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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962 Documents
<![CDATA[MOBILE APPLICATION DESIGN FOR PROCUREMENT ON XYZ COMPANY ]]>
<![CDATA[Sugianto, Victoria Angela]]>;
<![CDATA[Suyoto, Suyoto]]>;
<![CDATA[Rahayu, Swahesti Puspita]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.4.974
<![CDATA[Procurement of goods in Indonesia continues to experience rapid growth. In 2022, the Indonesian government has allocated a budget of Rp. 2,714 trillion to fulfill government spending. Procurement of goods is almost carried out every month, to meet office needs and support operational facilities. Document storage is one of the important things in every company, however, until now there is no mobile application that can help archiving documents online. This is a problem where files are created and stored manually, so it is still difficult to find files and in transparating data. From the existing problems, there needs to be an innovation that can facilitate the process of managing and storing matching files. One of the innovations was carried out by designing a mobile application using the Design Thinking method. The Design Thinking method can be used to solve problems by rearranging problems into user perspectives that produce design ideas. The results of this study are in the form of a procurement mobile application design. It is hoped that the design and development of the mobile application will be able to provide convenience for Company XYZ in storing procurement documents. So that procurement can be done appropriately, effectively, efficiently, and the procurement documentation process can be carried out quickly.]]>
<![CDATA[DECISION SUPPORT SYSTEM FOR SELECTION OF PESTICIDES FOR CHILI PLANTS USING THE MABAC METHOD ]]>
<![CDATA[Sukamto, Sukamto]]>;
<![CDATA[Fitriansyah, Aidil]]>;
<![CDATA[Nugrah, Randi Andri]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.5.977
<![CDATA[The use of pesticides in agriculture plays a role in preventing and reducing diseases in chili plants. Pesticides for chili plants are quite widely spread on the market and have the advantages of each product offered to farmers, so farmers must be more careful and understanding in choosing pesticides to be used in preventing chili plant diseases. For that we need a decision support system (SPK). The data used in this research are 10 types of pesticides as an alternative. While the criteria are determined based on the agriculture and food service, namely price, classification, number of diseases eradicated, method of action, shelf life, and formulation concentration. Data analysis uses the MABAC method to support decision making for farmers in providing an assessment of the best pesticides on chili plants by steps to forming decision matrices, normalizing decision matrices, determining weighted matrices, determining border area matrices, determining alternative distance matrices, and ranking. The research results obtained the three best pesticides are Tridex 80 WP, Ziflo 76 WG, and Cabriotop 60 WG.]]>
<![CDATA[HUMAN FACE RECOGNITION ON IMAGE VIDEO CONFERENCE APPLICATION USING SIAMESE NETWORK WITH SKIP CONNECTION SMALLER VGG MODEL ]]>
<![CDATA[Tanuwijaya, Evan]]>;
<![CDATA[Setiawan, Averill Saladin Atma]]>;
<![CDATA[Arianindita, Achmad Rijalu]]>;
<![CDATA[Kristanto, Timothy]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.5.981
<![CDATA[Attendance recording is needed to find out someone's attendance at a meeting or meeting. These meetings are sometimes conducted online through the video conferencing application. Recording attendance at online meetings is using an online form that is distributed via chat. There are several problems such as chats piling up and meeting participants arriving late so they cannot access the form link. Therefore, facial recognition can be used to record attendance using screenshots as an attendance record with the aim of helping to facilitate attendance recording through video conferencing applications using computer vision technology. This study proposes a method of using the Siamese network with the Smaller VGG skip connection model to improve human face recognition in video conferencing application images. Has validation accuracy results in the training phase of 98%, precision of 98%, and recall of 98%. For the similarity phase where the model is applied to the Siamese network, the accuracy is 95%, the precision is 53%, and the recall is 78%. Then the model is applied to the pipeline system with the YOLO-face model to classify the results of face detection from Yolo with the faces in the database so that the model does not need to be retrained if there are new faces, it only needs to add facial images to the database to be compared with the query image..]]>
<![CDATA[COMPARISON OF DATA MINING ALGORITHM FOR CLUSTERING PATIENT DATA HUMAN INFECTIOUS DISEASES ]]>
<![CDATA[Nurfadilla, Nadia]]>;
<![CDATA[Afdal, M.]]>;
<![CDATA[Permana, Inggih]]>;
<![CDATA[Zarnelly, Zarnelly]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.5.983
<![CDATA[Tuberculosis is known as an infectious disease whose transmission through air intermediaries is caused by the germ Mycobacterium Tuberculosis. This disease has become a case that has almost spread throughout the pelalawan Regency with the number continuing to increase every year so that it is possible to be able to group the areas where this disease spreads. Grouping of tuberculosis data distribution areas using data mining methods in the form of clustering with the data used coming from the Pelalawan Regency Health Office from 2020 to 2022. The data obtained earlier will then be processed using k-medoids, k-means, and x-means algorithms. The beginning of this research was by processing data from each year using these three algorithms. Determination of the most optimal algorithm using DBI or known as the Davies Bouldin Index. The results of the processing of existing indicators are grouped into three sections, namely areas with a high, medium, and low number of cases. From the results of the study, the optimal algorithm in 2020 data is the k-medoids algorithms with a DBI value of 0,553 and in 2021 data, the most optimal algorithm is the k-means and x-means algorithm with similar DBI values of 0,582. Furthermore, the data in 2022 the most optimal algorithms are the k-means and x-means algorithms because they have the same DBI value, which is 0,510.]]>
<![CDATA[IDENTIFYING AREA HOTSPOTS AND TAXI PICKUP TIMES USING SPATIAL DENSITY-BASED CLUSTERING ]]>
<![CDATA[Lestari, Mulia Dea]]>;
<![CDATA[Iswari, Lizda]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.5.992
<![CDATA[Taxis are one of the competitive sectors of transportation and are recognized as convenient and easy means of transportation to meet individual needs. However, in the operation of a taxi there are some problems that would make the taxi service less optimal, such as the difficulty with finding a taxi at specific hours, the imbalance between demand and taxi supplies, and the length of passengers waiting for a taxi. Therefore, to optimize taxi service, a knowledge base is needed for strategic management decision making. In the study, data of exploration taxis uses a DBSCAN algorithm aimed at identifying and clustering pickup hotspots based on time during weekday and weekend time from Queens, New York City. As for the features used which are pickup latitude and pickup longitude. Accuracy scores for modeling use coefficients to achieve accuracy scores of 0.80 on weekdays and 0.77 on weekends where the accuracy score falls into the accurate category in modeling. Results show that there are three areas of taxi pickup centers based on high taxi demand in January 2016, where they are at LaGuardia airport, John f. Kennedy international, and the area around Steinway Street.]]>
<![CDATA[RECOGNITION OF REAL-TIME HANDWRITTEN CHARACTERS USING CONVOLUTIONAL NEURAL NETWORK ARCHITECTURE ]]>
<![CDATA[Gumilang, Muhammad Satrio]]>;
<![CDATA[Avianto, Donny]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.5.993
<![CDATA[Pattern recognition, including handwriting recognition, has become increasingly common in everyday life, as is recognizing important files, agreements or contracts that use handwriting. In handwriting recognition, there are two types of methods commonly used, namely online and offline recognition. In online recognition, handwriting patterns are associated with pattern recognition to generate and select distinctive patterns. In handwritten letter patterns, machine learning (deep learning) is used to classify patterns in a data set. One of the popular and accurate deep learning models in image classification is the convolutional neural network (CNN). In this study, CNN will be implemented together with the OpenCV library to detect and recognize handwritten letters in real-time. Data on handwritten alphabet letters were obtained from the handwriting of 20 students with a total of 1,040 images, consisting of 520 uppercase (A-Z) images and 520 lowercase (a-z) images. The data is divided into 90% for training and 10% for testing. Through experimentation, it was found that the best CNN architecture has 5 layers with features (32, 32, 64, 64, 128), uses the Adam optimizer, and conducts training with a batch size of 20 and 100 epochs. The evaluation results show that the training accuracy is between 85, 90% to 89.83% and testing accuracy between 84.00% to 87.00%, with training and testing losses ranging from 0.322 to 0.499. This research produces the best CNN architecture with training and testing accuracy obtained from testing. The developed CNN model can be used as a reference or basis for the development of more complex handwriting pattern recognition models or for pattern recognition in other domains, such as object recognition in computer vision, facial recognition, and other object detection.]]>
<![CDATA[ANALYSIS OF IMPLEMENTATION OF PARTICLE SWARM OPTIMIZATION (PSO) METHOD ON LECTURERS ASSIGNMENTS TO STUDENTS ]]>
<![CDATA[Chaerullah, Dhiesky]]>;
<![CDATA[Chalid, Iqbal]]>;
<![CDATA[Solichin, Achmad]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.5.1002
<![CDATA[When preparing a program for a conference, it is very important to divide teaching and learning tasks according to the areas in which you are involved for teaching and learning to be effective. At the University, the assignment process is still done manually which is very time consuming. Therefore, an appropriate optimization method is needed to handle this. This problem can be solved using a population-based heuristic approach, Particle Swarm Optimization (PSO) has been applied to various fields such as scheduling and assignment. The data used in this research is lecturer assignment data in the form of prioritizing lecturer interest in teaching certain subjects. Based on the calculation results, a test was carried out to determine the effect of the test parameters on the fitness value obtained. From the results of the PSO parameter test, the best number of particles is 100, the best number of repetitions is 100, and the speed combination parameters c1 and c2 are 1.5 and 1.5 with the appropriate value of 94878. The system results, the solution obtained gives good results, i.e. always within tolerance limits, the error scores obtained by placing teachers on subjects that suit their preferences are lower]]>
<![CDATA[IMPLEMENTATION OF TEXT PROCESSING FOR SENTIMENT ANALYSIS OF TAX PAYMENT INTEREST AFTER THE "RUBICON" PHENOMENON ]]>
<![CDATA[Gusdiana, Ridian]]>;
<![CDATA[Alfian, Iqbal]]>;
<![CDATA[Juliane, Christina]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.5.1014
<![CDATA[In February 2023, an incident occurred involving the child of an official from the Indonesian Directorate General of Taxes who committed violence against a member of the GP Ansor organization. The news spread widely and brought a new issue, namely suspicious reporting of the official's wealth with an amount of up to 56 billion Indonesian Rupiahs. In order to determine public sentiment towards the "RUBICON" case, which was receiving attention, sentiment analysis of tax payment interest was conducted using text mining techniques. Data processing was done using the R language and RStudio application, taking a dataset of 23,785 tweets from the public about paying taxes on Twitter. Next, text cleaning was done to remove numbers, symbols, and URLs, as well as text processing using stemming, tokenizing, stopword removal, and TF-IDF methods. The TF-IDF method shows that the words "rafael" and "case" are the top keywords. This study used a supervised model by comparing SVM, KNN, and Naive Bayes algorithms, and evaluation was done using a confusion matrix with accuracy results in descending order of 0.8922, 0.8049, and 0.7369. The conclusion of this study is that the SVM algorithm successfully classified sentiment with the highest level of accuracy and obtained the highest negative sentiment of 5,616 sentences.]]>
<![CDATA[SOFTWARE DEVELOPMENT PROJECT MANAGEMENT BASED ON WORK BREAKDOWN STRUCTURE AND ODOO ERP ]]>
<![CDATA[Supriyono, Supriyono]]>;
<![CDATA[Chasanah, Nur]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.4.1077
<![CDATA[Software Development Project Management is the most important part of the Software Development Life Cycle process. The stages in project development include Initiating, Planning, Executing, Monitoring and Controlling, and Closing. This research uses the Work Breakdown Structure approach, which is a method used in project management to break down complex work into smaller and more manageable parts. Work Breakdown Structure helps in organizing, classifying, and describing the work to be done in a project. Odoo ERP is part of the tools that can be used for project management. Testing the project module using Blackbox Testing. The test scenario includes functional testing of the project management module. Application testing shows good results and is following existing needs. The results show that software project management using the Work Breakdown Structure approach can be implemented properly with Odoo ERP tools.]]>
<![CDATA[SECURE TEXT ENCRYPTION FOR IOT COMMUNICATION USING AFFINE CIPHER AND DIFFIE-HELLMAN KEY DISTRIBUTION ON ARDUINO ATMEGA2560 IOT DEVICES ]]>
<![CDATA[Permana langgeng wicaksono ellwid putra]]>;
<![CDATA[Sari, Christy Atika]]>;
<![CDATA[Isinkaye, Folasade Olubusola]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.4.1129
<![CDATA[In an Internet of Things (IoT) system, devices connected to the system exchange data. The data contains sensitive information about the connected devices in the system so it needs to be protected. Without security, the data in the IoT system can be easily retrieved. One way to prevent this is by implementing cryptography. Cryptography is a technique for protecting information by using encryption so that only the sender and receiver can see the contents of the information contained therein. The implementation of cryptography on IoT devices must consider the capabilities of IoT devices because in general IoT devices have limited processing capabilities compared to computer devices. Therefore, the selection of encryption algorithms needs to be adjusted to the computational capabilities of IoT devices. In this research, the affine cipher cryptography algorithm and Diffie-hellman key distribution algorithm are applied to the arduino atmega2560 IoT device. The purpose of this research is to increase the security of the IoT system by implementing cryptography. The method used in this research involves setting up a sequence of encryption and decryption steps using an affine cipher and diffie-hellman algorithms. Furthermore, these algorithms were implemented on an Arduino IoT device. Finally, the decryption time based on the number of characters and the avalanche test were tested. The results showed that on average, Arduino can perform decryption using affine cipher and diffie-hellman algorithms in 0.07 milliseconds per character. The avalanche test produced an average percentage of 45.51% from five trials.]]>
