulSaifullah, ShoffanGreen turtle and fish identification based on acoustic target strength

International Journal of Advances in Intelligent Informatics

53-62412018

10.26555/ijain.v4i1.147

http://ijain.org/index.php/IJAIN/article/view/147

Fisherman accidentally caught sea turtles in their fishnet. It could be dangerous for its population. This study measures the turtle target strength (TS) using modified echosounder. The result could be used to improve the efficiency of turtle repellent device. The experiment conducted in a hatchery fiber tank contained saline water. The Green were 1, 3, 12 and 18 years old. The study used three species of fish to ensure there are no overlapped value between fish and sea turtle. TS of the animals were calculated incorporating reference targets (sphere). The echo power of the turtle was compared with the solid steel sphere which is confirmed good agreements with the theoretical values. The echo power reference by applying Fast Fourier Transform (FFT) analysis has been used in calculating TS of the animal. From the echo evaluation in time domain at different angles, it is obviously shown that echo signal structure is different between the parts of turtle body. This study reveals that high echo strength is acquired from the carapace and the plastron parts. The finding also showed that there are significant differences between 3, 12, 18 years old turtles and fish in every angle measurement.IJAIN_vol1_vol4_no1.enl

Suhartono, SuhartonoKurniawan, FachrulImran, BahtiarIdentification of virtual plants using bayesian networks based on parametric L-system

International Journal of Advances in Intelligent Informatics

40-52412018

10.26555/ijain.v4i1.157

http://ijain.org/index.php/IJAIN/article/view/157

Parametric L-System is a method for modelling virtual plants. Virtual plant modelling consists of components of axiom and production rules for alphabets in parametric L-System. Generally, to get the alphabet in parametric L-System, one would guess the production rules and perform a modification on the axiom. The objective of this study was to build virtual plant that was affected by the environment. The use of Bayesian networks was to extract the information structure of the growth of a plant as affected by the environment. The next step was to use the information to generate axiom and production rules for the alphabets in the parametric L-System. The results of program testing showed that among the five treatments, the combination of organic and inorganic fertilizer was the environmental factor for the experiment. The highest result of 6.41 during evaluation of the virtual plant came from the treatment with combination of high level of organic fertilizer and medium level of inorganic fertilizer. Mean error between real plant and virtual plan was 9.45 %.IJAIN_vol1_vol4_no1.enl

Primasari, Clara HettyWardoyo, RetantyoSari, Anny KartikaIntegrated AHP, Profile Matching, and TOPSIS for selecting type of goats based on environmental and financial criteria

International Journal of Advances in Intelligent Informatics

28-39412018

10.26555/ijain.v4i1.105

http://ijain.org/index.php/IJAIN/article/view/105

Goat farm businessman should considered environmental and financial criteria in breeding their commodities. The environmental factors are temperature, humidity, rain intensity, and altitude. For financial criteria, used several sub criteria i.e NPV (Net Present Value), ROI (Return On Investment), BCR (Benefit Cost Ratio), PBP (Payback Period), and BEP (Break Event Point) to determine financial feasibility. This research aims to develop a decision support system for selecting type of goat to breed by combining AHP, Profile Matching, and TOPSIS. AHP method was used for calculating the weight, Profile Matching for environment suitability evaluation, and TOPSIS for producing a valid decision that represents the goat expert's decision. The result showed that three methods can be integrated, and an experimental results which was validated by expert show that Bligon goat had the highest preference value (0.8835847). This can be concluded that DSS decision was valid and it successfully represented expert’s consideration.IJAIN_vol1_vol4_no1.enl

Hartono, HartonoSitompul, Opim SalimTulus, TulusNababan, Erna BudhiartiBiased support vector machine and weighted-smote in handling class imbalance problem

International Journal of Advances in Intelligent Informatics

21-27412018

10.26555/ijain.v4i1.146

http://ijain.org/index.php/IJAIN/article/view/146

Class imbalance occurs when instances in a class are much higher than in other classes. This machine learning major problem can affect the predicted accuracy. Support Vector Machine (SVM) is robust and precise method in handling class imbalance problem but weak in the bias data distribution, Biased Support Vector Machine (BSVM) became popular choice to solve the problem. BSVM provide better control sensitivity yet lack accuracy compared to general SVM. This study proposes the integration of BSVM and SMOTEBoost to handle class imbalance problem. Non Support Vector (NSV) sets from negative samples and Support Vector (SV) sets from positive samples will undergo a Weighted-SMOTE process. The results indicate that implementation of Biased Support Vector Machine and Weighted-SMOTE achieve better accuracy and sensitivity.IJAIN_vol1_vol4_no1.enl

Latah, MajdToker, LeventA novel intelligent approach for detecting DoS flooding attacks in software-defined networks

International Journal of Advances in Intelligent Informatics

11-20412018

10.26555/ijain.v4i1.138

http://ijain.org/index.php/IJAIN/article/view/138

Software-Defined Networking (SDN) is an emerging networking paradigm that provides an advanced programming capability and moves the control functionality to a centralized controller. This paper proposes a two-stage novel intelligent approach that takes advantage of the SDN approach to detect Denial of Service (DoS) flooding attacks based on calculation of packet rate as the first step and followed by Support Vector Machine (SVM) classification as the second step. Flow concept is an essential idea in OpenFlow protocol, which represents a common interface between an SDN switch and an SDN controller. Therefore, our system calculates the packet rate of each flow based on flow statistics obtained by SDN controller. Once the packet rate exceeds a predefined threshold, the system will activate the packet inspection unit, which, in turn, will use the (SVM) algorithm to classify the previously collected packets. The experimental results showed that our system was able to detect DoS flooding attacks with 96.25% accuracy and 0.26% false alarm rate.IJAIN_vol1_vol4_no1.enl

Rathomi, Muhamad RadziPulungan, RezaA coarse-grained parallelization of genetic algorithms

International Journal of Advances in Intelligent Informatics

1-10412018

10.26555/ijain.v4i1.137

http://ijain.org/index.php/IJAIN/article/view/137

Genetic algorithms are frequently used to solve optimization problems. However, the problems become increasingly complex and time consuming. One solution to speed up the genetic algorithm processing is to use parallelization. The proposed parallelization method is coarse-grained and employs two levels of parallelization: message passing with MPI and Single Instruction Multiple Threads with GPU. Experimental results show that the accuracy of the proposed approach is similar to the sequential genetic algorithm. Parallelization with coarse-grained method, however, can improve the processing and convergence speed of genetic algorithms.