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Edi Sutoyo
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Indonesian Scientific Journal (Jurnal Ilmiah Indonesia) Jl. Pasar Atas No 3, Kompleks Setramas Kota Cimahi, Bandung
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International Journal of Advances in Data and Information Systems
Published by Indonesian Scientific Journal
ISSN : -     EISSN : 27213056     DOI : https://doi.org/10.25008/ijadis
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Advances in Data and Information Systems (IJADIS) (e-ISSN: 2721-3056) is a peer-reviewed journal in the field of data science and information system that is published twice a year; scheduled in April and October. The journal is published for those who wish to share information about their research and innovations and for those who want to know the latest results in the field of Data Science and Information System. The Journal is published by the Indonesian Scientific Journal. Accepted paper will be available online (free access), and there will be no publication fee. The author will get their own personal copy of the paperwork. IJADIS welcomes all topics that are relevant to data science, and information system. The listed topics of interest are as follows: Data clustering and classifications Statistical model in data science Artificial intelligence and machine learning in data science Data visualization Data mining Data intelligence Business intelligence and data warehousing Cloud computing for Big Data Data processing and analytics in IoT Tools and applications in data science Vision and future directions of data science Computational Linguistics Text Classification Language resources Information retrieval Information extraction Information security Machine translation Sentiment analysis Semantics Summarization Speech processing Mathematical linguistics NLP applications Information Science Cryptography and steganography Digital Forensic Social media and social network Crowdsourcing Computational intelligence Collective intelligence Graph theory and computation Network science Modeling and simulation Parallel and distributed computing High-performance computing Information architecture
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 14 Documents
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Search results for , issue "Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems" : 14 Documents clear
The Importance of Literacy on Artificial Intelligence for the Higher Education Students: A Systematic Literature Review Mahadewi, Mega Putri; Aysya, Alf Arira Ananta; Sofiyani, Zulfatun; Fahmi, Faisal
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1350

Abstract

The rapid development of AI technology makes AI literacy crucial in providing individuals with an understanding of the essential functions of AI and its ethical application in higher education. This study used a scoping literature review method by searching the Scopus, Web of Science, Science Direct, and Sage Journals databases. Based on the search results, the eligibility criteria data were analyzed. Authors found as many as 153 pieces of literature, and eleven were declared to meet the eligibility criteria for the literature reviewed in this study. This study shows that AI literacy is essential in higher education. Educators and higher education institutions are responsible for providing programs that support the development of AI literacy skills in students. The application of AI literacy for students in higher education is essential in dealing with the development of AI technology. However, the lack of studies that address the evaluation of the importance of AI literacy and its implications limits the in-depth understanding of this topic.
Enterprise Architecture Design Vision Architecture and Business Architecture Stage Using TOGAF ADM at SMA ABC Pamungkas, Ananda Cipta; Samihardjo, Rosalin; Murnawan, Murnawan
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1351

Abstract

Digitalization of Education in realizing the vision of an independent curriculum, encourages the development of educational unit technology. In realizing the development of information technology, enterprise architecture planning (EAP) is used to build a balance between business strategy and information technology in implementing integrated educational unit digitalization. This research was conducted at SMA ABC Bandung. The research method used is The Open Group Framework (TOGAF) Architecture Development Method (ADM) with the aim of explaining and providing a methodology in analyzing EAP and finding the vision architecture and business architecture periodically. The purpose of this study is to design information system management, direct business strategy with planning, information technology governance and educational unit management. Research results In the architectural vision, the research is able to identify the needs of organizational capacity that must be met to support the achievement of the vision and mission of SMA ABC Bandung. While at the Business Architecture stage, it produces a gap analysis (GAP analysis) of existing business processes, produces business process diagrams and functional decomposition diagrams to describe the main and supporting business processes at the school, produces stakeholder identification, organizational scope, and main business processes at SMA ABC, and formulates a catalog of principles that are the basis for the proposed enterprise architecture design.
Analysis of Helpdesk System Development in A Manufacturing Company using Design Thinking Approach Sofi, Khalis; Santoso, Bagus Jati
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1354

Abstract

The IT department is vital in manufacturing companies, including PT XYZ, where operations involve transforming raw materials into finished goods. With the complexity of these activities, IT support is essential for managing software and hardware that aligns with business processes. PT XYZ implemented a helpdesk system to streamline IT services but encountered communication issues in the ticketing feature, affecting system efficiency and effectiveness. This research aimed to improve communication between users and administrators to enhance efficiency in monitoring and maintaining IT infrastructure. The study used a design thinking approach, chosen for its collaborative, flexible, and adaptive nature. The process began with the empathize stage, using usability scales and in-depth interviews with users to identify pain points and gather insights. Define, ideate, and prototype stages involved brainstorming and designing solutions in collaboration with the IT team. Finally, the testing stage evaluated user feedback on the improved system. The redevelopment of the helpdesk system yielded significant results, including a 12.27-point increase in usability scale scores. Enhanced features addressed user needs effectively, and all components of the upgraded system were well-received during testing. The improvements led to more structured and systematic communication, making the helpdesk system at PT XYZ more effective and efficient.
Implementation of Business Intelligence and Data Mining in Money Changer Transaction Analysis (Case Study of PT. Gemilang Artha Valindo) Utama, I Komang Ram Pramartha; Putra, Made Adi Paramartha; Purnama, I Nyoman
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1355

Abstract

This study aimed to implement Business Intelligence (BI) and Data Mining for analyzing currency exchange transactions at PT. Gemilang Artha Valindo to support data-driven decision-making. Transaction data was analyzed using Power BI to generate visualizations, including a pie chart for transaction frequency by currency type, a bar chart for the number of buy and sell transactions per currency, and a line chart for monthly average exchange rate fluctuations. The pie chart indicated that the AUD currency dominated transactions, contributing 51.95% of the total. The bar chart revealed that AUD buy transactions accounted for 63.22% of total AUD transactions, while the line chart showed that GBP and EUR had the highest average exchange rates, reaching Rp20,835 and Rp17,700, respectively. The exchange rate prediction process utilized three algorithms: Linear Regression, K-Nearest Neighbors (KNN), and Random Forest. Their performances were evaluated using Root Mean Squared Error (RMSE). The Random Forest algorithm produced the most accurate predictions with the lowest RMSE value of 134.63, followed by KNN and Linear Regression. These findings highlight the importance of leveraging BI and Data Mining to transform transaction data into valuable insights, enabling more informed business decisions.
Implementation of ARIMA for Prediction of Paddy Rice Production in Cisolok Sub-District, Sukabumi District Mugni, Rafi Abdul; Setiawan, Iwan Rizal; Indrayana, Didik
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1356

Abstract

Indonesia as an agricultural country, agriculture, especially paddy production, plays an important role in food security. However, Cisolok District, Sukabumi Regency faces challenges in terms of effective rice production management. This study aims to improve the accuracy of rice production prediction in Cisolok District by implementing Arima. The methodology used is Knowledge Discovery in Databases (KDD), which includes data selection, data pre-processing, model selection, model training, and model evaluation. The data used include weather attributes and paddy production, which are collected from various related sources. The results of the study indicate that the model built with Arima provides accurate estimates and can help farmers and decision makers in planning and managing paddy production more efficiently. These findings are expected to increase paddy productivity in Cisolok District, Sukabumi Regency.
Sentiment Analysis of Twitter Towards the Free Lunch Program Using the C4.5 Algorithm Hanin, Allamanda Salsabila; Maryam, Maryam
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1357

Abstract

This study analyzes public sentiment towards the Makan Siang Gratis (Free Lunch) Program on social media X using the C4.5 algorithm. This program, which was initiated as a campaign promise in the 2024 Election, aims to provide free nutritious food for school students in Indonesia. Given the high public interaction on social media, this study was conducted to determine the public response to the program, which can be positive, neutral, or negative sentiment. The methods used include data collection from social media X, text pre-processing, sentiment labeling, application of Term Frequency-Inverse Document Frequency (TF-IDF), and model evaluation with accuracy metrics. The dataset consists of 3,344 tweets which are then classified using the C4.5 algorithm. Based on the evaluation results, it produces an average precision value of 79%, recall of 76%, F1-score of 77%, and is able to provide an accuracy of 78%. Thus, this model shows effective performance in classifying public sentiment. This study can contribute to the use of social media sentiment analysis as a tool for public policy evaluation.
Web-Based Village Land Information System Development for Optimizing Regional Land Administration Sidiq, Habibi Hasbi; Junarto, Rohmat; Wahyuni, Wahyuni
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1360

Abstract

Access to land information in Indonesia is restricted, especially at the village and sub-district levels, where detailed data is essential for efficient land administration. This research aims to create a web-based Village Land Information System to improve regional land administration through the provision of organized, accessible, and dependable land data. The study employed a Research and Development (R&D) methodology using a prototyping approach, gathering data through observation, surveys, and literature analysis. Data were examined using both descriptive and quantitative methods, with validation and reliability assessments conducted on questionnaires administered to 100 respondents. The assessment employed the End User Computing Satisfaction (EUCS) and Importance-Performance Analysis (IPA) methodologies. The system development encompassed multiple phases: requirements analysis, prototype design, implementation, functionality testing, and evaluation. The Unified Modeling Language (UML) was utilized for system modeling, and user interfaces were crafted with a focus on usability. Functionality tests verified that all features functioned well, and user assessments revealed significant satisfaction with the system’s content, correctness, format, usability, and promptness. The application markedly enhanced land administration by providing comprehensive land information, facilitating access, elucidating service procedures, and systematizing data storage. The results illustrate the capability of web-based technologies to enhance regional land administration and facilitate village government in improving service delivery and land information management.
Comparison of Text Classification Techniques in Fake News Detection in the Digital Information Age Ilham, Dimas Muhammad; Mujiyono, Sri
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1365

Abstract

A comparison of text classification techniques for detecting fake news in the digital information age has been discussed in this study, with a focus on the application of Deep Learning methods, specifically Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). The increasing spread of fake news through digital platforms emphasizes the importance of developing effective methods for identifying inaccurate information. In this study, a news dataset was collected from various sources, and both models were applied for text classification analysis. The performance of the model was then measured based on accuracy, precision, recall, and F1-score. The results showed that although both have their own advantages, better results in terms of processing speed and classification accuracy were found in CNN compared to RNN. These findings provide important insights for the development of more efficient and effective fake news detection systems in the digital age.
Grid-Based Ship Density Analysis and Anomaly Detection for Ship Movements Monitoring at Tanjung Priok Port Ikhsan, Muhammad Ramadhan; Pamungkasari, Panca Dewi; Purbantoro, Babag; Sholihati, Ira Diana; Farahdinna, Frenda; Sumantyo, Josaphat Tetuko Sri; Heezen, Damy Matheus
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1367

Abstract

Indonesia, as a maritime country, depends on ports to support inter-island transport and a smooth regional economy. So, the awareness of knowing the marine status with various platforms is needed. This research distinguishes itself from several previous studies on ship movement detection by concentrating specifically on anomalies in ship movement within areas of high traffic density. This research proposes to find out the ship density area using the grid technique and identify the anomalies that have occurred, as information on ship movements at Tanjung Priok Port. Anomaly detection is done by looking for it through visualization, where AIS data is converted into a form of visualization using the Python language. The results obtained two pieces of information, namely that the areas with the highest density are around the harbor, docks, and ship lanes. Then, two types of anomalies were detected, namely large ships with dangerous cargo speeding in dense areas and ships that behave differently compared to other ships with the same status.
Predicting Software Defects at Package Level in Java Project Using Stacking of Ensemble Learning Approach Zahra, Nabila Athifah; Arifiyanti, Amalia Anjani; Kartika, Dhian Satria Yudha
International Journal of Advances in Data and Information Systems Vol. 6 No. 1 (2025): April 2025 - International Journal of Advances in Data and Information Systems
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/ijadis.v6i1.1368

Abstract

Compared to manual and automated testing, AI-driven testing provides a more intelligent approach by enabling earlier prediction of software defects and improving testing efficiency. This research focuses on predicting software defects by analyzing CK software metrics using classification algorithms. A total of 8924 data points were collected from five open-source Java projects on GitHub. Due to class imbalance, undersampling was applied during preprocessing along with data cleaning and normalization. The final dataset consists of 1314 instances (746 clean and 568 buggy). The predictive model is developed in two stages: base learner (level-0) using AdaBoost, Random Forest (RF), Extra Trees (ET), Gradient Boosting (GB), Histogram-based Gradient Boosting (HGB), XGBoost (XGB), and CatBoost (CAT) algorithms, and meta-learner (level-1) that optimizes the results using ensemble stacking techniques. The stacking model achieved an ROC-AUC score of 0.8575, outperforming all individual classifiers and effectively distinguishing defective from non-defective software components. The comparison of performance improvements between the base model (tree-based ensemble) and stacking was statistically validated using paired t-tests. All p-values were below 0.05, confirming the significance of Stacking’s superior performance, with the largest gain observed against Gradient Boosting (+0.0411, p = 0.0030). The confusion matrix of stacking model is the most optimal model because it has high of True Positive and True Negative, while  False Positive and False Negative values are relatively low. These findings affirm that ensemble stacking yields a more robust and balanced classification system, enhancing defect prediction accuracy and enabling earlier issue detection in the Software Development Life Cycle (SDLC). 

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