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All Journal JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Sistemasi: Jurnal Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) Budimas : Jurnal Pengabdian Masyarakat International Journal of Computer and Information System (IJCIS) Transformasi International Journal Artificial Intelligent and Informatics Jurnal Dinamika Informatika (JDI) Techno Journal of Artificial Intelligence and Digital Business Electronic Journal of Education, Social Economics and Technology Jurnal Pengabdian Masyarakat Bangsa International Journal of Advance Social Sciences and Education (IJASSE) Jurnal Rekayasa Sistem Informasi dan Teknologi Jurnal Pengabdian Masyarakat Nasional Jurnal Pengabdian Masyarakat Ekonomi dan Bisnis Digital Jurnal SINTA: Sistem Informasi dan Teknologi Komputasi
Fatkhurrochman, Fatkhurrochman
STMIK Bina Patria Magelang
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Prediction of Peak Ground Acceleration for The Bengkulu Region Using Artificial Neural Network Febriani, Yeza; Fatkhurrochman, Fatkhurrochman; Yunita, Farida; Farid, Muhammad; Apriniyadi, Mohammad; Saleh, Arif Rahman
Jurnal Ilmiah Pendidikan Fisika Al-Biruni Vol 14 No 1 (2025): Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/jipfalbiruni.v14i1.24586

Abstract

This study aimed to predict Peak Ground Acceleration (PGA) values for the Bengkulu region using an Artificial Neural Network (ANN) model. The ANN model utilized earthquake parameter inputs, including magnitude, depth, and hypocenter distance, with soil PGA data collected from the Bengkulu City area. The PGA values were estimated using a neural network model, with the results optimized, validated, and evaluated for performance. The model accurately predicted PGA for large-magnitude earthquakes (R² = 0.99 for magnitudes 7.9–6.5). However, its performance declined significantly for smaller magnitudes (R² = 0.0141 for magnitude 4), reflecting challenges in accurately capturing input parameters, like focal depth and epicentre distance for low-magnitude events. Across a magnitude range of 4.0 to 7.9, the model achieved an overall R² value of 0.99, indicating high accuracy, particularly for larger magnitudes. However, the model's performance declined for lower magnitudes, with R² values dropping significantly, attributed to inaccuracies in input parameters, such as focal depth, epicentre distance, and period. The study provided logarithmic equations for each magnitude range tailored to the seismic characteristics of Bengkulu City, highlighting the importance of localized PGA prediction models. The findings suggest the potential effectiveness of the ANN model for improving earthquake early warning systems and seismic risk management in Bengkulu City under simulated conditions, particularly for large-magnitude earthquakes (R² = 0.99). However, the model’s limitations in predicting PGA for low-magnitude events (R² = 0.0141) highlight the need for further refinement before real-world implementation. This research contributes to the growing body of knowledge by validating and refining the ANN approach for region-specific seismic conditions, offering a practical tool for local authorities and disaster management agencies. Future research should improve the model's accuracy for low-magnitude earthquakes and explore hybrid machine learning techniques to enhance predictive.
Data Security Analysis on the Use of E-Commerce to Prevent Online Fraud Yusnanto, Tri; Fatkhurrochman, Fatkhurrochman; Muin, Muhammad Abdul; Mustofa, Khaoirul
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 1 (2025): Februari - April
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i1.371

Abstract

As the purchasing and selling process has changed, so too has electronic fraud, which has led to several individuals losing money to online frauds. The goal of this study is to ascertain how trust affects the high rate of e-commerce fraud when executing transactions. Qualitative interpretative methodologies are used in this investigation. Research that looks at phenomena having meaningful patterns and relationships is known as phenomenological research. Field research indicates that a lack of understanding, ignorance, the temptation of phony gifts, high unemployment and poverty rates, and weak government security measures are the main causes of fraud in e-commerce transactions. about the various forms of fraud that occur in online transactions.
Optimization of Clustering Model for Mapping Tourism Potential in Magelang Regency Using K-Means Clustering Algorithm Kanafi, Kanafi; Fatkhurrochman, Fatkhurrochman
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.1011

Abstract

Magelang Regency has various tourist destinations with highly diverse potentials, including nature, history, culture, and religious tourism. However, the management of these tourism potentials still faces serious challenges, particularly in terms of mapping, which has not been well-structured. The numerous different tourist spots with various regional potentials have led to local and international tourists experiencing difficulties in selecting promising destinations. The role of mapping for clustering tourism potentials has become a primary need to accelerate economic growth in Indonesia. If clustering is conducted conventionally, without being based on in-depth data analysis, it can risk producing policies that are not well-targeted. The objective of this study is to map the tourism potentials in Magelang Regency using the optimization of the K-Means Clustering method. This clustering is based on variables: attractiveness, accessibility, facilities, number of visitors, ticket prices, security, and rating values. The research methods include literature review, data collection, data pre-processing, K-Means algorithm implementation and optimization, model evaluation and validation, system visualization development, testing, reporting, and publication. The final result of this study is the clustering of tourism potentials into three 7 clusters, the Silhouette Coefficient test yielded a score of 0.504.
The Best Nurse Performance Recommendation Model with Integration of AHP and Weighted Product Methods Fatkhurrochman, Fatkhurrochman; Kanafi, Kanafi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 6 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i6.5529

Abstract

This study aims to develop a recommendation model for identifying the best nurse performance by integrating the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods. Nurse performance plays a vital role in determining the quality of healthcare services; however, existing performance evaluations are often subjective and lack transparency. This situation leads to dissatisfaction among nurses and reduces work motivation. Therefore, a system that provides objective and fair evaluation is needed. The AHP method is employed to determine the priority weights of nurse performance criteria through pairwise comparisons, while the WP method is applied to rank nurses based on the assigned weights. The criteria used include Technical Competence, Professional Attitude, Teamwork, and Patient Satisfaction. This research adopts a Research and Development (R&D) approach, which involves data collection, criteria identification, AHP weighting, web-based system development, and model validation and evaluation. The results indicate that integrating the AHP and WP algorithms can produce a comprehensive and practical nurse performance recommendation model that enhances decision-making efficiency and accuracy in hospitals. The best nurse performance recommendation resulted in Wulandari achieving the highest score of 0.3251.
Co-Authors Ahmad Wildan L Alfatta, Hanif Arif Rahman Saleh Dwi Astuti Farida Yunita Fatimah Nur Arifah handayani, riska dwi Joko Purwanto Joko Purwanto Juwari Juwari Kanafi, Kanafi Kapti . Kapti Kapti, Kapti Khasanah, Ilfi Laili Kusrini, Kusrini Laidestifre Putri Santoso Moch Ali mahmudi Mohammad Apriniyadi Muhammad Abdul Muin Muhammad Farid Muqorobin Muqorobin Muqorobin, Muqorobin Mustofa, Khaoirul Nugroho, Adlan Riska Dwi Handayani Sri Waluyo Sri Waluyo Sugeng Wahyudiono Sugeng Wahyudiono Sukris Sutiyatno Tri Yusnanto Ulinuha, Zakya Faaza Wahyu Priyoatmoko Wijaya Widjanarka Natasaputra Yeza Febriani