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[DEVELOPMENT OF MOBILE-BASED FREELANCE SERVICES MARKETPLACE WITH FEATURE-DRIVEN DEVELOPMENT METHODOLOGY ]]>
<![CDATA[Nurdiansyah, Mochamad Ikhsan]]>;
<![CDATA[Kusumo, Dana Sulistyo]]>;
<![CDATA[Ramadhan, Arief]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.5.2569
<![CDATA[The rapid advancement of technology demands that humans adapt to the evolving workplace. One of the impacts of technological development is the emergence of freelancers who use online platforms. Online platforms make it easier for freelancers and clients to collaborate. Currently, there are various Freelance Services Marketplace platforms available. However, it is important to note that the developers of these platforms are from outside Indonesia, which poses a risk to the security of people's data and the ease of payment applicable in Indonesia. With the high number of mobile device users in Indonesia,, the development of a mobile-based Freelance Services Marketplace application system that is tailored to local needs and takes into account the data security of Indonesian people, as well as involving local developers, is needed. This research aims to overcome these problems by designing a mobile-based freelance services marketplace application system using the Feature-Driven Development (FDD) method. The selection of FDD as an application development methodology is based on complex feature requirements, good planning management, emphasis on feature quality, and structured. The development process follows the FDD approach starting from feature planning and design, scheduling, implementation, and testing. The application design in this research is based on user needs with a focus on the features needed. This solution is important because it can be used by clients to find freelancers who match their needs and provide opportunities for freelancers to offer their services properly with guaranteed data security and transactions. The main result of this research is that the FDD method can help in the development of a freelance service marketplace application by paying attention to the systematic or structured level, quality, and security of the application.]]>
<![CDATA[WEB-BASED IMAGE CAPTIONING FOR IMAGES OF TOURIST ATTRACTIONS IN PURBALINGGA USING TRANSFORMER ARCHITECTURE AND TEXT-TO-SPEECH ]]>
<![CDATA[Muazam, Safa]]>;
<![CDATA[Kurniawan, Yogiek Indra]]>;
<![CDATA[Iskandar, Dadang]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.5.2585
<![CDATA[Purbalingga is a region located in Central Java Province, offering interesting natural beauty and tourist destinations. Many tourists capture their moments in photos, which are then uploaded to social media. However, a picture can contain a lot of information, and each individual may interpret it differently. Without captions, people may struggle to extract this information. Image captioning addresses this challenge by automatically generating text descriptions for images. Additionally, text-to-speech is used to enhance accessibility for the visually impaired in understanding image descriptions. This research aims to develop an image captioning model for images of tourist attractions in Purbalingga using transformer architecture and ResNet50. The transformer architecture employs an attention mechanism to learn the context and relationships between inputs and outputs, while ResNet50 is a robust convolutional network for image feature extraction. Model evaluation using BLEU metrics, which compare generated sentences to reference sentences, shows the best results as BLEU-{1, 2, 3, 4} = {0.672, 0.559, 0.489, 0.437}. Experiments indicate that increasing embeddings and layers extends training time and lowers BLEU scores, while changing the number of heads has minimal impact on results. The best model is implemented in a web-based application using the SDLC waterfall method, Flask framework, and MySQL database. This application allows users to upload tourist attraction images, receive automatic descriptions in Indonesian, and listen to the captions read aloud using the Web Speech API-based text-to-speech feature. Blackbox testing results show valid outcomes for all tests, indicating that the application operates as required and is suitable for use.]]>
<![CDATA[Information Retrieval Related to Information Regarding Covid-19 Using Transformers Architecture ]]>
<![CDATA[Wiktasari, Wiktasari]]>;
<![CDATA[Prayitno, Prayitno]]>;
<![CDATA[Kartika, Vinda Setya]]>;
<![CDATA[Lavindi, Eri Eli]]>;
<![CDATA[Ardhana, Naufal Reky]]>;
<![CDATA[Nariswana, Rucirasatti]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2025.6.2.2606
<![CDATA[The spread of the COVID-19 virus has occurred exponentially, necessitating advanced search technologies that provide accurate information. The primary challenge in searching for COVID-19 related information involves the diversity and rapid changes in data, as well as the need to understand specific medical contexts. Unstructured information sources, such as research articles, news reports, and social media discussions, add complexity to retrieving relevant and up-to-date information. As the volume of data and information related to the COVID-19 pandemic increases, there is a pressing need for effective and accurate information retrieval systems. Transformer architecture, known for its capabilities in natural language processing and managing complex contexts, offers great potential to enhance search quality in the healthcare domain. BERT is a deep learning model that performs searches based on specific queries, with search results sorted accordingly. The ranking process uses BERT architecture to compare the performance of transformer encoders, specifically between bi-encoders and cross-encoders. A bi- encoder is an architecture where two separate encoders process two different inputs, such as queries and documents. In contrast, a cross-encoder processes two texts simultaneously using a single encoder, allowing the model to capture contextual interactions between them. Research indicates that cross-encoder performance is significantly better than bi-encoder for cases with relatively small data sets. Evaluation results show that the NDCG score for bi-encoder is 0.89, while for cross-encoder it is 0.9. The mAP score for bi-encoder is 0.7, and for cross-encoder, it is 0.89. Both bi-encoder and cross-encoder achieved an MRR score of 1.0.]]>
<![CDATA[Sentiment Analysis of Cyber Attacks in Bank Syariah Indonesia Using SVM and Indobert Method ]]>
<![CDATA[Apriyadi, Chandra]]>;
<![CDATA[Styawati, Styawati]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2025.6.2.2636
<![CDATA[Bank Syariah Indonesia (BSI) is one of the Islamic banking institutions that operates based on Islamic principles in accordance with Islamic law and has obtained an operational license from the Dewan Syariah Nasional (DSN). The advancement of information technology brings unique risks to the banking industry, including BSI. One example is the ransomware attack experienced by BSI from May 8 to 11, 2023, where 15 million customer data and 1.5 terabytes of internal data were stolen, leading to significant public concern and response across various media platforms. This has the potential to affect public trust in the Islamic banking industry, particularly BSI. This research aims to analyze public sentiment on Twitter regarding the attack to identify the majority sentiment formed, as well as to compare the performance of the SVM and IndoBERT models in classifying sentiments. Additionally, this study reveals the topics present in the negative sentiments based on the classifications of both models through topic modeling using Latent Dirichlet Allocation (LDA). The results indicate that the majority of sentiments are negative, while IndoBERT shows better performance compared to SVM, with an accuracy of 85% and an F1-Score of 82%. The topics present in the negative sentiments classified by SVM include issues related to fund security as well as transfers and withdrawals, whereas the topics present in the negative sentiments classified by IndoBERT are more related to problems with mobile banking and fund withdrawals.]]>
<![CDATA[IMPLEMENTATION OF A COMBINATION OF ADVANCED ENCRYPTION STANDARD CRYPTOGRAPHY WITH SUBBYTES MODIFICATION AND STEGANOGRAPHY BASED ON A WEBSITE ]]>
<![CDATA[Kurniawan, Muhammad Ilham]]>;
<![CDATA[Maryanto, Eddy]]>;
<![CDATA[Rahayu, Swahesti Puspita]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.5.2665
<![CDATA[The Advanced Encryption Standard (AES) is a symmetric encryption algorithm commonly used to protect digital data. However, concerns about potential attacks on cryptographic keys and the development of cryptanalysis methods further reinforce the need for security enhancement. This study aims to combine two technologies: the Advanced Encryption Standard (AES) cryptography with modifications to the SubBytes, and steganography using the Least Significant Bit (LSB) method in images, to enhance the security level of encrypted messages in the context of transmission through websites. In this study, modifications were made to the AES algorithm by replacing the S-box in the SubBytes process with a perfect SAC S-box with an average SAC value of 0.5. This testing is divided into two types: algorithm testing and system testing. Algorithm testing involves performance testing methods that show longer decryption times with an average difference of 80.27 milliseconds, cryptanalysis testing showing increased ciphertext security based on cryptanalysis time estimates using brute force, and randomness testing to demonstrate improvements in Frequency and Poker tests. System testing using the Black Box method shows results that are valid as expected.]]>
<![CDATA[SENTIMENT ANALYSIS FOR E-COMMERCE PRODUCT REVIEWS BASED ON FEATURE FUSION AND BIDIRECTIONAL LONG SHORT-TERM MEMORY ]]>
<![CDATA[Akbar, Habibullah]]>;
<![CDATA[Aryani, Diah]]>;
<![CDATA[Mohammed Al-shammari, Marwan Kadhim]]>;
<![CDATA[Ulum, M. Bahrul]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.5.2675
<![CDATA[E-commerce platforms would benefit from performing sentiment analysis of their customer's feedback. However, the vast amount of transaction data makes manual sentiment analysis of product reviews impractical. This research proposes an approach to automatically classify the sentiment of a given product review based on three major steps: data preprocessing, text representation, and classification model development. First, review data is cleaned to remove ambiguity and non-meaningful elements. Second, Word2Vec and GloVe features are combined to represent the words in a more unified vector space. Lastly, these combined features are classified to determine sentiment polarity using the Bidirectional Long Short-Term Memory Network (BiLSTM) model. The test results demonstrate that the proposed BiLSTM model achieves 91% uniform performance for all four metrics (accuracy, precision, recall, and F1-score), which is 3% higher than the results achieved by the standard LSTM model. Moreover, the BiLSTM model requires 9.91 seconds less training computation time than the LSTM.]]>
<![CDATA[CHATBOT FEATURES ON WEBSITES USING DIALOGFLOW FRAMEWORK WITH RULE-BASED METHOD ]]>
<![CDATA[Nabiha Riandika, Muhammad Afiq]]>;
<![CDATA[Susanto, Ajib]]>;
<![CDATA[Respatria, Nabila Maharani]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.5.2688
<![CDATA[A chatbot is an artificial intelligence (AI) technology that can mimic human conversation in the form of text or voice messages through a website, or mobile application. Chatbots are widely used to facilitate communication, such as finding information, or services. In this research, the difficulty of accessing information in obtaining answers to questions asked by the public, as well as taking too long for the admin to reply when providing information to people who ask questions related to information about the topic raised, is an initial problem that will be solved in this research. Chatbot is a solution that can overcome the above problems, chatbot itself is designed to help food license applicant services on the website of the Semarang City Health Office in the field of Pharmacy and Perbekes. By utilizing the Dialogflow framework, this chatbot will use the Rule-Based method because in this development, the Rule-Based method can adjust common questions and answers that are often asked by the public, and can also be changed and even expanded to manage conversations without experiencing much difficulty in changing them that follow questions that are often asked over time. The system consists of agents, intentions, and training phrases that will be trained to understand various questions and provide relevant responses. This chatbot development aims to improve the efficiency of food licensing services, reduce applicant waiting time, and provide accurate and easily accessible information. The test results in this development are on a chatbot system that can run well, and is able to understand various kinds of questions related to food licensing, and provide appropriate responses in accordance with the predetermined intent. In addition, an evaluation of the level of user satisfaction will be carried out to measure the success of this system. This chatbot can improve the quality of public services in the field of food licensing and provide convenience for the public in processing licenses.]]>
<![CDATA[Identification of Dominant Frequencies in Javanese Vocal Phonemes Using Fast Fourier Transform and Random Forest Classification ]]>
<![CDATA[Muhadi, Muhadi]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2025.6.2.2708
<![CDATA[The majority of speech recognition research currently uses English as the research base, but the results can also be used for another language, including Javanese speech recognition. Previous research stated that there were differences in frequency between English and Dutch. This shows that the frequency of Javanese can also be different. The difference in frequency allows for a new way of recognizing Javanese Speech. By using a dataset of Javanese vowel phonemes, this research aims to identify the dominant frequencies in Javanese speech using the Fast Fourier Transform data extraction an2d the Random Forest Classifier. The feature importance level data will be tested with a deep neural network to determine the accuracy and speed of the process. Choosing a dominant frequency is expected to make the process more effective and efficient in using computing resources.]]>
<![CDATA[HORTICULTURE SMART FARMING FOR ENHANCED EFFICIENCY IN INDUSTRY 4.0 PERFORMANCE ]]>
<![CDATA[Arifin, Nurhikma]]>;
<![CDATA[Insani, Chairi Nur]]>;
<![CDATA[Milasari, Milasari]]>;
<![CDATA[Rasyid, Muhammad Furqan]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.5.2728
<![CDATA[Chili peppers and papayas are important horticultural commodities in Indonesia with high economic value. To enhance productivity and efficiency in cultivating these crops, the application of Smart Farming technology is crucial. This study evaluates the use of image processing and artificial intelligence in the pre-harvest and post-harvest processes for chili peppers and papayas. For the pre-harvest process, data from 50 images of ripe chili peppers on the plant were used. The counting of ripe chilies was performed using HSV color segmentation with two masking processes, resulting in an average accuracy of 82.58%. In the post-harvest phase, 30 images of papayas, consisting of 10 images for each ripeness category—unripe, half-ripe, and ripe—were used. Papaya ripeness classification was carried out using the Support Vector Machine (SVM) algorithm with a Radial Basis Function (RBF) kernel and parameters C = 10 and γ = 10-3, achieving perfect classification accuracy of 100% for all categories. This study underscores the significant potential of Industry 4.0 technologies in enhancing agricultural practices and efficiency in the horticultural sector, providing important contributions to optimizing chili pepper and papaya production.]]>
<![CDATA[SPEARMAN CORRELATION ANALYSIS OF AIR AND BILLET TEMPERATURE IN ALUMINUM HOMOGENIZATION USING IoT-BASED REAL-TIME DATA COLLECTION ]]>
<![CDATA[Afiqah, Filzah Amanina]]>;
<![CDATA[Prasetyo, Murman Dwi]]>;
<![CDATA[Sjafrizal, Teddy]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.5.3503
<![CDATA[Understanding the correlation between the parameters involved in the homogenization process of aluminum billets contributes to better process control. As a critical step in the production of aluminum billets, failure to control the homogenization temperature can lead to variations in product quality and a negative effect on mechanical strength. To address this issue, this study aims to understand the correlation between air and billet temperature of homogenization using temperature data obtained from thermocouple sensors placed at different points in the oven and billet. The temperature data was collected in real time through an Internet of Things (IoT) network. Spearman correlation analysis was performed on the collected data to determine the relationship between temperatures at different measurement points. The analysis results show that the air temperature at the Z2 right point had a strong correlation with the billet temperature, with a correlation value of 0.90. In contrast, the correlation between air temperature and billet temperature at Z1 Left was lower, indicating a weaker correlation and resulting in uneven heat distribution. These results highlight the importance of controlling the air temperature at Z2 Right to improve the temperature distribution during heat treatment. In addition, this study provides a real case in the implementation of real-time monitoring technology for better understanding on industrial process, especially heat treatment process.]]>
