Jurnal Teknik Informatika (JUTIF)
Jurnal Teknik Informatika (JUTIF) is an Indonesian national journal, publishes high-quality research papers in the broad field of Informatics, Information Systems and Computer Science, which encompasses software engineering, information system development, computer systems, computer network, algorithms and computation, and social impact of information and telecommunication technology. Jurnal Teknik Informatika (JUTIF) is published by Informatics Department, Universitas Jenderal Soedirman twice a year, in June and December. All submissions are double-blind reviewed by peer reviewers. All papers must be submitted in BAHASA INDONESIA. JUTIF has P-ISSN : 2723-3863 and E-ISSN : 2723-3871. The journal accepts scientific research articles, review articles, and final project reports from the following fields : Computer systems organization : Computer architecture, embedded system, real-time computing 1. Networks : Network architecture, network protocol, network components, network performance evaluation, network service 2. Security : Cryptography, security services, intrusion detection system, hardware security, network security, information security, application security 3. Software organization : Interpreter, Middleware, Virtual machine, Operating system, Software quality 4. Software notations and tools : Programming paradigm, Programming language, Domain-specific language, Modeling language, Software framework, Integrated development environment 5. Software development : Software development process, Requirements analysis, Software design, Software construction, Software deployment, Software maintenance, Programming team, Open-source model 6. Theory of computation : Model of computation, Computational complexity 7. Algorithms : Algorithm design, Analysis of algorithms 8. Mathematics of computing : Discrete mathematics, Mathematical software, Information theory 9. Information systems : Database management system, Information storage systems, Enterprise information system, Social information systems, Geographic information system, Decision support system, Process control system, Multimedia information system, Data mining, Digital library, Computing platform, Digital marketing, World Wide Web, Information retrieval Human-computer interaction, Interaction design, Social computing, Ubiquitous computing, Visualization, Accessibility 10. Concurrency : Concurrent computing, Parallel computing, Distributed computing 11. Artificial intelligence : Natural language processing, Knowledge representation and reasoning, Computer vision, Automated planning and scheduling, Search methodology, Control method, Philosophy of artificial intelligence, Distributed artificial intelligence 12. Machine learning : Supervised learning, Unsupervised learning, Reinforcement learning, Multi-task learning 13. Graphics : Animation, Rendering, Image manipulation, Graphics processing unit, Mixed reality, Virtual reality, Image compression, Solid modeling 14. Applied computing : E-commerce, Enterprise software, Electronic publishing, Cyberwarfare, Electronic voting, Video game, Word processing, Operations research, Educational technology, Document management.
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<![CDATA[IMAGERY IDENTIFICATION OF TOMATOES WHICH CONTAIN PESTICIDES USING LEARNING VECTOR QUANTIZATION ]]>
<![CDATA[Ade Sumarsono]]>;
<![CDATA[Supatman Supatman]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.1.15
<![CDATA[Tomatoes have a risk of carrying pesticides above the maximum residue limit (MRL) because the fruit is directly sprayed with pesticides during its production process. Pesticide residue in farmers’ produce pose indirect effects to the consumers, but in the long run, it may cause health problems such as neural disorders as well as enzyme metabolism. This research identifies the image of tomatoes containing pesticides by using two types of tomatoes were used as samples, namely tomatoes which contain pesticides, and those which do not contain pesticides. This research aims to develop an algorithm to identify tomatoes that contain pesticides and those which do not contain pesticides using Learning Vector Quantization (LVQ). The characteristics used to identify tomato images are average, variant, and standard deviation. This research consisted of two classes and used 40 training image data and 40 test image data for each class. During the training process using LVQ parameters, there were 98.75% best percentage at alpha 0.001 and decalpha 0.9 with the lowest iteration of 3. The final weight obtained from the parameters was then used to perform test data identification. In terms of the best performance on the test data, it was with alpha 0.001 and decalpha 0.9, which reached 97.5%.]]>
<![CDATA[ANALYSIS AND DESIGN OF USER INTERFACE/USER EXPERIENCE WITH THE DESIGN THINKING METHOD IN THE ACADEMIC INFORMATION SYSTEM OF JENDERAL SOEDIRMAN UNIVERSITY ]]>
<![CDATA[Hananda Ilham]]>;
<![CDATA[Bangun Wijayanto]]>;
<![CDATA[Swahesti Puspita Rahayu]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.1.30
<![CDATA[User Interface/User Experience (UI/UX) design is very important because with a good design that meets user needs, it can make users feel comfortable when using a product. One example is the Academic Information System (SIA), if the design of the SIA is not user friendly, it will have an impact on both the user and the system. Such as input errors, missing information, difficulties in using it. The purpose of conducting UI / UX analysis and design at SIA Universitas Jenderal Soedirman is to solve the problems experienced by users today. Users involved in this research are students. Design is made using the Design Thinking method and for the testing using Usability Testing.]]>
<![CDATA[CLASSIFICATION OF MEAT IMAGERY USING ARTIFICIAL NEURAL NETWORK METHOD AND TEXTURE FEATURE EXTRACTION BY GRAY LEVEL CO-OCCURRENCE MATRIX METHOD ]]>
<![CDATA[Chairul Imam]]>;
<![CDATA[Eka Wahyu Hidayat]]>;
<![CDATA[Neng Ika Kurniati]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.1.37
<![CDATA[Lately, there is often a mixture of beef and pork done by traders to the general public as buyers. This is due to the unconsciousness of the buyer on how to recognize the type of meat purchased. The effect of this meat mix can certainly be detrimental to buyers, especially Muslims. Image processing is a general term for various methods in which it is used to manipulate and modify images in various ways. Classification is a method of grouping some information and ensuring it is listed in a class.. Classification of beef and pork differentiator in this application using Artificial Neural Network (ANN) method while for texture extraction using Gray Level Co-occurrence Matrix (GLCM) method. The information used in the examination was 30 images of fresh meat divided into 15 images of fresh beef and 15 images of fresh pork. The data used is data Classification of Beef and Pork Image based on Color and Texture Characteristics. The result of classification accuracy obtained in this application is 80%.]]>
<![CDATA[THE DECISION SUPPORT SYSTEM OF PUBLIC SERVICE SATISFACTION USING TOPSIS METHOD AT REGIONAL I BKN YOGYAKARTA ]]>
<![CDATA[Benedictus Fredika Apriawan Santoso]]>;
<![CDATA[Indah Susilawati]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.1.42
<![CDATA[Public service satisfaction is the result of public opinion and assessment for the service performance provided by the public service organizer apparatus. In real action, this public satisfaction survey is conducted periodically to discover the real value owned and anything that the public wants to get for its services. This then becomes one of the commitments of the Regional I BKN Yogyakarta in implementing the predetermined quality policies and service standards which are useful for improving the service quality for the public. Hence, additional efforts are needed in processing the data obtained from the public satisfaction survey report results to follow up according to the real requirements expected by the public in making decisions, so that they can be right on target. Researchers aim to make a decision support system prototype that gives an overview about the public service satisfaction rate, using the TOPSIS Method with the parameter data of satisfaction criteria and the survey data as well as the value range of the public service satisfaction survey in January to March 2019. Based on the data of the public service satisfaction test for that 3 months, either the results of the system prototype calculation or the manual calculation, 3-period compatibility with 100% was obtained.]]>
<![CDATA[WEB-BASED LIBRARY INFORMATION SYSTEM IN MADRASAH IBTIDAIYAH NEGERI SURAKARTA ]]>
<![CDATA[Dedi Gunawan]]>;
<![CDATA[Ivanovick Abdurrakhman Ar Raniri]]>;
<![CDATA[Robby Nugroho Setyawan]]>;
<![CDATA[Yogatama Dwi Prasetya]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.1.44
<![CDATA[Library is a primary supporting facility in any level of education spanning from elementary school, middle school and higher education i.e., university. The main aim of library is providing facility in which it can improve educational quality and allow the member to advance their knowledge from various reference sources. Managing book circulation is a crucial aspect for library in which it further increases effectivity for its business process such as returning and borrowing books. However, Madrasah Ibtidaiyah (MI) Negeri Surakarta does not have any such application system which can help its library management, as a result the library member cannot obtain have updated information related to the library collection. Currently, the school relies on manual procedure where the library staff records borrowing and returning books activities in a certain book log. Unfortunately, the manual procedure causes missing data and data consistency in the recording book. Therefore, research aim to design and build e-library. The e-library is a web-based information system that has specific features that can address the school problems. To realize objective, we adopt waterfall software development method to build the information system. We also evaluate our design by using black box testing to ensure its functionality. Results show that our developed system works as it is designed and can handle any request from user without causing any errors.]]>
<![CDATA[GPS-BASED TRACKING IN ARMAPS: THE EFFECT OF DEGREE SLANT SMARTPHONE TO DISPLAY AUGMENTED REALITY OBJECTS ]]>
<![CDATA[Anna Syahrani]]>;
<![CDATA[Dede Wira Trise Putra]]>;
<![CDATA[Aulia Rahma]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.1.45
<![CDATA[This paper discusses the functionality testing of the augmented reality (AR) application, namely ARmaps. ARmaps is an AR application for directions that uses GPS-based tracking technology (GPS-based tracking). GPS-based tracking is one of the basic techniques in AR, which does not require special media to scan visual objects (marker-less) GPS-based tracking is used to display data digitally. Digital data displayed in the form of user location and directions. Based on the test results, it was found that there was an effect of the degree slant smartphone on the delay time in displaying 3D AR graphic objects. The test is done statically by adjusting the degree slant, namely acute, right-angle, and obtuse. Each test was carried out 30 times. Smartphones that support ARmaps performance should have an accelerometer, proximity, gyroscope, compass, A-GPS with Glonass and BDS sensors, as well as a camera. Smartphones that are placed with a large degree slant of 90o (obtuse angle) have a faster delay time in displaying 3D AR graphic objects, which is 12.7 seconds. This research becomes the basis for developing ARmaps as a guiding application (visualization guiding).]]>
<![CDATA[COMPARISON OF MACHINE LEARNING METHODS IN CLASSIFYING POVERTY IN INDONESIA IN 2018 ]]>
<![CDATA[Pardomuan Robinson Sihombing]]>;
<![CDATA[Ade Marsinta Arsani]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.1.52
<![CDATA[Poverty is still one of the main problems in economic development besides inequality, unemployment, and economic growth. This study aims to model poverty directly using a discrete choice model, namely the machine learning classification method. The data used are imbalanced data where one of the categories is small enough so that the resample of both sampling method is used. In this study, several machine learning methods were applied, including the Decision Tree, Naïve Bayes, K-Nearest Neighbor (KNN), and Rotation Forest. The results show that the technique of using resample both samplings provides optimal results for the four machine learning methods. If viewed from the indicators of accuracy, specificity, sensitivity, AUC, and the highest Kappa coefficient produced, the best method is the KNN method. The KNN model has an accuracy value of 0.73 percent, sensitivity of 0.68 percent, specificity of 78 percent, and AUC of 0.73.]]>
<![CDATA[PEOPLE COUNTING FOR PUBLIC TRANSPORTATIONS USING YOU ONLY LOOK ONCE METHOD ]]>
<![CDATA[Tsabita Al Asshifa Hadi Kusuma]]>;
<![CDATA[Koredianto Usman]]>;
<![CDATA[Sofia Saidah]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 2 No. 1 (2021): JUTIF Volume 2, Number 1, June 2021 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2021.2.2.77
<![CDATA[People counting have been widely used in life, including public transportations such as train, airplane, and others. Service operators usually count the amount of passengers manually using a hand counter. Nowadays, in an era that most of human-things are digital, this method is certainly consuming enough time and energy. Therefore, this research is proposed so the service operator doesn't have to count manually with a hand counter, but using an image processing with You Only Look Once (YOLO) method. This project is expected that people counting is no longer done manually, but already based on computer vision. This Final Project uses YOLOv4 that is the latest method in detecting untill 80 classes of object. Then it will use transfer learning as well to change the number of classes to 1 class. This research was done by using Python programming language with various platforms. This research also used three training data scenarios and two testing data scenarios. Parameters measured are accuration, precision, recall, F1 score, Intersection of Union (IoU), and mean Average Precision (mAP). The best configurations used are learning rate 0.001, random value 0, and sub divisions 32. And the best accuration for this system is 69% with the datasets that has been trained before. The pre-trained weights have 72.68% of accuracy, 77% precision, and 62.88% average IoU. This research has resulted a proper performance for detecting and counting people on public transportations.]]>
