IJISTECH
IJISTECH (International Journal of Information System & Technology) has changed the number of publications to six times a year from volume 5, number 1, 2021 (June, August, October, December, February, and April) and has made modifications to administrative data on the URL LIPI Page: http://u.lipi.go.id/1492681220 IJISTECH (International Journal Of Information System & Technology) is a peer-reviewed open-access journal published two times a year in English-language, provides scientists and engineers throughout the world for the exchange and dissemination of theoretical and practice-oriented papers dealing with advances in intelligent informatics. All the papers are refereed by two international reviewers, accepted papers will be available online (free access), and no publication fee for authors. The articles of IJISTECH will be available online in the GOOGLE Scholar. IJISTECH (International Journal Of Information System & Technology) is published with both online and print versions. The journal covers the frontier issues in computer science and their applications in business, industry, and other subjects. Computer science is a branch of engineering science that studies computable processes and structures. It contains theories for understanding computing systems and methods; computational algorithms and tools; methodologies for testing of concepts. The subjects covered by the journal include artificial intelligence, bioinformatics, computational statistics, database, data mining, financial engineering, hardware systems, imaging engineering, internet computing, networking, scientific computing, software engineering, and their applications, etc. • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Autonomous Agents and Multi-Agent Systems • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Cognitive systems • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, fault analysis, and diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High-Performance Computing • Information storage, security, integrity, privacy, and trust • Image and Speech Signal Processing • Knowledge-Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Memetic Computing • Multimedia and Applications • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition, and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Stochastic systems • Support Vector Machines • Ubiquitous, grid and high-performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data
Articles
394 Documents
<![CDATA[Analysis of the Potential and Business Development Opportunities in Catfish Farming Using Artificial Neural Networks ]]>
<![CDATA[Rianda, Kiki Rizki]]>;
<![CDATA[Apdillah, Dicky]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.384
<![CDATA[In recent years, there has been a significant increase in catfish consumption. The average consumer demand reaches 50 to 100 kg with a catfish harvest age of about 2.5 months. Catfish farming has not only increased the income of the community but has also transformed those who previously had no knowledge of how to farm catfish and the potential of utilizing yard land into successful catfish farmers. In connection with this, the author intends to recognize more deeply the potential and opportunities of catfish farming in Air Hitam Village, Kualuh Leidong District. In this research, the author applies the Learning Vector Quantization (LVQ) method, which is one of the approaches in Artificial Neural Networks. Learning Vector Quantization (LVQ) is a competitive layer training technique with a supervised learning approach, which uses a network structure with a single layer. The use of Artificial Neural Network (ANN) is a sophisticated way that can be applied to manage catfish farming business. The results showed that the use of the LVQ method in analyzing catfish farming data can help farmers make more informed decisions, predict business development, and increase yields and profits.]]>
<![CDATA[Application of Large Language Model for New Student Admission Chatbot ]]>
<![CDATA[Anwar, Rafidan]]>;
<![CDATA[Pratiwi, Heny]]>;
<![CDATA[Wahyuni, W]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.379
<![CDATA[This study aims to develop a chatbot system based on a Large Language Model (LLM) that provides information related to new student admission in higher education. The system utilizes the SentenceTransformer model to generate embeddings of question and answer texts, as well as FAISS for vector-based search. Additionally, LLAMA is used to generate context-based answers, allowing the chatbot to provide more dynamic and relevant responses. System evaluation is conducted using ROUGE-1, ROUGE-2, and ROUGE-L metrics. The evaluation results show an average ROUGE-1 Precision of 54.89%, ROUGE-2 Precision of 47.37%, and ROUGE-L Precision of 52.72%. The Recall scores for ROUGE-1, ROUGE-2, and ROUGE-L are 89.43%, 74.08%, and 82.91%, respectively]]>
<![CDATA[Application of The Eoq Model to Web-Based Inventory Control Application In Companies ]]>
<![CDATA[Yurindra, Y]]>;
<![CDATA[Wijaya, Benny]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.397
<![CDATA[Inventory of goods is one of the important components in a company. Problems occur in the management of companies that still use a manual system, so that companies have difficulty determining the stock of updated goods, recaping incoming and outgoing goods, and making routine reports. This will affect the next inventory planning and the company makes inventory with estimated needs or when goods run out without being known. To overcome this problem, an application is needed that can manage the company's inventory of goods. This study uses object-oriented methods and prototyping models. Accompanied by an inventory planning calculation model using the Economic Order Quantity model. In its design, it uses a unified modelling language, encoded with the PHP programming language, and tests are carried out with black-box testing. Inventory control applications built on the web by implementing Economic Order Quantity as inventory planning can run well, so that companies can use them to overcome inventory management and planning problems.]]>
<![CDATA[Customer Loyalty Classification With Random Forest Algorithm ]]>
<![CDATA[Sari, Anggi Puspita]]>;
<![CDATA[Noviriandini, Astrid]]>;
<![CDATA[Fauziah, Sifa]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.393
<![CDATA[Customer loyalty is very important for the survival of the company. Because with customers who have customer loyalty, they will make purchases regularly. Customer loyalty needs to be maintained to increase profits. The method is to classify loyal customers with non-loyal ones, in order to retain loyal customers and set strategies for non-loyal customers. The method used is classification with random forest with cleaning stages that can clean data from noise or empty data or data that does not match, selection that can select some data to be processed for classification, transformation that can change data into two or three formats, classification with random forest with split validation using testing data and training data and with rapidminer software. Evaluation by checking the results of the classification with random forest in the form of accuracy, precision, recall, and AUC. The results of the classification show from the accuracy table that the prediction of loyal and true loyal customers is 129 more than the prediction of not loyal and true not loyal customers which is 32. The accuracy result is 96.41% which shows that the data is really accurate with very high results. The recall result is 98.47%, while the precision result is 96.99%.]]>
<![CDATA[Analysis of Nutritional Needs In Elementary School-Aged Children In Remote, Underdeveloped, and Border Regions Using Android-Based Artificial Neural Network Method ]]>
<![CDATA[Febriani, Arisa]]>;
<![CDATA[Apdillah, Dicky]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.385
<![CDATA[The nutritional needs of elementary school children are very important to support their growth, development, and learning abilities. Good nutrition is essential to support the growth of bones, muscles, and organs. In addition, protein, calcium, and iron intake are very important. Nutrition also affects brain function, including children's concentration and memory. One of the schools where various factors related to children's nutrition can be studied is State Elementary School 134633 Tanjung Balai. It is hoped that the analysis of nutritional needs in school children can provide an overview of food consumption patterns, nutritional status, and the factors that influence them. The system developed using the Artificial Neural Network (ANN) model with the Backpropagation algorithm successfully analyzed the nutritional status of children based on the data provided. By categorizing nutritional status into thin, fat, and normal, the system can provide adequate results for the nutritional analysis needs of Elementary School Children in the 3T Area.]]>
<![CDATA[Optimization of Spareparts Stock Data Management at PT. Astra Motor Kaltim 2 using the Trend Moment Method ]]>
<![CDATA[Adeputra, James]]>;
<![CDATA[Pratiwi, Heny]]>;
<![CDATA[Wahyuni, W]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.380
<![CDATA[Spareparts inventory management is a crucial aspect of operations in automotive companies, including PT. Astra Motor Kaltim 2. An imbalance between demand and spareparts availability can lead to stockpiling or stock shortages, ultimately resulting in operational cost inefficiencies. Therefore, this study aims to analyze and forecast spareparts sales using the Trend Moment method to optimize stock management. The Trend Moment method is used to identify sales trend patterns for sparepart 44711K59A12, based on historical sales data from September 2024 to February 2025. The forecasted results are then adjusted using a seasonal index to improve accuracy. Forecast accuracy is evaluated using the Mean Absolute Percentage Error (MAPE), which provides an overview of how close the forecasted results are to the actual data. The results of the study show that the Trend Moment method can provide fairly accurate predictions in estimating the demand for sparepart 44711K59A12 in the upcoming periods. By implementing this method, the company can develop a more efficient stock procurement strategy, reduce the risk of overstocking or stockouts, and improve customer satisfaction. In conclusion, this forecasting approach can serve as a solution to enhance the effectiveness of spareparts inventory management at PT. Astra Motor Kaltim 2]]>
<![CDATA[Performance Evaluation Of SVM With Parameter Optimization On Credit Card Fraud Data Subset Using SMOTE ]]>
<![CDATA[Mahardika, Ahmad Farrel]]>;
<![CDATA[Fahrezi, Irza Nuzul]]>;
<![CDATA[Alleredha, Muhammad Hadya]]>;
<![CDATA[Amaliah, Khusnatul]]>;
<![CDATA[Rofianto, Dani]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.398
<![CDATA[This study evaluates the performance of the Support Vector Machine (SVM) algorithm in detecting credit card fraud by overcoming the class imbalance problem using the Synthetic Minority Oversampling Technique (SMOTE) technique and parameter optimization through Grid Search. The dataset used is sourced from Kaggle, consists of 10,001 transactions, and has been balanced. SMOTE is applied exclusively to the training data to prevent data leakage. The optimization process produces the best parameters at a value of C = 10 and gamma = 0.1. Model evaluation is carried out using recall, precision, F1-score, and AUC-ROC metrics. The results show a significant increase in performance in recognizing fraudulent transactions. The final model recorded a recall of 0.68, precision 0.90, F1-score 0.77, and AUC-ROC 0.98. These findings prove that the combination of SMOTE techniques and parameter optimization can improve the effectiveness of SVM in classifying minority classes more accurately. This approach is considered to have great potential to be applied in automated fraud detection systems in the financial sector.]]>
<![CDATA[Design And Construction of Simpang Empat Village Public E-Service Using Mobile-Based Extreme Programming Method ]]>
<![CDATA[Zoelkifli, Mayang Zahra]]>;
<![CDATA[Samsudin, S]]>;
<![CDATA[Santoso, Heri]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.394
<![CDATA[The E-Community Services application is a website and Android-based application that can be used to overcome several problems in community affairs in the Simpang Empat Village government. Some of the matters that can be handled using this application are Single NA Management Letters, Divorce/Death NA Management Letters, Business License Letters and various other letters. This E-Community Services application also provides security and infrastructure features for the community. The type of research used by the author in this research is Qualitative Research and the System Development Method used is the Extreme Programing (XP) method. With data collection techniques consisting of Observation, Interviews and Literature Study. The E-Community Services application that was built has succeeded in helping to overcome various problems in the Simpang Empat Village government. The results of system testing also obtained very good results, so it can be concluded that the system is running well according to the results of the testing and validation that has been carried out.]]>
<![CDATA[Analysis of Swiftlet Nest Quality In Relation to Price using the Sugeno Method ]]>
<![CDATA[Lubis, Fitri Handayani]]>;
<![CDATA[Sitorus, Zunaida]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 6 (2025): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i6.386
<![CDATA[Many swiftlet nest entrepreneurs in Pangkalan Lunang Village lack a comprehensive understanding of how to assess the quality of swiftlet nests. In fact, nest quality is influenced by various factors, including cultivation techniques, environmental conditions, and post-harvest handling. This lack of knowledge often leads to challenges in maintaining product quality, ultimately affecting selling prices and market competitiveness. Given this situation, it is essential to conduct an in-depth analysis of how nest quality influences its market value. This study employs the Fuzzy Sugeno method to help swiftlet business owners gain a clearer understanding of the relationship between quality parameters—such as color, humidity, shape, and cleanliness—and the selling price. The findings indicate that these quality attributes significantly impact the selling price; the higher the quality, the greater the market value. This emphasizes the importance of adopting best practices in cultivation and post-harvest management to enhance nest quality, meet consumer expectations, and ultimately increase profitability and competitiveness in the market.]]>
<![CDATA[Web-Based Material Inventory Information System For ALAR Welding Workshop ]]>
<![CDATA[Probonegoro, Wishnu Aribowo]]>;
<![CDATA[Sari, Lili Indah]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 9, No 1 (2025): The June Edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v9i1.399
<![CDATA[The ALAR welding workshop is a welding industry that welds various types of metal using various methods and techniques. Material inventory is crucial in this business. Currently, material inventory recording is still done manually, resulting in frequent data errors, information delays, and difficulties in tracking inventory, as it is still manually calculated. Given these issues, the author designed and built a web-based material inventory information system to help manage material stock effectively and accurately. This system replaces error-prone manual processes and improves operational efficiency at the ALAR welding workshop. The method used in this study is the waterfall method because it has a step-by-step design process, namely needs analysis, system design, implementation, testing, and system maintenance. The research results show that the developed information system can facilitate workshop staff in recording, monitoring, and reporting material inventory in real time. This system also improves data accuracy, time efficiency, and supports owners in making faster decisions in the material procurement process, because it is supported by actual and well-documented data. Therefore, this web-based inventory information system can be an effective solution for material management at the ALAR Welding Workshop.]]>
