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International Journal of Advances in Intelligent Informatics
Published by Universitas Ahmad Dahlan
ISSN : 24426571     EISSN : 25483161     DOI : 10.26555
Core Subject : Science,
Computer Science & IT
International journal of advances in intelligent informatics (IJAIN) e-ISSN: 2442-6571 is a peer reviewed open-access journal published three times a year in English-language, provides scientists and engineers throughout the world for the exchange and dissemination of theoretical and practice-oriented papers dealing with advances in intelligent informatics. All the papers are refereed by two international reviewers, accepted papers will be available on line (free access), and no publication fee for authors.
Arjuna Subject : -
Articles 330 Documents
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K-Means cluster analysis in earthquake epicenter clustering Pepi Novianti; Dyah Setyorini; Ulfasari Rafflesia
International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i2.100

Abstract

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.
Generated rules for AIDS and e-learning classifier using rough set approach Sarina Sulaiman; Nor Amalina Abdul Rahim; Andri Pranolo
International Journal of Advances in Intelligent Informatics Vol 2, No 2 (2016): July 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i2.74

Abstract

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 model
A new model for threat assessment in data fusion based on fuzzy evidence theory Ehsan Azimirad; Javad Haddadnia
International Journal of Advances in Intelligent Informatics Vol 2, No 2 (2016): July 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i2.56

Abstract

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.
Spatial data modeling in disposable income per capita in china using nationwide spatial autoregressive (SAR) Tuti Purwaningsih; Anusua Ghosh; Chumairoh Chumairoh
International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i2.93

Abstract

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).
Optimization pitch angle controller of rocket system using improved differential evolution algorithm Dwi Lastomo; Herlambang Setiadi; Muhammad Ruswandi Djalal
International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i1.83

Abstract

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.
Analysis of energy efficient connected target coverage algorithm for static and dynamic nodes in IWSNs Anupam Mittal; Ruchi Aggarwal; Sapinder Kaur
International Journal of Advances in Intelligent Informatics Vol 2, No 2 (2016): July 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i2.65

Abstract

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 results
Performance IEEE 802.14.5 and zigbee protocol on realtime monitoring augmented reality based wireless sensor network system Arda Surya Editya; Surya Sumpeno; Istas Pratomo
International Journal of Advances in Intelligent Informatics Vol 3, No 2 (2017): July 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i2.99

Abstract

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).
Review implementation of linguistic approach in schema matching Galih Hendro Martono; Azhari SN
International Journal of Advances in Intelligent Informatics Vol 3, No 1 (2017): March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v3i1.75

Abstract

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.
Comparative analysis of multiple target tracking methods Michael Kamaraj Devadoss; Balakrishnan Ganesan
International Journal of Advances in Intelligent Informatics Vol 2, No 2 (2016): July 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i2.55

Abstract

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.
Brainwaves feature classification by applying K-Means clustering using single-sensor EEG Ahmad Azhari; Leonel Hernandez
International Journal of Advances in Intelligent Informatics Vol 2, No 3 (2016): November 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v2i3.86

Abstract

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.

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