Analysis and Modeling of Population Administration Information System Business Processes Using BPI and BPMN

Population administration services are a form of public service that requires effective, efficient processes to deliver optimal services to the community. However, in practice, several obstacles persist, including data re-entry, discrepancies between physical documents and system data, and continued reliance on manual processes, which contribute to service delays. This study aims to analyze and improve the business process of population administration services in the Population Administration Information System (SIAK) at the Population and Civil Registration Office of Bojonegoro Regency using the Business Process Improvement (BPI) and Business Process Model and Notation (BPMN) methods. Data were collected through observations and interviews with sub-district operators and Disdukcapil officers to understand the existing process flow. The analysis was conducted through As-Is process modeling, bottleneck identification, value-added and non-value-added activity analysis, and the design of a To-Be process model as the proposed improvement. The results showed that the main bottlenecks were data re-entry activities and dependence on manual processes, which increased service time. The proposed improvements simplified the service flow, reduced non-value-added activities, and ultimately improved overall process efficiency. Based on the measurement results, service processing time decreased from 55 minutes to 38 minutes, resulting in a 30.9% improvement in efficiency.

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Publication Details

Journal
MALCOM Indonesian Journal of Machine Learning and Computer Science
Published
2026-10-30
DOI
https://doi.org/10.57152/malcom.v6i4.3002
Primary Topic
Business Process Modeling and Analysis
Type
article
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article

Analysis and Modeling of Population Administration Information System Business Processes Using BPI and BPMN

Jauhara Rana Budiani, Zakky Alawi, Nihayatus Sa'adah
MALCOM Indonesian Journal of Machine Learning and Computer Science
Business Process Modeling and Analysis
article

Analysis and Modeling of Population Administration Information System Business Processes Using BPI and BPMN

Jauhara Rana Budiani, Zakky Alawi, Nihayatus Sa'adah
article en

Abstract

Population administration services are a form of public service that requires effective, efficient processes to deliver optimal services to the community. However, in practice, several obstacles persist, including data re-entry, discrepancies between physical documents and system data, and continued reliance on manual processes, which contribute to service delays. This study aims to analyze and improve the business process of population administration services in the Population Administration Information System (SIAK) at the Population and Civil Registration Office of Bojonegoro Regency using the Business Process Improvement (BPI) and Business Process Model and Notation (BPMN) methods. Data were collected through observations and interviews with sub-district operators and Disdukcapil officers to understand the existing process flow. The analysis was conducted through As-Is process modeling, bottleneck identification, value-added and non-value-added activity analysis, and the design of a To-Be process model as the proposed improvement. The results showed that the main bottlenecks were data re-entry activities and dependence on manual processes, which increased service time. The proposed improvements simplified the service flow, reduced non-value-added activities, and ultimately improved overall process efficiency. Based on the measurement results, service processing time decreased from 55 minutes to 38 minutes, resulting in a 30.9% improvement in efficiency.

MALCOM Indonesian Journal of Machine Learning and Computer Science
Universitas Nahdlatul Ulama Indonesia (ID), Universitas Nahdlatul Ulama Sunan Giri (ID)
Openalex Percentile: Top 6%
Business Process Modeling and Analysis
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Analysis and Modeling of Population Administration Information System Business Processes Using BPI and BPMN — Jauhara Rana Budiani, Zakky Alawi, et al. · MALCOM Indonesian Journal of Machine Learning and Computer Science (2026) | TGRS Research Map | TGRS