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All Journal Indonesian Journal of Data and Science Kajian Ilmiah Hukum dan Kenegaraan
Idhom, Muhammad
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Transformation of Indonesia’s Licensing System: A Juridical Analysis of Risk-Based Approach Implementation in Practice Irawan, Donny; Pattynama, Francis Maryanne; Pradita, Fajar; Idhom, Muhammad; Prasadja, Yanas Putra; Hayakawa, Narumi; Harya, Gyska Indah
Kajian Ilmiah Hukum dan Kenegaraan Vol 4 No 2 (2025): Desember
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/kihan.v4i2.6352

Abstract

Purpose: This study aims to analyze the legal basis, implementation, and challenges of Risk-Based Business Licensing (Perizinan Berusaha Berbasis Risiko/PBBR) as regulated in Government Regulation Number. 28 of 2025 in Indonesia. Methodology/Approach: This study employs a normative empirical approach. Normatively, it examines the administrative law principles underlying PBBR, whereas empirically it analyzes its implementation through the Online Single Submission (OSS) system and its impact on public service efficiency. Results/Findings: This study finds that PBBR represents a significant reform in Indonesian administrative law by applying the principles of proportionality, legal certainty, and public benefit. Empirically, its implementation has improved the efficiency of business licensing services, particularly through faster processing via the OSS system. However, several substantive and technical challenges remain, including inadequate digital infrastructure, overlapping regional and central regulations, and low legal literacy among micro and small business actors regarding risk classification and standard certification obligations. Conclusions: This study concludes that PBBR improves efficiency and legal certainty but is constrained by infrastructure, regulatory overlap, and low MSME legal literacy. Further improvements are needed. Limitations: This research is limited to regulatory analysis and selected empirical observations and does not include large-scale field surveys or quantitative measurement of business performance outcomes. Contributions: This study contributes to the development of administrative law and public policy literature by providing an integrated analysis of risk-based licensing reform in Indonesia and offering practical recommendations for improving institutional capacity and regulatory harmonization.
Application of the DeepSurv Model to Predict Survival in Patients with Kidney Failure Undergoing Hemodialysis Amanda, Rizki; Damaliana, Aviolla Terza; Idhom, Muhammad
Indonesian Journal of Data and Science Vol. 7 No. 1 (2026): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v7i1.389

Abstract

This study aims to improve survival prediction in patients with kidney failure undergoing hemodialysis, given their high mortality risk. Traditional models such as Cox Proportional Hazards (Cox PH) have limitations in capturing complex and nonlinear relationships in clinical data. Therefore, this study applies DeepSurv, a deep learning–based survival model, and compares its performance with Cox PH and Cox PH Spline. A total of 300 patients were included, with 165 events and 135 censored observations. The data were split into training and testing sets. DeepSurv was implemented using two hidden layers (64 and 32 neurons), a dropout rate of 0.2, and a learning rate of 1e-3. The model was trained for up to 1000 epochs with early stopping at epoch 435. Performance was evaluated using the concordance index (C-index) and time-dependent AUC at 365, 544, and 730 days. Patients were stratified into low-, medium-, and high-risk groups based on predicted scores. Results showed that Cox PH achieved a C-index of 0.913 and average AUC of 0.964, while Cox PH Spline reached 0.917 and 0.971. DeepSurv achieved a C-index of 0.920 and average AUC of 0.969. Performance differences were small, but DeepSurv provided consistent individual risk estimates. In conclusion, DeepSurv is a flexible approach with performance comparable to Cox-based models. Further external validation and clinical evaluation are needed before wider application
Co-Authors Amanda, Rizki Damaliana, Aviolla Terza Donny Irawan, Donny Harya, Gyska Indah Hayakawa, Narumi Pattynama, Francis Maryanne Pradita, Fajar Prasadja, Yanas Putra