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[OPTIMIZATION OF MACHINE LEARNING MODEL ACCURACY FOR BRAIN TUMOR CLASSIFICATION WITH PRINCIPAL COMPONENT ANALYSIS ]]>
<![CDATA[Maulana, Indra]]>;
<![CDATA[Siregar, Amril Mutoi]]>;
<![CDATA[Rahmat, Rahmat]]>;
<![CDATA[Fauzi, 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.2024.5.3.2058
<![CDATA[The main issue in brain tumor classification is the accuracy and speed of diagnosis through medical imaging. This study aims to improve the accuracy of machine learning models for brain tumor classification by using Principal Component Analysis (PCA) for dimensionality reduction. The research methods include image preprocessing, feature scaling, PCA application, and the implementation of machine learning algorithms such as Logistic Regression, Random Forest, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes. The dataset consists of 3,264 images divided into training and testing sets. The results show that the use of PCA has varying impacts on different algorithms. PCA increases the accuracy of the SVM algorithm from 81% to 83% and KNN from 68% to 71%, but decreases the accuracy of Logistic Regression from 77% to 69% and Naive Bayes from 49% to 42%. Evaluation is performed using the Confusion Matrix and AUC-ROC to measure model performance. In conclusion, selecting the appropriate algorithm and preprocessing method is crucial in medical image classification, and the use of PCA should be considered based on the characteristics of the data and the algorithms used. This study also encourages the exploration of alternative dimensionality reduction methods for medical image analysis.]]>
<![CDATA[PERFORMANCE COMPARISON OF SVM, NAIVE BAYES, AND LOGISTIC REGRESSION CLASSIFICATION ALGORITHMS IN ANALYZING NOICE APP USER REVIEWS ]]>
<![CDATA[Ahmad Bahar]]>;
<![CDATA[Tri Astuti]]>;
<![CDATA[Primandani Arsi]]>
<![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.2024.5.4.2061
<![CDATA[In the rapidly growing digital era, user reviews on distribution platforms such as the Google Play Store are a key indicator in assessing the popularity, quality, and user satisfaction of applications. This study aims to compare the performance of SVM, Naive Bayes, and Logistic Regression classification algorithms in analyzing user reviews of the Noice app, an audio content platform. The research involves steps such as data collection, data pre-processing, word embedding, modeling, model evaluation, and sentiment analysis. Testing was conducted using 1877 data. The data from the reviews were divided into scenarios, with training and testing data divided in ratios of 90:10, 80:20, and 70:30. The results showed that the SVM algorithm achieved the highest accuracy rate (80%) in the 90:10 data split scenario. However, Naive Bayes also showed competitive results with 78% accuracy in the same scenario. Meanwhile, Logistic Regression achieved 78% accuracy when the data was split in an 80:20 ratio. Evaluation was done using metrics such as accuracy, precision, recall, and F1-score. Sentiment analysis showed a positive trend with 1194 positive data compared to 683 negative data. From the comparison of data sharing scenarios and algorithms, SVM at 90:10 data sharing gave the best results.]]>
<![CDATA[TRAFFIC FLOW AND CONGESTION DETECTION WITH YOLOV8 AND BYTETRACK-BASED MULTI OBJECT TRACKING ]]>
<![CDATA[Fahrezi, Marchel Maulana]]>;
<![CDATA[Laksana, Eka Angga]]>
<![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.2024.5.4.2063
<![CDATA[The rapid urbanization witnessed in cities like Bandung, Indonesia, has emerged as a pressing issue, precipitating severe traffic congestion that poses challenges to economic growth and diminishes overall quality of life. This study endeavors to confront these multifaceted challenges through the development of a sophisticated real-time traffic surveillance and control system. The proposed system utilizes the current CCTV infrastructure in the city and incorporates advanced technologies like YOLOv8 for accurate vehicle detection and ByteTrack for dynamic real-time vehicle tracking. This system utilizes a comprehensive strategy, including multi-object tracking techniques to improve the precision of congestion detection. The system was thoroughly assessed in several places in Bandung, and it showed remarkable performance metrics. Specifically, YOLOv8 achieved an impressive 80% accuracy rate in vehicle detection, showcasing its efficacy in discerning vehicles within complex urban environments. Simultaneously, ByteTrack exhibited an average error rate of 17% in vehicle counting, further Strengthening the system's capabilities in accurately quantifying vehicular traffic. Furthermore, the combination of YOLOv8 and ByteTrack in a multi-object tracking paradigm yielded an 80% accuracy rate in congestion detection, emphasizing the system's robustness in real-time traffic management scenarios. These findings underscore the immense potential of the integrated YOLOv8 and ByteTrack system in traffic management strategies and alleviating congestion in smart cities like Bandung. This research has produced precise outcomes in identifying and quantifying the traffic congestion in various scenarios.]]>
<![CDATA[THE INFLUENCE OF FEATURE EXTRACTION ON AUTOMATIC TEXT SUMMARIZATION USING GENETIC ALGORITHM ]]>
<![CDATA[Rahmadianti, Fitrah Amalia]]>;
<![CDATA[Hendrastuty, Nirwana]]>
<![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.2024.5.4.2064
<![CDATA[Text summarization using extraction methods is a technique that summarizes by retaining a subset of sentences to create a summary. There are two types of documents commonly used for summarization: single document and multi-document. Multi-document refers to documents originating from one or more sources that contain several main ideas. The data used in this research is obtained from the E-lapor DIY website, consisting of 1000 data entries. E-Lapor DIY is a website provided by the DIY government to accommodate all public aspirations and complaints, such as damaged roads, broken traffic lights, insufficient street lighting, litter in public places, and more. The accumulation of data and the delayed response time has become an issue for the government in addressing these complaints. This research aims to consider the impact of using feature extraction for text summarization using genetic algorithms. The feature extraction compared in this research is the influence of sentence position in feature extraction. The results obtained show that Precision testing using F1 is 0.64, and without using F1, it is 0.66. Recall testing using F1 is 0.65, and without using F1, it is 0.68. F-Measure testing using F1 is 0.65, and without using F1, it is 0.68. This testing using the algorithm can be an interesting alternative for more time-efficient text summarization.]]>
<![CDATA[DESIGN OF A WORDPRESS BASED E-COMMERCE WEBSITE AND INTEGRATION OF CRYPTOCURRENCY PAYMENT GATEWAY ]]>
<![CDATA[Anggoro, Restu]]>;
<![CDATA[Susanto, Erliyan Redy]]>
<![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.2024.5.4.2067
<![CDATA[The Internet has become one of the main media, especially e-commerce transactions, which are increasingly popular and play an important role in the growth of online businesses. The RestLyfe store uses the Itemku platform, which uses a Business to Customer (B2C) and Customer to Customer (C2C) model, to sell digital products such as digital vouchers and game keys. However, some of the issues faced when using the platform include high costs, limited market reach, and payment methods that can only be used by certain customers. Building an e-commerce website and adding a cryptocurrency payment gateway will hopefully solve these problems. To achieve this goal, an e-commerce website based on the WordPress content management system (CMS) with the WooCommerce plugin will be built. This plugin will incorporate a cryptocurrency payment gateway and facilitate transaction design. To collect related data, observation and literature review were conducted. The waterfall model System Life Cycle Development (SDLC) method will be used to build the e-commerce website. The results and conclusions of this study show that the website built can solve the problem with implementation results that meet the needs of the initial analysis, and the results of black box testing conducted on the website show good results. In addition, this study demonstrates the use of modern sales strategies for cryptocurrencies and the optimization of the latest technologies. Thus, the e-commerce site offers more opportunities to reach the target market and meet the needs of an increasingly digitized market.]]>
<![CDATA[HYBRID MODEL OF PARTICIPATORY AND DELIBERATIVE E-DEMOCRACY IN INDONESIA’S ELECTIONS ]]>
<![CDATA[Widhiarso, Dytha Ananda]]>;
<![CDATA[Ibrahim, Ali]]>
<![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.2024.5.4.2072
<![CDATA[E-democracy is a branch e-government that uses information technology to support the process of implementing democracy. E-Democracy itself has several models that can be applied. The election process in Indonesia itself has 2 methods, namely Noken and individual, therefore, in this research the model focused on is the hybrid of participatory and deliberative model. This research aims to see the level of public readiness in using the e-democracy model for the implementation of General Elections. The research was carried out using the literature study method with a qualitative approach and accompanied by quantitative data collection using a questionnaire. The questionnaire was used to see the level of readiness to use the e-democracy model for elections. The questionnaire uses a mixture of TAM (Technology Acceptance Model) and DOI (Divergent of Innovation) methods. The results of this research show that the range of dimension index values is above 72%, with the highest value being 82% in the Calculation Results Dimension and 80% in the Perceived Usefulness Dimension. This shows that the public is ready to use e-democracy in the election process, and increases the possibility of using e-democracy in elections.]]>
<![CDATA[SYSTEMATIC LITERATURE REVIEW ON THE APPLICATION OF UI/UX DESIGN METHODS IN SYSTEM DEVELOPMENT ]]>
<![CDATA[Ramadani, Romi]]>;
<![CDATA[Mahdiana, Deni]]>
<![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.2024.5.4.2073
<![CDATA[In the current modern digital era, system development is undoubtedly rapid and massive, especially across various sectors such as healthcare, business, and public services. In system development, many aspects are considered, one of which is the appearance of the user interface. Interface design becomes an intriguing aspect and has an influence on system or application development. System development surely involves user interface and user experience aspects as part of the human-computer interaction (HCI) discipline. This research aims to identify research opportunities in UI/UX aspects in system development, with data obtained from relevant journals spanning from 2019 to 2024 as a representation of the latest study on UI/UX design research. This study utilizes the Systematic Literature Review (SLR) method. The results of this research provide a systematic literature review of existing studies on UI/UX design. This research can benefit the HCI community by applying methods in UI/UX design in system development to shape the direction of future research.]]>
<![CDATA[THE EVALUATIONS FOR THE BACKEND OF ONTI MEASURES WITH BLACK BOX METHOD ]]>
<![CDATA[Ekowati, Nur Alfi]]>;
<![CDATA[Sulistiyasni, Sulistiyasni]]>;
<![CDATA[Lestari, Ika Indah]]>
<![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.2024.5.4.2089
<![CDATA[Inconsistency in an ontology can be a serious problem since it can mess up the information in the ontology. Ontology-based inconsistency measure gives inconsistency value of the whole base of the OWL ontology. It means the produced inconsistency value is used to evaluate its whole base. Based on this characteristic, there were 10 inconsistency measures created in the previous research and collected into one package of measures in an application program, namely Onti Measures. The application will not be useful if the measures do not work well. This problem leads to conduct evaluations. In this research, evaluations for the backend part of Onti Measures with the use of three kinds of OWL reasoners are done to know the performance of the application system with the comparison of each reasoner usage. The evaluations for the whole part of the application are not the scope of this research since they are only done for the backend part. Particularly, they are done with the black box method since the structure of the codes are not necessary to be known. They are evaluated with several OWL files as test cases and as the inputs of the backend program. The evaluation shows that the same inconsistent OWL file that is computed with a different type of inconsistency measure with any chosen reasoner may result in different inconsistency value. Other evaluations are provided. Overall, they show that Pellet is better than the two other reasoners and I_(D_f ) is more efficient than the other measures.]]>
<![CDATA[DEVELOPMENT OF HERBIFY APPLICATION WITH AI INTEGRATED UTILIZING YOLO V8 FOR OPTIMIZING HERBAL POTENTIAL IN INDONESIA ]]>
<![CDATA[Ahmad Fajruddin Syauqi]]>;
<![CDATA[Prasetya, Didik Dwi]]>
<![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.2024.5.4.2094
<![CDATA[Indonesia is known as the home to 80% of the world's medicinal plant species, with an estimated 25,000-30,000 potential plants. However, this is in stark contrast to the current situation of limited access to herbal information, leading to restricted consumption and distribution of herbal products. The numerous digital platforms providing herbal data still fail to address this issue, as the information provided does not cater to the users' needs. Therefore, to address the current challenges in the Indonesian herbal industry, researchers developed an AI-integrated application called Herbify. The application was developed using the Agile Software Development Life Cycle method, chosen to meet user needs with a user-centered design approach. From this research, a mobile application with two main features, namely 'Herbalpedia' and 'Scanherbal,' was developed. Measurements through three methods: mAP matrix, usability tests, and user experience questionnaires (UEQ), yielded positive results. The measurement results show that the trained model achieved a 94.6% mAP with an inference time of 0.07965 seconds. Furthermore, the usability test results of the application show a 0% mission unfinished rate, with an average completion time of 10 seconds. The UEQ results indicate that the application has high usability, trustworthiness, and information quality. Based on these results, it can be concluded that Herbify has great potential to effectively optimize herbal potentials in Indonesia.]]>
<![CDATA[ANALYSIS OF CHATGPT ACCEPTANCE FOR EDUCATION USING MODIFIED TECHNOLOGY ACCEPTANCE MODEL ]]>
<![CDATA[Mahmud Rizal Mustofa]]>;
<![CDATA[Siregar, Maria Ulfah]]>
<![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.2024.5.4.2095
<![CDATA[The presence of ChatGPT provides various benefits from all sectors including education. However, despite the various benefits obtained, many researchers argue that ChatGPT also has many significant drawbacks. This research aims to analize the effect of perceived threat, perceived ease of use, perceived usefulness, attitude toward using dan behavioral intention to use the system of ChatGPT in education. The TAM modification in this research is the addition of a perceived threat variable which refers to the problem of the research object.The population in this research is active students of Universitas Islam Negeri Sunan Kalijaga Yogyakarta. The sampling technique is carried out using probability sampling or simple random sampling. While the determination the number of samples in this study used a sample table so that 377 respondents were students from various faculties. The data used in this study were obtained by distributing questionnaires and analyzed using SEM-PLS with the help of SmartPLS 3 software. The result of this research show that perceived threat and perceived ease of use affect perceived usefulness, perceived ease of use and perceived usefulness affect attitude toward using and attitude toward using affects behavioral intention to use of ChatGPT in education.]]>
