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All Journal PROFICIO: Jurnal Pengabdian Masyarakat Journal of Informatics and Communication Technology (JICT) Journal of Informatics and Communication Technology (JICT) Computer Journal Proceeding of Community Service and Engagement
Hertanto Suryoprayogo
Universitas Telkom
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Mathematics Social Sciences Other

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Journal : computer journal

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Penerapan Metode OWASP IoT Top 10 dalam Analisis Kerentanan Keamanan Perangkat Internet of Things: Studi Kasus Smart Waste Arif Rahman Hakim; Rizki Surya Permana; Demi Adidrana; Hertanto Suryoprayogo; Deny Haryadi
Computer Journal Vol. 4 No. 2 (2026): August
Publisher : Yayasan Pendidikan Mitra Mandiri Aceh (YPMMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58477/cj.v4i2.471

Abstract

This study examines security vulnerabilities in a publicly accessible IoT-based smart waste system using Nmap, Wireshark, and OWASP ZAP to assess network services, packet traffic, and the web application layer. Results were mapped to the OWASP IoT Top 10 (2018). Because the assessment was external black-box testing without exploitation, the mapping is indicative rather than comprehensive. Nmap identified several active TCP ports, although only six open ports were explicitly documented. Wireshark captured 62,591 packets, indicating port-scanning activity and ongoing TCP communication. OWASP ZAP identified 14 web application weaknesses: six medium, five low, and three informational, with no high-risk findings. Four OWASP IoT Top 10 categories (I2, I3, I7, and I9) were supported by direct evidence, while I1 and I5 require further verification and I4, I6, I8, and I10 were outside the testing scope. Key risks involved insecure network services, default settings, and inadequate data protection during transmission and storage.
Penerapan Ensemble Machine Learning Random Forest dan XGBoost dengan Explainable Artificial Intelligence (XAI) untuk Prediksi Urban Heat Island dan Land Surface Temperature di DKI Jakarta Hertanto Suryoprayogo; Widang Muttaqin; Annisa Desianty
Computer Journal Vol. 4 No. 2 (2026): August
Publisher : Yayasan Pendidikan Mitra Mandiri Aceh (YPMMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58477/cj.v4i2.501

Abstract

The Urban Heat Island (UHI) effect in tropical urban settings arises from interactions among built surfaces, vegetation, water bodies, and urban energy dynamics. This study modeled Land Surface Temperature (LST) in DKI Jakarta using Random Forest and XGBoost optimized with RandomizedSearchCV and 5-fold cross-validation. The analysis used 5,821 grid points at approximately 300 m resolution and five predictors: road density, NDVI, NDBI, NDWI, and distance to green open space. XGBoost slightly outperformed Random Forest, achieving R² = 0.507 and RMSE = 1.830°C compared with R² = 0.497 and RMSE = 1.849°C, although the difference was not statistically significant (Wilcoxon, p = 0.352). The RF-XGBoost ensemble did not improve performance due to very high residual correlation (r = 0.988) and a theoretical ensemble standard deviation reduction of only ~0.3%. SHAP analysis identified NDBI as the dominant predictor (mean|SHAP| = 0.986), with the strongest interaction between NDBI and road density (0.101). Hyperparameter tuning changed model ranking, statistical significance, and the leading SHAP interaction pair.
Co-Authors Alfarhad Maulana Annisa Desianty Arif Rahman Hakim Arif Rahman Hakim Arif Rahman Hakim Dede Rizki Dede Rizki Demi Adidrana Deny Haryadi Dwina Satrinia Ilham Roni Yansyah Irgi Shalby Ramadhani Maryam Laurannisa Williams Muhammad Radja Rizkyana Muhammad Zidan Alfarizi Muttaqin, Widang Nurul Ilmi Rania Zamrizq Rizki Surya Permana Sasmi Hidayatul Yulianing Tyas Siti Zahrotul Fajriyah