Jurnal Ilmu Siber dan Teknologi Digital

Implementation of Fuzzy Sugeno in Mobile-Based Inventory Management

Muhammad Tajul Fajri — 2026-05-05

Purpose: This study aims to develop a mobile web-based inventory management system for Toko Percetakan Diraza by integrating the Fuzzy Sugeno method to improve stock prediction accuracy and reduce errors caused by manual record-keeping, which previously led to stock shortages, overstock, and inefficient monitoring.

Research Methodology: The research used inventory and sales data from January to June 2025, consisting of 229 product records across six categories. The system applied the first-order Fuzzy Sugeno method with two input variables: inventory level and sales data. Development followed the Waterfall model using PHP, MySQL, and Bootstrap. Validation was conducted through manual calculation comparison and black-box testing.

Results:The system calculation results are consistent with the manual Fuzzy Sugeno computations. For the sample product “Ordinary Map B” (inventory: 36 units; sales: 31 units), the system generated a stock demand prediction of 23 units, which corresponds to the manual calculation results. The implementation of the system enhances stock monitoring efficiency and minimizes the risk of manual recording errors.

Conclusions: The Fuzzy Sugeno method can be effectively implemented in a mobile web-based system to provide accurate and adaptive stock predictions for small businesses.

Limitations: The study only used two main inputs inventory levels and sales data without considering additional factors such as lead time or seasonal demand variations.

Contributions: This study contributes to the field of inventory management and decision-support systems by demonstrating that Fuzzy Sugeno can effectively support small businesses, especially printing stores, in predicting stock needs and improving operational efficiency.

Decision Tree C4.5 Algorithm for Classifying Bullying and Sexual Harassment Types in Senior High Schools

Rafli Pahlevi — 2026-05-03

Purpose: This study aims to implement the Decision Tree C4.5 algorithm to classify bullying and sexual harassment cases in senior high schools and develop a web-based decision support system for consistent, evidence-based identification and intervention.
Methodology: A quantitative experimental approach was applied. Data were collected through anonymous student surveys and interviews with Guidance and Counselling (BK) teachers, resulting in 120 cases (93 bullying and 27 sexual harassment). The C4.5 algorithm was implemented using RapidMiner, while the web system was developed using Waterfall System Development Life Cycle (SDLC) with Personal Home Page (PHP) Laravel, MySQL, HTML/CSS, and tested using black box testing.
Results: The model produced a total entropy of 2.44989, with “Incident Type” as the root node (Information Gain = 1.811). “Incident Frequency” became the second-level node. The system successfully classified cases and provided recommendations with 100% success in all nine black box tests covering authentication, classification, reporting, and data management modules.
Conclusions: The C4.5 algorithm effectively classifies bullying and sexual harassment cases, while the web-based system enhances consistency and reduces subjectivity in school decisionmaking.
Limitations: The dataset is limited to 120 cases at the senior high school level, without precision, recall, or F1-score analysis and no longitudinal data.
Contributions: This study provides an operational decision support system using C4.5 for structured classification of schoolbased bullying and sexual harassment cases.

Star Trek’s Technological Predictions and Their Impact on Modern Innovation

Derah Sudjaniah — 2026-05-02

Purpose: This study examines the relationship between futuristic technologies portrayed in the Star Trek series and the development of modern technological innovation, highlighting how science fiction can influence technological advancement.

Research Methodology: A descriptive qualitative approach with a literature review method was employed. Data were collected from academic journals, books, technology reports, digital documentation, and technological representations presented in Star Trek. The data were analyzed using content, comparative, and interpretative analysis.

Results: The findings reveal significant similarities between Star Trek technologies and contemporary innovations, including smartphones, digital tablets, artificial intelligence, smart assistants, AI-based translation systems, wearable devices, virtual reality, digital healthcare technologies, video communication, and smart automation.

Conclusions: The study demonstrates that Star Trek serves not only as entertainment but also as a form of technological foresight that can inspire scientific research, innovation, and digital transformation.

Limitations: This research is limited to secondary data and literature-based analysis without empirical evidence from technology developers, users, or audiences.

Contributions: This study contributes to the fields of media studies, communication studies, digital transformation, and technology innovation by providing insights into the relationship between science fiction narratives and real technological advancement.

Data Security in Electronic Health Information Systems: A Mixed-Methods Analysis of Indonesian Hospital Practices

Adi Ahmad — 2026-05-03

Purpose: Electronic Health Information Systems (EHIS) are widely adopted in Indonesian hospitals, but this has introduced significant data security challenges. This study assesses EHIS data security implementation, identifies systemic vulnerabilities, and offers evidence-based improvement recommendations.
Research Methodology: A mixed-methods design was employed, combining surveys, interviews, and document analysis. Data were triangulated using the Electronic Health Information Systems (EHIS) security frameworks: the CIA Triad (Confidentiality, Integrity, and Availability), ISO/IEC 27001, and the National Institute of Standards and Technology (NIST) Cybersecurity Framework.
Results: Four key security gaps were identified: awareness training (70% aware, 45% trained), policy compliance (85% have policies, 60% implement encryption), high incident rates (65%, mainly unauthorised access and malware), and low technology adoption (50% encryption use, 35% multi-factor authentication).

Conclusions: Indonesian EHIS security shows policy compliance gaps. Priorities include multi-factor authentication, encryption, staff training, and audits, supported by ISO/IEC 27001 and Minister of Health Regulation (PMK) No. 24/2022.
Limitations: The case study sample may not represent all Indonesian hospitals, access to internal security incident data was limited, and quantitative results are descriptive rather than inferential.
Contributions: This study analyzes EHIS data security in Indonesia using survey data and international frameworks to provide evidence based recommendations.