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[IMPLEMENTATION OF PATHFINDING ALGORITHM IN SCOUT EXPLORING GAME WITH DIGITAL GAME-BASED LEARNING-INSTRUCTIONAL DESIGN METHOD ]]>
<![CDATA[Kurniadi, Dede]]>;
<![CDATA[Tresnawati, Dewi]]>;
<![CDATA[Sopiah, Dede]]>
<![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.2024.5.4.1931
<![CDATA[Scouting, or Praja Muda Karana, which means young people who like to work, has become an extracurricular activity that must be held in schools and is regulated by the Law of the Republic of Indonesia. Tri Satya and Dasa Dharma are scouting principles applied through scouting teaching methods, including interactive learning in the open air. One form of implementation is through exploration activities. Along with the rapid development of science and technology, scouting material is now easier to convey through educational games. Educational games are specifically designed to teach specific concepts and understanding, as well as to guide, train skills, and motivate players. Therefore, the aim of making this game is to describe and simulate exploration activities, which is one of the essential aspects of scouting activities. Applying the A* pathfinding algorithm in a 3D game with a scout exploration theme is critical in helping players determine the fastest path to the destination post. This game is expected to improve the player's learning experience with realistic challenges and interactive learning. This game was developed using the Digital Game-Based Learning-Instructional Design (DGBL-ID) method and tested using black box testing. The implementation results show that the scout exploration game application provides positive benefits, as proven by the results of a questionnaire using the Guttman scale with the title "Very Good," indicating that this game is a learning medium that is easy to understand and fun.]]>
<![CDATA[DESIGNING UI/UX FOR A MEDITERRANEAN DIET APP TO MINIMIZE TYPE 2 DIABETES RISK ]]>
<![CDATA[Salam, Farah Danisha]]>;
<![CDATA[Pamungkas, Endang Wahyu]]>
<![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.2024.5.4.1932
<![CDATA[The industrial revolution has had a significant impact in health field, where the crucial disease in Indonesia is Type 2 Diabetes Mellitus (T2DM). One of the effective ways to minimize the increase in T2DM is by developing a diet application using Mediterranean diet Method. The Mediterranean diet involves controlling certain types of foods and beverages, characterized by high intake of fruits, vegetables, whole grains, nuts, legumes, moderate consumption of fish, low intake of red/processed meat, and low intake of high-fat dairy products. In this research and design, the Author applied User Centered Design (UCD) method, which encompasses User Interface (UI) and User Experience (UX). The author also applied the UX law (Hick’s Law, Law of Proximity, dan Aesthetic-usability Effect) on designing the user interface. This article included a A/B Testing and System Usability Scale (SUS) result that showed an interesting findings, where the design that achieved a higher success rate had a lower user satisfaction score and vice versa. However, both designs have an acceptable score and C grade.]]>
<![CDATA[SENTIMENT ANALYSIS OF INDONESIAN ELECTION 2024 USING THE K-NEAREST NEIGHBOR METHOD ]]>
<![CDATA[Kurniawan, Rido Dwi]]>;
<![CDATA[Muliawan, Joshua]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.2.1934
<![CDATA[The abstract of this research discusses the analysis of Indonesian public sentiment regarding the 2024 election as observed via Twitter. Sentiment graph Research uses the Natural Language Processing method and the K-Nearest Neighbor algorithm to classify sentiment as positive, neutral, or negative. The current era of globalization influences the rapid progress of information technology circulating in society, one of the intermediaries is through the social media Twitter. Twitter can be used as a means of conveying opinions regarding suggestions, criticism and public opinion. Currently social media has a big impact on building public political sentiment and preferences. The social media I took is Twitter so that people's Tweets related to elections can be used to see a picture of public opinion. There are various opinions of Twitter users with positive, neutral and negative sentiments. However, classifying sentiment from Twitter users requires quite a lot of time and effort due to the large number of tweets found. The aim of this research is to conduct a public sentiment analysis of public opinion regarding the 2024 election. Data was collected in October and December 2023. The results show that positive sentiment dominates with 76%, followed by neutral sentiment at 16%, and negative 6%. This analysis helps understand public opinion regarding the 2024 election on social media, especially Twitter.]]>
<![CDATA[INTEGRATING GHRM AND INFORMATION SYSTEMS FOR SUSTAINABILITY IN OIL & GAS: 2019-2023 BIBLIOMETRIC STUDY ]]>
<![CDATA[Rachman, Adryan]]>;
<![CDATA[Diandra, Nadia]]>;
<![CDATA[Anthony, Gerald Ethan]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.2.1935
<![CDATA[In an era where ecological sustainability intersects with corporate accountability, this study pioneers the integration of Green Human Resource Management (GHRM) practices within the oil and gas sector, heralding a paradigm shift towards environmental stewardship and sustainable business operations. Through an incisive bibliometric analysis of data sourced from Scopus, ScienceDirect, and ResearchGate databases covering the years 2019-2023, this research meticulously examines a corpus of 52 journals, selectively narrowing down to 10 seminal works that underscore the critical nexus between organizational strategies and sustainable investment practices. Leveraging the analytical prowess of VosViewer for a nuanced exploration of the thematic landscape, this study illuminates the transformative role of GHRM in driving the oil and gas industry towards a future where environmental considerations are not merely an adjunct to business strategy but are embedded within the core operational ethos. The investigation transcends conventional academic discourse, positioning itself as a clarion call for the industry to reevaluate and realign its project management and investment frameworks in favor of sustainable development principles. The findings of this research are both a testament to and a roadmap for the integration of sustainability into the fabric of corporate strategy, highlighting innovation, strategic adaptability, and a steadfast commitment to green practices as indispensable to securing the sector’s long-term viability. This study not only contributes to the burgeoning field of GHRM but also sets a benchmark for future research, advocating for a symbiotic relationship between economic growth and environmental preservation. This groundbreaking work challenges the oil and gas sector to lead by example, embodying the principles of sustainability in every facet of its operations, thereby setting a new standard for corporate responsibility in the face of global ecological challenges.]]>
<![CDATA[COMBINATION OF AHP AND MAUT METHOD TO DETERMINE SCHOLARSHIP RECIPIENTS IN HIGHER EDUCATION (CASE STUDY: UNIVERSITAS TEKNOKRAT INDONESIA) ]]>
<![CDATA[Romdoni, Muhammad]]>;
<![CDATA[Parjito, Parjito]]>
<![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.2024.5.4.1940
<![CDATA[Universitas Teknokrat Indonesia is an educational institution located in the city of Bandar Lampung. Every new academic year a new student admission selection is carried out. Selection is carried out with two channels, namely regular and scholarship. One of the scholarship pathways is the Indonesia Smart Lecture Card (KIP-K). The acceptance of the scholarship pathway is done conventionally. This method certainly has obstacles, namely less effective time efficiency. The solution offered is through research by applying a combination of Analytical Hierarchy Process (AHP) and Multi Attribute Utility Theory (MAUT) methods to the Decision Support System. To assist in making decisions to determine prospective students who are eligible for KIP-K Scholarships, the right criteria are needed. The criteria used include economic status, achievement, parents' income, number of dependents, housing conditions, previous scholarships, parental assistance, organizational experience, test scores, and parents' status. The purpose of this research is to apply the AHP and MAUT methods in a decision support system that can assist the campus in determining scholarship recipients quickly, precisely and efficiently. The stages of this research are data collection, application of AHP and MAUT methods, and system implementation. Based on calculations carried out using a combination of AHP and MAUT methods, the highest preference value is Destia Putri with a value of 0.7791 and the lowest preference value is Pramutya Galuh 0.0444. Judging from the ranking results, it can be concluded that the combination of AHP and MAUT methods can be used to assist in decision making to determine prospective student recipients of KIP-K scholarships at Universitas Teknokrat Indonesia.]]>
<![CDATA[BLACK BOX TESTING WITH THE EQUIVALENCE PARTITIONING AND CAUSE EFFECT GRAPH METHOD IN ARCHIVE INFORMATION SYSTEM ]]>
<![CDATA[Ismiati, Suci]]>;
<![CDATA[Aditiawan, Firza Prima]]>;
<![CDATA[Nurlaili, Afina Lina]]>
<![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.2024.5.4.1944
<![CDATA[The Wijaya Putra University Archives Information System is a website-based information system used by Wijaya Putra University teaching staff as a digital archive storage medium. Several users mentioned that there were errors in the system, such as login problems, data access problems, and no file delivery notifications, so testing was needed to find functional errors in the system so that repairs could be made. Testing was carried out using the Black Box method with Equivalence Partitioning and Cause Effect Graph techniques. The use of Equivalence Partitioning is used to divide data input into each form, and each form input will be tested and grouped based on its function, whether it is appropriate or not appropriate. Meanwhile, the Cause Effect Graph is used to find out whether the test results obtained from the Equivalence Partitioning process are in accordance with the relationship between cause (input) and effect (output) expected in the system. Based on the research conducted, the final results show that out of a total of 58 test cases, there were 50 appropriate test cases and 8 inappropriate test cases, resulting in an effectiveness value of 87.67%. With this value, the Wijaya Putra University Archives Information System is running according to its function, but still needs to be repaired and further developed for functions that still have errors.]]>
<![CDATA[CLASSIFICATION OF RICE PLANTS AFFECTED BY RATS USING THE SUPPORT VECTOR MACHINE (SVM) ALGORITHM ]]>
<![CDATA[Nofie Prasetiyo]]>;
<![CDATA[Baihaqi, Kiki Ahmad]]>;
<![CDATA[Lestari, Santi Arum Puspita]]>;
<![CDATA[Cahyana, Yana]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.2.1949
<![CDATA[In the era of Indonesia's agrarian economy which is supported by the agricultural sector, rice plants play an important role in meeting food needs. However, pest attacks, especially field mice, can cause significant losses in rice production. To overcome this, this research proposes the use of the Support Vector Machine (SVM) algorithm with the Particle Swarm Optimization method in predicting rat pest attacks on rice plants. This research involves the process of collecting data from drone photos to identify affected agricultural land. The preprocessing stage involves changing colors from RGB to GRAY and zoom augmentation. Feature extraction is carried out using Histogram of Oriented Gradients (HOG) and Local Binary Pattern (LBP). Testing was carried out involving the SVM/SVC model and performance evaluation was carried out using accuracy, precision and recall metrics. The preprocessing test results showed an increase in performance with training accuracy of 68.33%. However, the actual prediction on the original image results in a low accuracy of around 25%. However, image testing after involving the entire process, including preprocessing and model prediction, shows a higher level of accuracy, reaching around 90%.]]>
<![CDATA[COMPARISON OF K-NEAREST NEIGHBOR AND SUPPORT VECTOR MACHINE ALGORITHM OPTIMIZATION WITH GRID SEARCH CV ON STROKE PREDICTION ]]>
<![CDATA[Aprilliandhika, Wahyu]]>;
<![CDATA[Abdulloh, Ferian Fauzi]]>
<![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.2024.5.4.1951
<![CDATA[Stroke ranks second as the leading cause of death globally, with disability being the primary accompanying factor. The cause of death in stroke patients is due to the lack of an optimal stroke prediction system; therefore, identifying whether a patient is experiencing a stroke or not becomes the focus of this research. Thus, the objective of this study is to compare the performance of stroke prediction using two classification models, namely K-Nearest Neighbors (KNN) and Support Vector Machine (SVM), with and without using the GridSearchCV optimization technique. In this experiment, the dataset is processed and divided into training and testing data using the SMOTE oversampling technique. Initial testing is conducted without GridSearchCV. The results of the initial testing show that the KNN model performs better than SVM, with accuracies of 91% and 83%, respectively. After optimizing parameters using GridSearchCV, both models experience a significant performance improvement. The KNN model increases accuracy to 95% with precision of 91% and recall of 98%, while the SVM model increases accuracy to 94% with precision of 90% and recall of 99%. These results indicate that using GridSearchCV to optimize parameters of KNN and SVM models can significantly enhance stroke prediction performance. There are differences in precision and recall between KNN and SVM. The KNN model tends to have higher recall, while the SVM model has higher precision, and for accuracy, the KNN algorithm outperforms SVM in stroke prediction.]]>
<![CDATA[SYSTEMATIC LITERATURE REVIEW APPLICATION OF METHODS IN INFORMATION SYSTEMS DEVELOPMENT ]]>
<![CDATA[Gita Cahyani, Annisa Putri]]>;
<![CDATA[Mahdiana, Deni]]>
<![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.2024.5.4.1954
<![CDATA[In today's rapidly changing digital age, information system development is critical to the growth and success of organizations and businesses. It is critical to select the appropriate system development method because it can impact many aspects of the system, including efficiency, dependability, and alignment with organizational requirements. Businesses or organizations may struggle to determine the best approach based on their project environment and specific requirements. The goal of this study is to gain a better understanding of the various approaches to systems development and how they work. In information systems, each system development technique's complexity and effectiveness will be investigated using a qualitative approach in conjunction with descriptive analysis. A better understanding of the features and benefits of each method, such as agile, waterfall, Rapid Application Development (RAD) and others, will be enable organizations to make more precise and goal-driven decisions. Furthermore, this study will look at previous research on a variety of topics and discussions, such as information system design and the practical application of cutting-edge software. Determine trends, best practices, and issues that have emerged during the development of current information systems. One of the motivations for this research is the growing complexity of project environments, as well as the need for dependable and efficient systems. Learning more about systems development techniques can assist organizations and businesses in lowering project risks, increasing efficiency, and identifying solutions that better meet their business goals. The waterfall method is most popular because it provides more control over the system development process.]]>
<![CDATA[COMPARISON OF INDEX, PARTITION, AND MATERIALIZED VIEW METHODS ON THE ORACLE DATABASE STUDY ON CENTRAL GOVERNMENT FINANCIAL REPORTS (LKPP) ]]>
<![CDATA[Rachman, M Harviandi]]>;
<![CDATA[Samidi, Samidi]]>;
<![CDATA[Aprianto, Eko]]>
<![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.2024.5.4.1962
<![CDATA[The Indonesian Central Government Financial Report (LKPP) is a financial document prepared to increase transparency and accountability in the implementation of the State Revenue and Expenditure Budget (APBN). It is prepared within a tight schedule, hence changes made by each entity must be updated promptly. Therefore, this research focuses on the optimal table design for presenting financial reports. Query optimization is a major concern in database design, with the use of indexing concepts to increase data search speed. Table partitioning is also a strategy to consider, namely dividing a table into parts that form separate data ranges. The use of a Materialized View (MV) is another alternative, providing increased performance with the space-for-time trade-off principle. Experiments were carried out by comparing the response time of applying index, partition, and materialized views to produce financial report data. Experimental results indicate that materialized views can provide significant advantages when faced with large volumetric data. The decision to choose a materialized view can be considered contextually, depending on the specific needs and characteristics of the data encountered in a database system.]]>
