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Journal of Information Technology and Computer Science

jitecs
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Published by Universitas Brawijaya

ISSN : 25409433 EISSN : 25409824 DOI : -

Core Subject : Science, Engineering,

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

The Journal of Information Technology and Computer Science (JITeCS) is a peer-reviewed open access journal published by Faculty of Computer Science, Universitas Brawijaya (UB), Indonesia. The journal is an archival journal serving the scientist and engineer involved in all aspects of information technology, computer science, computer engineering, information systems, software engineering and education of information technology. JITeCS publishes original research findings and high quality scientific articles that present cutting-edge approaches including methods, techniques, tools, implementations and applications.

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Articles 12 Documents

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Search results for , issue "Vol. 4 No. 1: June 2019" : 12 Documents clear

Open Source Geospatial Solution for Disseminating Green Park Information Paul, Arati; Mondal, Rabi Sankar; Chakraborty, Debasish
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Green parks and open spaces are indispensable parts of an urban environment as they play important roles in promoting public health, protecting natural ecosystems and improving socioeconomic conditions of the city dwellers. Hence, the information of green and open spaces in a city needs to be provided to its governing authority and people for better management and utilisation. WebGIS technology is capable of maintaining and disseminating green park information among its users over the web. The availability of open source geospatial software and tools made this technology more cost effective and acceptable to the user community. In present study an interactive and user friendly WebGIS enabled solution is developed for green parks of Kolkata city that facilitates city dwellers and decision makers to search and visualise green parks both on map and satellite image along with park information and ground photo. It is an easy deployable solution that helps in urban planning for creating new as well as preserving the existing green spaces.

Intelligent Computing System to Predict Vocational High School Student Learning Achievement Using NaÃ¯ve Bayes Algorithm Herlambang, Admaja Dwi; Wijoyo, Satrio Hadi; Rachmadi, Aditya
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Vocational High School with ICT major need an intelligent computing system that could predict the student learning achievement. The system used fifteen achievement indicators and NaÃ¯ve Bayes algorithm in data processing. Testing on student achievement data produces the conclusion that is the highest intelligent accuracy values in 53% with lowest accuracy value in 48% based on NaÃ¯ve Bayes algorithm processing. The result of mining process using NaÃ¯ve Bayes algorithm can be used to classify the 3rd year student achievement to five categories. These categories are Very Good, Good, Fair, Poor, and Failed. The system testing result showed that this intelligent computing system function was fitted with Vocational High Schoolâ€™s system requirement, system design, and system implementation.

Utilization of Current Data for Geospatial Analysis of the Appropriateness of Apple Plantation Land Based on Fuzzy Inference Systems Lestantyo, Prayudi; Ramdani, Fatwa; Mahmudy, Wayan Firdaus
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Apple is a high-value import fruit in Indonesia. One of the Apple production centers in Indonesia is Batu City, but the results tend to be declining in every year. To fulfill the demand of domestic apple industry, it is than a must to open new plantation land by observing the spatial factor. Expert and direct field review are needed to perform the analysis of land suitability, so that it will takes a lot of time and effort. Therefore, a smart system that can conduct geospatial analysis by using fuzzy inference system is developed. The data was obtained by using satellite imagery, data interpolation, and digitized and then analyzed into information. The analysis was performed on each pixel with six variable inputs including altitude, rainfall, humidity, air temperature, soil type and sun shine intensity. Besides that, the five-clustering output makes the results more accurate. From the results of the accuracy test, it is obtained a 92,86% accuracy, by comparing the results of the spatial analysis using fuzzy inference system with direct review on the field.

Using Guided Initial Chromosome of Genetic Algorithm for Scheduling Production-Distribution System Rody, Rafiuddin; Mahmudy, Wayan Firdaus; Tama, Ishardita Pambudi
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Production and distribution system in a company should be managed carefully. Delay in product delivery not only results in a late penalty due to customer dissatisfaction or breach of contract, but also causes a supply chain failure. Of course, all these impacts will also reduce the reputation of a company. Scheduling integrated production-distribution is classified as NP-Hard problem. Genetic algorithm can be used to solve complex problem. In this paper, genetic algorithm is used for scheduling production-distribution in make to order system where each job has a different deadline and volume (size). This problem is represented on mixed integer programing model. We verify the genetic algorithmâ€™s performance by comparing the results with the total cost calculated by lower bounds of the problems. Experiments show that the traditional initial random cannot produce good result with more than 15 job size problem. We proposed guided initial chromosome to tackle this problem. From further experiments shows that the proposed method approach can increase the performances of genetic algorithm in more than 15 job size problem. In general, proposed genetic algorithm with guided initial chromosome shows better solution quality and better time efficiency compared to previous related research.

Measuring User Assessments and Expectations: The Use of WebQual 4.0 Method and Importance-Performance Analysis (IPA) to Evaluate the Quality of School Websites Syahidi, Aulia Akhrian; Asyikin, Arifin Noor; Subandi, Subandi
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

As time goes by and technology advances, any information can be easily obtained from many media, both from various print media or digital electronic media. One of the fastest growing digital media and the main choice for individuals or agencies to get fast and accurate information is the website. One of the benefits of the website is that it can be used as an effective promotional media because it can be accessed by anyone and at any time. This study discusses the evaluation of school websites with a case study at the SMK Muhammadiyah 1 Banjarmasin using the WebQual 4.0 and Importance-Performance Analysis (IPA) methods. This study aims to measure user ratings of performance and expectations of users/visitors to the website of the SMK Muhammadiyah 1 Banjarmasin. The data in this study were obtained from the questionnaire using a sample of web visitors themselves, both through online based questionnaires and offline questionnaires with paper. This study uses data processing software, namely Structural Equation Modeling (SEM) 2.0. It can be concluded that in this study the results are measured by the level of performance (actual) and the level of importance (expectations) which shows that there is an overall gap for all dimensions -0.38 ie the website needs improvement and tends to still not be as expected. The biggest gap is in the Usability dimension with the largest value being -1.07 on USE5 variables, which means that the appearance of this website tends to be unattractive, not in line with expectations, and needs improvement. Then the acquisition of the value of R Square for the variable user satisfaction is 0.61, which means that the value indicates that the variable user satisfaction can be explained by usability, information quality, and service interaction with a value of 67.7%, while the remaining 32.3% is influenced by variables others not found in the research model.

An Exploratory Study of Requirements Engineering Practices in Indonesia â€“ Part 1: Concepts and Problems Kurniawan, Tri A.; Rusdianto, Denny S.; Brata, Adam H.; Amalia, Faizatul; Santoso, Angga; Raharjo, Dini I. N. R. P.
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

This paper provides the first part of statistical research findings of an exploratory study of the requirements engineering practices implemented in software development processes in Indonesia. This first part attempts to reveal facts regarding concepts and problems exist in such requirements engineering practices. We developed a comprehensive online questionnaire consisting of both closed- and open-ended questions in order to capture such facts. We invited 158 participant candidates representing industry and higher education institutions, however, 31 of them joined our web-based survey. Results show that most of participants confirm that requirements engineering must be properly performed in order to clearly define the valid product. They, however, encounter some difficulties in implementing requirements engineering concepts in practice due to a tight schedule, inappropriate skill of the analysts and inadequate tools used.

Improve Hybrid Particle Swarm Optimization and K-Means for Clustering Auliya, Yudha Alif; Mahmudy, Wayan Firdaus; Sudarto, Sudarto
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Abstract. Potato production is strongly influenced by the selection of suitable land for crops. Criteria for land suitability of planting potatoes is influenced by climatic factors and land characteristics. planted area clustered based on 11 criteria land suitability. The clustering results in the form of four clusters, namely: very suitable (S1), appropriate (S2), is quite suitable (S3) and are not suitable (N). Clustering of land aims to improve the quality and quantity of the potato crop. Clustering is done using a hybrid Particle Swarm Optimization with K-Means (KCPSO). The hybrid method is used to obtain an accurate result cluster. In this study used a new approach to doing improve KCPSO with random injection method. The calculation of the value of cost based on the silhouette coefficient. The results obtained KCPSO showed better results when compared to using the K-Means algorithm without hybrid. The calculation result KCPSO get the best centroid indicated by the value of the largest Silhouette coefficient.Keywords: Clustering, K-Means, Particle Swarm Optimization, random injection, silhouette Coefficient.

Web-based Application for Visual Representation of Learners' Problem-Posing Learning Pattern Supianto, Ahmad Afif; Wicaksono, Satrio Agung; Bachtiar, Fitra A.; Herlambang, Admaja Dwi; Hayashi, Yusuke; Hirashima, Tsukasa
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Studentsâ€™ learning process analysis normally involves massive amount of data. This study explores the pattern and relationship of studentsâ€™ learning process data in an interactive learning media to identify their learning process patterns to ease the needs of sophisticated data analysis for class instructors and educational researchers. This study focuses on the development of a web-based software application that creates a visual representation of studentsâ€™ learning process in a learning media. The result of this software is a visualization of studentsâ€™ activity sequence. This result is then used to infer studentsâ€™ learning patterns as well as identifying their learning behavior and to create a better feedback via the learning instructors. As a case study, this research uses the data log of Monsakun, a digital learning environment that focuses on the subject of mathematic for grade school students on the topic of arithmetic using story-based question and problem-posing approach. Investigation result shows four distinct learning activity patterns which are: smart pattern, adventure pattern, peer pattern and cyclic pattern. Each pattern requires different feedback to optimize learning progression, by using this web-based application, appropriate feedback to specific learning pattern is then applied to each student based on its learning activity pattern.

Texture Feature On Determining Quantity of Soil Organic Matter For Patchouli Plant Using Backpropagation Neural Network Dewi, Candra; Sundari, Suci; Mardji, Mardji
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Patchouli (Pogostemon Cablin Bent) has higher PA (Patchouli Alcohol) and oil production if grown in soil containing 75% organic matter. One way that can be used to detect the content of organic matter is to use soil images. The problem in the use of soil images is the color of the soil that is almost similar, namely the gradation between dark brown to black. Therefore, color features are not enough to be used as input in the recognition process. For this purposes, texture features are added in this study in addition to color features. The color features are extracted using color moment and the texture features are extracted using Gray Level Co-occurrence Matrix (GLCM). These feature was then chosen to get the best combination as input in the identification process using the Backpropagation Neural Network (BPNN). The system identifies the quantity of soil organic matter into five classes, namely very low, low, medium, high, and very high. The highest accuracy result obtained was 73% and MSE value 0.5122 by using five GLCM features (Angular Second Moment, contrast, correlation, Inverse Difference Moment, and entropy). This result was obtained by using the BPNN parameter, namely learning rate values 0.5, maximum iteration values of 1000, number training data 210, and total test data 12.

Cover and Table of Contens Purbosari, Lina
Journal of Information Technology and Computer Science Vol. 4 No. 1: June 2019
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Cover and Table of Contens Vol 4 No 1 June 2019

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