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All Journal INTECOMS: Journal of Information Technology and Computer Science Journal of Innovation Research and Knowledge
Taswanda Taryo
Universitas Pamulang, Tangerang Selatan
Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences

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MODEL EFEKTIVITAS IMPLEMENTASI K3 DI FASILITAS NUKLIR: INTEGRASI STANDAR BAPETEN DAN BUDAYA KESELAMATAN KERJA Ridwan Taufik Hidayat; Umi Rusilowati; Hamsinah B; Fitri Marsela; Taswanda Taryo
Journal of Innovation Research and Knowledge Vol. 6 No. 1 (2026): Juni 2026
Publisher : Bajang Institute

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Abstract: This study aims to formulate an effectiveness model for Occupational Safety and Health (OSH) implementation at the G.A. Siwabessy Multipurpose Reactor (RSG-GAS) Facility by integrating the regulatory standards of the Nuclear Energy Regulatory Agency (BAPETEN) with the reinforcement of safety culture. Using a qualitative approach with a case study design, data were collected through technical document reviews, field observations, and in-depth interviews with key personnel. The results indicate that the effectiveness of the OSH system cannot be achieved solely through administrative regulatory compliance. Instead, it requires an integrated model where BAPETEN standards serve as the structural framework, while safety culture acts as the operational driver. The critical determinants of this model's effectiveness include high-level management commitment, worker situational awareness, two-way safety communication, and the consistent application of field procedures. The study concludes that the ideal effectiveness model in a nuclear facility is a synergy between compliance-based safety and behavior-based safety. These findings are expected to serve as a strategic reference and an evaluation model for nuclear facility managers to enhance worker protection standards and facility security sustainably.
PEMODELAN NILAI B-VALUE UNTUK MITIGASI RISIKO GEMPA DI ZONA MEGATHRUST SELATAN JAWA MENGGUNAKAN LSTM, SVM, DAN RANDOM FOREST Ismi Amalia; Taswanda Taryo; Sudarno Wiharjo
INTECOMS: Journal of Information Technology and Computer Science Vol. 9 No. 2 (2026): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/apcvbd82

Abstract

Zona Megathrust Selatan Jawa merupakan wilayah subduksi aktif dengan tingkat kegempaan tinggi yang rawan terhadap bencana gempa bumi besar dan tsunami, di mana parameter b-value bertindak sebagai indikator kritis dalam memetakan akumulasi tegangan tektonik. Penelitian ini bertujuan memodelkan dinamika deret waktu b-value secara spasio-temporal menggunakan metode Maximum Likelihood Estimation (MLE) yang dikombinasikan dengan teknik pemulusan jendela bergerak serta tiga pendekatan kecerdasan buatan, yaitu Long Short-Term Memory (LSTM), Support Vector Machine (SVM/SVR), dan Random Forest (RF). Hasil evaluasi menunjukkan bahwa pada konfigurasi standar, pendekatan SVM memberikan akurasi numerik terbaik karena ketangguhannya mengolah dataset berukuran sedang tanpa gejala overfitting, disusul oleh efisiensi model RF, meskipun keduanya menunjukkan keterbatasan berupa gejala perkiraan malas (lazy prediction) atau penundaan fase waktu. Sebaliknya, superioritas arsitektural sekuensial yang sesungguhnya berhasil dicapai oleh jaringan LSTM pada skenario eksperimen kontrol berbasis masukan data seketika, di mana pemotongan rantai historis jangka panjang mampu membebaskan model dari bias inersia temporal sehingga mekanisme gerbang pengaturnya bekerja jauh lebih responsif, adaptif, dan presisi dalam melacak kausalitas perubahan stres tektonik tanpa penundaan fase naif.
Co-Authors Fitri Marsela Hamsinah B Ismi Amalia Ridwan Taufik Hidayat Sudarno Wiharjo Umi Rusilowati