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All Journal JPM (Jurnal Pemberdayaan Masyarakat) Indonesian Journal of Data and Science Journal of Embedded Systems, Security and Intelligent Systems
Abdul Rachman Manga'
Universitas Muslim Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Implementasi Sistem Layanan Mandiri untuk Efisiensi Administrasi Desa Biji Nangka Kabupaten Sinjai Purnawansyah; Rahma Puspitasari; Abdul Rachman Manga'; Herdianti Darwis; Sitti Nurhalimah
Jurnal Pemberdayaan Masyarakat Vol 11 No 1 (2026): Mei
Publisher : Direktorat Penelitian dan Pengabdian kepada Masyarakat (DPPM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/jpm.v11i1.13200

Abstract

This community service program aims to improve administrative efficiency in Biji Nangka Village, which previously used manual processes and was prone to delays, inconsistencies, and the risk of archive loss. This activity implemented a website-based self-service system and provided training to village officials on the use of key features such as digital letter management, automatic numbering, and electronic archive storage. A total of 17 participants participated in the training and all successfully operated the system. Evaluation results showed that the time to create letters was reduced from 10–15 minutes to 3–5 minutes. Furthermore, the results of the pre-test and post-test comparison showed a 9.412% increase in participant understanding, indicating the effectiveness of the training in improving the digital competence of village officials. Overall, this program has had a positive impact on improving the quality of administrative services and supporting the realization of digital-based village governance.
A Comparative Study of LSTM and CNN Models in SQL Injection Attack Detection Abdul Rachman Manga'; Wahyu Kadri Rahmat Suat Suat; Huzain Azis
Indonesian Journal of Data and Science Vol. 7 No. 2 (2026): Indonesian Journal of Data and Science
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v7i2.460

Abstract

Introduction: SQL Injection (SQLi) remains a critical cybersecurity threat because it exploits vulnerabilities in user input validation and can compromise the confidentiality, integrity, and availability of information systems. This study compares Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) architectures for detecting malicious SQL queries under identical experimental conditions. Method: A publicly available dataset containing 148,327 malicious and benign SQL query instances was preprocessed through missing-value removal, label encoding, tokenization, sequence transformation, padding, and embedding representation. LSTM and CNN models were evaluated using three train-test split scenarios of 70:30, 80:20, and 90:10. Performance was assessed using accuracy, precision, recall, F1-score, and confusion matrices, with the 80:20 split selected for detailed evaluation. Results and Discussion: LSTM consistently achieved higher accuracy across the evaluated splits, ranging from 97.84% to 98.00%. Under the 80:20 configuration, LSTM achieved 97.86% accuracy, 99.34% precision, 96.55% recall, and a 97.92% F1-score, compared with CNN at 97.00%, 97.68%, 96.56%, and 97.12%, respectively. LSTM also reduced false positives from 356 to 99, demonstrating better discrimination between legitimate and malicious queries. Conclusion: LSTM provides more reliable SQL Injection detection than CNN by better capturing sequential dependencies within SQL query structures, making it a promising approach for practical cybersecurity systems
Design and Build an Automatic Soil Spraying Device on Soil Moisture Using Soil Moisture Sensors Abdul Rachman Manga'; Dewi Widyawati; Fahmi; Samsul
Journal of Embedded Systems, Security and Intelligent Systems Vol 5, No 1 (2024): March 2024
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v5i1.1228

Abstract

The conventional manual watering method employed by cultivators often results in uneven watering and inconsistent water levels during each irrigation session. To address this problem, automatic watering tools are commonly adopted that utilize soil moisture sensors for efficient watering. However, challenges arise in dealing with diverse soil conditions across multiple planting media. In response to these challenges, the author proposed the design and development of a soil moisture-based watering device utilizing NodeMCU ESP32 as a microcontroller connected to six soil moisture sensors. This tool aims to provide a solution for watering six different soil media with varying conditions. The system incorporates six solenoid valves to control water channels, with a relay regulating the valve performance. The testing and implementation involve watering each soil medium when the sensor detects humidity levels exceeding 2047 bits. The preliminary tests demonstrated successful operation, particularly with solenoid valve 1 exhibiting consistent performance across ten trials, leading to positive outcomes for all six solenoid valves. Overall, the proposed tool proved effective in watering different soil media, with successful results in eight out of ten trials.
Co-Authors Dewi Widyawati Fahmi Herdianti Darwis Huzain Azis Purnawansyah Purnawansyah Rahma Puspitasari Samsul Sitti Nurhalimah Wahyu Kadri Rahmat Suat Suat