Analisis Yuridis Ketentuan-Ketentuan Pemrosesan Data Pribadi Berdasarkan Persetujuan Pada Aplikasi Identitas Kependudukan Digital

This study analyzes the disclaimer of liability by personal data controllers and the processing of personal data based on consent within the Digital Population Identity (IKD) application, in light of privacy policies and Indonesian regulations. The research theme stems from the disharmony between the Ministry of Home Affairs Regulation No. 72 of 2022 and Law No. 27 of 2022 on Personal Data Protection (PDP Law). The inclusion of liability disclaimer clauses by data controllers also motivates this study. Using a normative juridical method, it employs statutory, conceptual, and comparative approaches. Legal materials collected through literature reviews are analyzed using grammatical, systematic, and comparative legal interpretation. The findings reveal that crucial information regarding data processing based on consent is often omitted or inconsistent with Article 21(1) of the PDP Law. Additionally, the liability disclaimer clause weakens personal data protection. Therefore, it is necessary to revise the Ministry of Home Affairs Regulation No. 72 of 2022 to clarify data processing purposes, data types and relevance, retention periods, data subject rights, as well as enhancing data security and digital service interoperability, as implemented in the Besluit Digitale Overheid in the Netherlands.

Authors

Institutions

Publication Details

Journal
Rechtjiva
Published
2025-03-24
DOI
https://doi.org/10.21776/rechtjiva.v2n1.8
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analisis Yuridis Ketentuan-Ketentuan Pemrosesan Data Pribadi Berdasarkan Persetujuan Pada Aplikasi Identitas Kependudukan Digital

Afrizal Mukti Wibowo, Diah Pawestri Maharani, Diwandaru Galih Pradipto
Rechtjiva
Data Mining and Machine Learning Applications
article

Analisis Yuridis Ketentuan-Ketentuan Pemrosesan Data Pribadi Berdasarkan Persetujuan Pada Aplikasi Identitas Kependudukan Digital

Afrizal Mukti Wibowo, Diah Pawestri Maharani, Diwandaru Galih Pradipto
article en

Abstract

This study analyzes the disclaimer of liability by personal data controllers and the processing of personal data based on consent within the Digital Population Identity (IKD) application, in light of privacy policies and Indonesian regulations. The research theme stems from the disharmony between the Ministry of Home Affairs Regulation No. 72 of 2022 and Law No. 27 of 2022 on Personal Data Protection (PDP Law). The inclusion of liability disclaimer clauses by data controllers also motivates this study. Using a normative juridical method, it employs statutory, conceptual, and comparative approaches. Legal materials collected through literature reviews are analyzed using grammatical, systematic, and comparative legal interpretation. The findings reveal that crucial information regarding data processing based on consent is often omitted or inconsistent with Article 21(1) of the PDP Law. Additionally, the liability disclaimer clause weakens personal data protection. Therefore, it is necessary to revise the Ministry of Home Affairs Regulation No. 72 of 2022 to clarify data processing purposes, data types and relevance, retention periods, data subject rights, as well as enhancing data security and digital service interoperability, as implemented in the Besluit Digitale Overheid in the Netherlands.

RechtjivaVol. 2(1)
University of Brawijaya (ID)
Openalex Percentile: Top 64%
Data Mining and Machine Learning Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.