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[ORNAMENTAL PLANT IDENTIFICATION SYSTEM USING TRANSFER LEARNING ON CONVOLUTIONAL NEURAL NETWORK ]]>
<![CDATA[Prilianti, Kestrilia Rega]]>;
<![CDATA[Oktariyanto, Vidian Vito]]>;
<![CDATA[Setiawan, Hendry]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1964
<![CDATA[There was a spike in the ornamental plants as a hobby while spending time at home during the COVID pandemic when people were restricted to activities outside the house. Unfortunately, along with this trend also came the serious issues associated with fake reports claiming that some ornamental plants were harmful to people's health. The public is more worried and perplexed by this situation, which also erodes their confidence in ornamental plants. This research aims to develop a real-time ornamental plant identification system as an educational medium for the public. To increase the system's accuracy, the transfer learning method is applied to the modified MobileNet CNN model. There are 9 species of popular ornamental plants in this identification system. From the experiments, it is known that the best accuracy has been achieved using the Adagrad optimization method (96% for training and 88% for testing data). The CNN model is then embedded in PLANTIS, an Android-based application prototype for ease of use purpose.]]>
<![CDATA[SENTIMENT ANALYSIS OF PUBLIC OPINION ON THE RIGHT OF INQUIRY IN INDONESIA IN 2024 USING THE SUPPORT VECTOR MACHINE (SVM) METHOD ]]>
<![CDATA[Sebastian, Dicky Fernanda]]>;
<![CDATA[Sulistiani, Heni]]>;
<![CDATA[Isnain, Auliya Rahman]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1968
<![CDATA[Research on the right of inquiry refers to public responses on twitter social media related to the 2024 elections. The right of inquiry is a right used in investigations. There are a lot of public opinions about the right of inquiry that are discussed on twitter social media that convey their various opinions or criticisms of government policies towards the 2024 elections. Based on Law No. 17/2014, the right of inquiry of the House of Representatives is regulated in Article 20A of the 1945 Constitution, which regulates the right of inquiry of the House of Representatives. Sentiment analysis is used in this research to determine the accuracy value of public opinion which is categorized into two, namely positive and negative sentiment. In this study, the SVM method is used to identify and find the results of public opinions or responses regarding the issue of the right of inquiry in Indonesia in 2024 which is being widely under the twitter social media platform, so it is necessary to analyze the sentiment. By using the support vector machine (SVM) algorithm and word weighting using TF-IDF (term frequency-inverse document frequency). Data collection using Google Collaboratory tools with the python programming language. The data used were 2,179 tweets with the keywords "inquiry right", "DPR inquiry right", "election inquiry right". The results obtained from the SVM process with an accuracy value of 77%, negative precision value 77%, positive precision value 77%, negative recall value 57%, positive recall value 89%, positive f1-score value 66%, negative f1-score value 82%. The data that has been tested and processed has an adequate accuracy value for SVM algorithm classification using confusion matrix calculation. The results of the research conducted have been effective with the SVM method.]]>
<![CDATA[PATTERNS RECOGNITION (MAUMERE SARONG) USING EDGE DETECTION WITH PREWITT, SOBEL, LAPLACIAN OF GAUSSIAN (LOG), AND CANNY METHODS ]]>
<![CDATA[Piran, Gerfasius Take]]>;
<![CDATA[Alfan, Hilarius]]>;
<![CDATA[Yunita, Maria]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1972
<![CDATA[Maumere Ikat Weaving is a cloth made from a weaving process that requires a lot of energy and time. Maumere Ikat weaving is not only limited to artistic creations; its production also considers symbols of social, religious, cultural, and economic status. The location of an image is easy if the image is clear and sharp. Still, the exact location of the edges makes it difficult to determine if the image contains interference such as noise. Objective: Recognize a Lipa pattern (Maumere Sarong) using Prewitt, Sobel, Laplacian of Gaussian (LoG), and Canny edge detection. Methods: Prewitt, Sobel, Laplacian of Gaussian (LoG), and Canny edge detection. Results: The Lipa (Maumere Sarong) pattern recognition application using Canny edge detection can increase accuracy in recognizing a Lipa (Maumere Sarong) pattern so that it can provide knowledge for tourists and the wider community to recognize and obtain information on the Lipa (Maumere Sarong) more easily.]]>
<![CDATA[ELECTRONIC MEDICAL RECORD INFORMATION SYSTEM DESIGN TO SUPPORT THE REPORTING OF COMPLETENESS OF BPJS PATIENT MEDICAL RECORDS WITH EXTREME PROGRAMMING METHOD ]]>
<![CDATA[Kustiani, Rini]]>;
<![CDATA[Syahidin, Yuda]]>;
<![CDATA[Yunengsih, Yuyun]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1976
<![CDATA[This research was conducted considering that there are still many problems regarding the completeness of medical records, especially for BPJS patients. The number of incomplete filling of medical records and the inaccuracies in the medical record completeness analysis report. The inaccuracy of the data causes miscommunication between doctors and medical record officers. Also, notes about the incompleteness of medical records that doctors need to complete are still done conventionally so they are prone to being lost and unreadable. This study aims to design an electronic medical record information system design to support the reporting of medical record completeness. The research method used is qualitative and data obtained from observations, interviews, literature studies, and software development with Extreme Programming method. This research produces a system that can help officers and doctors to access data on the results of BPJS patient medical record analysis, including information about incompleteness. This can prevent data inaccuracies and ensure officers and doctors know the latest information about the completeness of medical records as a requirement for BPJS claims. This system can also help improve the performance of officers in processing medical record analysis data and produce reports that are more accurate and efficient than the system used previously.]]>
<![CDATA[DATABASE-BASED GUI SYSTEM TO INCREASE THE EFFECTIVENESS OF STUDENT DATA MANAGEMENT IN THE FKIP UHAMKA DORMITORY ]]>
<![CDATA[AMURU, ISMAT]]>;
<![CDATA[Dzikrillah, Akhmad Rizal]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1981
<![CDATA[Data management in the digital era is crucial in various institutions. One of these institutions is the dormitory or student residence, where it's important to track the progress achieved by the residents. However, data management at the FKIP UHAMKA Dormitory still faces several challenges, particularly regarding the loss of previous evaluation data, which is essential for the management. Data loss is a significant issue in the data management process for the relevant institution. Hence, there is a need for innovation in designing a database system that is user-friendly for data management in the digital era. This research aims to develop a GUI-based database system to efficiently manage student data at the FKIP UHAMKA Dormitory. The research adopts the waterfall development method, which involves stages such as requirements analysis, design, coding, and testing. Data is obtained through observation, interviews, and literature studies. The results of the research indicate that the GUI application based on the Dormitory FKIP UHAMKA Database has a good level of usability, with a System Usability Scale (SUS) score of 73.654. This suggests that users find the application easy to use and efficient in meeting their needs related to dormitory management. In addition to the SUS evaluation, this research stands out for developing a more comprehensive GUI system with significant additional features.]]>
<![CDATA[EXPERIMENTAL COMPARISON OF MACHINE LEARNING ALGORITHM PERFORMANCE FOR OPTIMIZING ELECTIVE SUBJECT SELECTION IN PHASE F OF THE MERDEKA CURRICULUM ]]>
<![CDATA[Mulyadi, Dedy]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1983
<![CDATA[In phase f of the Merdeka Curriculum, electives are an important element at the senior high school level. Students are faced with the challenge of choosing four out of twelve elective subjects that are relevant to their talents, interests, further study plans and career goals over a two-year study period. Applying machine learning with the right algorithm is a solution for the effectiveness and efficiency of elective selection. The dataset used comes from the 10th grade report card data, the results of the interest, aptitude, further study, and career choice tests, and the manual selection of electives chosen by students in the previous year. The use of a small data set requires a cross-validation method to improve the generalizability of the model and to optimize the data set, thereby increasing the validity of the results. The test will be conducted using an application that tests five machine learning algorithm models suitable for small datasets, namely Naive Bayes, Decision Tree, Random Forest, Support Vector Machine, and k-Nearest Neighbors. The test focuses on comparing the performance of the five algorithms based on the best accuracy, recall, and confusion matrix and the results obtained Support Vector Machine (SVM) algorithm has the best performance results by achieving the highest accuracy of 57.3770%, the highest recall of 0.574, and the highest true positive (TP) of 0.574. The Support Vector Machine (SVM) algorithm will be a recommendation for further research, namely the development of machine learning for the selection of f-stage elective subjects at Atisa Dipamkara senior high school, to provide relevant guidance to students in making decisions regarding the selection of elective subjects more accurately and according to their respective characteristics.]]>
<![CDATA[DECISION SUPPORT SYSTEM FOR SELECTING THE BEST MASTER PULSE DEALER TO DETERMINE MONTHLY BONUSES USING THE SIMPLE ADDITIVE WEIGHTING METHOD ]]>
<![CDATA[Yuwono, Bagus Prastowo]]>;
<![CDATA[Fernando, Yusra]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1992
<![CDATA[The pulse industry is one of the most dynamic and competitive business sectors, selecting the right master dealer is critical to ensuring optimal business performance. However, a manual selection process can be cumbersome. In this context, user of a decision support system (SPK) that uses simple additive weighting (SAW) are essential. This research aims to design and implement the SPK o.’[uj This research aims to design and implement a system that allows pulse business owners to select the best master dealer more efficiently and objectively. The SAW method is used to calculate the relative weight of each criterion used in the selection of master dealers, such as total transactions, total deposits, number of agents and product marketing. The use of this method makes it possible to assign a relative value to each criterion, according to the preferences and interests of the business owner. By using this SPK, they can determine the master dealer that best suits their business needs and maximize the monthly bonus earned. In addition, the integration of technology in the selection process can also improve operational efficiency and reduce human errors that may occur in manual processes. And in the ranking stage, the final result of the master dealer has been selected on behalf of Ilmi with the highest score of 1.0 and Gagah with the lowest score of 0.26.]]>
<![CDATA[ROUTING OPTIMIZATION ON SOFTWARE DEFINED NETWORK ARCHITECTURE USING BREADTH FIRST SEARCH ALGORITHM ]]>
<![CDATA[Armanda, David]]>;
<![CDATA[Mukti, Fransiska Sisilia]]>;
<![CDATA[Sulistyo, Danang Arbian]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2000
<![CDATA[Software Defined Network (SDN) is a network modelling that separates the control plane and data plane. SDN is a new form of paradigm used for large-scale networks, one of which is for routing. Most types of routing used today use single-path routing. Single-path only uses one path as data transmission. This will result in reduced performance on the network which is often referred to as network congestion. In this test, the routing algorithm used is Breadth First Search (BFS) by modifying the path so that congestion on the network can be minimised. The BFS algorithm is implemented using Mininet emulator, Ryu Controller, and fat-tree topology. In the test, 20 scenarios were used with a bandwidth of 50 - 1000 Mbps within 15 seconds. Tests were conducted to measure the performance of the BFS algorithm, namely the path and QOS (Quality Of Service) parameters which include testing delay, packet loss, jitter, and throughput. The data obtained in testing using the conventional BFS algorithm is compared with the modified BFS algorithm data in the same test method. In path testing, the modified BFS algorithm is superior and in parameter testing, it is produced with a degraded percentage value in delay (65%), packet loss (99%), jitter (84%), and throughput has increased by (41%). So the modified BFS algorithm is superior due to the utilisation of path modification for routing optimisation which is more effective in handling network congestion.]]>
<![CDATA[PROTOTYPE OF CONTACTLESS PAYMENT SYSTEM WITH RFID AND BLOCKCHAIN TECHNOLOGY INTEGRATED WITH MOBILE APPLICATION ]]>
<![CDATA[Jiustian, Danny]]>;
<![CDATA[Yohannis, Alfa]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.3.2002
<![CDATA[The COVID-19 pandemic has led to a change in payment methods, with a shift towards cashless payments to avoid germs and viruses. Contactless payments, especially those using RFID technology, have become popular due to their convenience and no need to enter security codes. However, there is a risk of data manipulation in transaction records, leading to decreased trust and transparency. To solve this problem, this research develops an RFID contactless payment system connected with blockchain technology as the main goal of the research. Blockchain is known for its security and transparency, making it suitable for minimizing data manipulation that often occurs. This research will use the Sepolia Test Network of the Ethereum base network for development in terms of blockchain to serve as a security layer in this research. The Waterfall method will be used for application development, focusing on structured and linear stages such as requirements analysis, system design, implementation, testing, and maintenance. The application development process has shown positive results, with successful black box testing and the ability to track and validate transactions stored in the database and blockchain. This validation process is critical to ensure the integrity of transactions and detect any data manipulation.]]>
<![CDATA[IMPLEMENTATION OF THE YOLOV8 METHOD TO DETECT WORK SAFETY HELMETS ]]>
<![CDATA[Direja, Azhar Ferbista]]>;
<![CDATA[Cahyana, Yana]]>;
<![CDATA[Rahmat, Rahmat]]>;
<![CDATA[Baihaqi, Kiki Ahmad]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.3.2005
<![CDATA[Work safety helmets are an important tool in OHS (Occupational Health and Safety) that must be used by workers. Workers who work with heavy equipment must wear work safety helmets as an obligation. Unfortunately, there are still many workers who do not comply with this rule. They will only wear helmets if there is supervision from a supervisor. However, if the supervisor is not on site, many workers will remove their helmets. The need for supervision of workers is important in reducing work accidents. From these problems, a work safety helmet detection model was created using the YOLOv8 method. This implementation aims to increase the accuracy values obtained and can reduce workload and increase efficiency in checking violations of the use of work safety helmets among workers. The method used consists of several stages, namely image acquisition of 670 images, image labeling, preprocessing, augmentation in roboflow, YOLOv8x model training with 100 epochs, image testing with a distance of 1, 3, 5 meters between the object and the camera, evaluation of test results. Based on the results of training with 467 images, the mAP50 reached 99.5%. Meanwhile, the test results with 100 images showed an accuracy of 99%.]]>
