Article Per Year (5 Year)
p-Index From 2021 - 2026
1.827
P-Index
This Author published in this journals
All Journal JSAI (Journal Scientific and Applied Informatics) Idealis : Indonesia Journal Information System Jurnal Teknik Informatika (JUTIF) Jurnal Algoritma Journal of Elektronik Sistem InformasI
Budy Santoso, Cahyono
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 5 Documents
Search
Journal : JSAI (Journal Scientific and Applied Informatics)

 1 
Implementasi Data Warehouse dan Bussiness Intelligence Kasus AIDS di Jawa Barat Budy Santoso, Cahyono; Muhammad Mujiburochman; Reyner Shaquille Rachim; Raihan Cikal Herlambang
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7567

Abstract

This study discusses the design of a data warehouse for analyzing AIDS cases in West Java using the Nine Step Methodology. The background of this research is the high prevalence of AIDS cases in West Java during 2018–2019 and the need for an integrated data management system to support data-driven health policies. The objective of this study is to design and implement a data warehouse capable of integrating data from various dimensions, such as region, age group, gender, and year, to support epidemiological analysis of AIDS. The methodology employed includes stages such as data extraction from various sources, data transformation to enhance quality, and data loading into a PostgreSQL-based data warehouse system. The study also utilizes the ETL (Extract, Transform, Load) process to ensure the integrity of the processed data. The results indicate that the designed data warehouse successfully maps the distribution of AIDS cases based on relevant dimensions. Key findings reveal that the productive age group (25–49 years) and males have the highest number of cases, with Bandung City being the region with the most cases. The contribution of this study is the provision of a data platform that supports evidence-based decision-making while identifying high-risk regions and groups for more effective health interventions. Limitations include the scope of data limited to two years and the absence of predictive analytics features. Future research is recommended to expand the time coverage and integrate predictive analysis to enhance the effectiveness of health policy
Implementasi NLP Klasifikasi Berita Pemilu Menggunakan Algoritma LSTM Harry Vadilan Sianturi; Budy Santoso, Cahyono
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8212

Abstract

This study examined the application of a Long Short-Term Memory (LSTM)-based text classification method to categorize election news according to presidential and vice-presidential candidate entities. The core problem addressed was the lack of an automated classification system capable of identifying political affiliations directly within the vast volume of digital news content. In this research, news data were collected from open-access sources and automatically labeled based on the occurrence of candidate-related keywords. A supervised learning approach was implemented using the LSTM architecture to capture sequential patterns within the news text. The evaluation results demonstrated that the model achieved a validation accuracy of 95.44% and a macro-averaged F1-score of 0.95, indicating strong classification performance across all candidate categories. Furthermore, predictions on test data revealed the model’s consistency and stability in recognizing political entities. This study confirmed the effectiveness of the LSTM-based approach for entity-based election news classification and highlighted its potential for integration into automated media analytics and political discourse monitoring systems.
Perancangan Aplikasi Sistem Presensi Guru Berbasis Web Menggunakan Geo Fencing Pada Sekolah SDN XYZPerancangan Aplikasi Sistem Presensi Guru Berbasis Web Menggunakan Geo Fencing Pada Sekolah SDN XYZ Faizul Anwar Ramdhani; Budy Santoso, Cahyono
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8231

Abstract

The web-based teacher attendance system application with Geo-Fencing technology integration is designed to improve the accuracy and efficiency of the teacher attendance recording process in the school environment. The use of Geo-Fencing allows attendance to only be done when the user is in a predetermined area, thus minimizing the potential for fraud and data manipulation. This research aims to develop a web-based attendance application and evaluate its usability level using the System Usability Scale (SUS) method. The evaluation was conducted on 20 respondents consisting of teachers and school administrators. Based on the test results, an average SUS score of 75 was obtained, which is included in the Good usability category. Thus, this application is considered quite easy to use, effective, and acceptable to users. The results of this study indicate that the web-based teacher attendance system application with Geo-Fencing has the potential to be widely implemented in the school environment, with some further development recommendations to improve user experience.
Perancangan Web E-Commerce Pada Toko XYZ Dengan Fitur Sistem Rekomendasi Hafid Roihan; Budy Santoso, Cahyono
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8268

Abstract

This research aims to design and implement a web-based e-commerce system for XYZ Store by providing a fresh vegetable product recommendation feature, using the Apriori algorithm and the Rapid Application Development (RAD) approach. The design process begins with collecting data through interviews to find out the needs of the system. Transaction data for one month was analyzed using the Apriori algorithm to identify patterns of association between products that are often purchased together. The results of this analysis were used as the basis for creating recommendation features. The RAD approach was used because it allows the system to be developed quickly and gradually by involving users in each phase of development. This research analyzes the usability level of the platform using the System Usability Scale (SUS) method. Testing was conducted on 15 participants who had tried the platform prototype in the designed usage scenario. The measurement results indicate that the average SUS score is 78.2, placing it in the “Good” category. The recommendation system feature received a positive response, with the majority of users finding it helpful in finding relevant products. These findings suggest that integrating the recommendation system not only enriches the platform's features but also contributes to improving the overall user experience.
Evaluasi Metode Retrieval pada Chatbot Domain Khusus Berbasis Retrieval-Augmented Generation Asmaidin, Asmaidin; Budy Santoso, Cahyono
JSAI (Journal Scientific and Applied Informatics) Vol 9 No 1 (2026): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v9i1.9897

Abstract

This study evaluated retrieval methods in the implementation of a domain-specific chatbot based on Retrieval-Augmented Generation to improve information accuracy and relevance while reducing hallucination risks. The primary problem addressed was the incorrect selection and prioritization of contextual documents in chatbot systems built on large language models, particularly in technical domains. An experimental approach was applied by comparing three retrieval strategies: lexical retrieval based on term frequency–inverse document frequency, semantic retrieval using vector representations, and a hybrid retrieval method combining lexical and semantic signals. System performance was measured using Recall at different ranking thresholds and Mean Reciprocal Rank to assess both document discovery and ranking quality. The results demonstrated that lexical retrieval achieved the highest precision at the top-ranked position, while semantic retrieval showed reduced effectiveness due to semantic drift in technical documents. The hybrid approach improved mid-range recall performance but still exhibited ranking ambiguity for top-ranked results. These findings indicated that retrieval quality in Retrieval-Augmented Generation systems depended more on effective ranking and context prioritization than on document availability alone. The study concluded that systematic evaluation of retrieval methods was essential for developing reliable domain-specific chatbots.
Co-Authors Ahmad, Alifio Fikra Ahmad Asmaidin, Asmaidin Bhagawanta, Bajra Effendi, Rufman Iman Akbar Faizul Anwar Ramdhani Ghaniy, Rajib Hafid Roihan Harry Vadilan Sianturi Johannes Hamonangan Siregar Muhammad Mujiburochman Rachma, Mutia Raihan Cikal Herlambang Reyner Shaquille Rachim Vistiyawati, Vanessa