Sri Kusumadewi, Rahadian Kurniawan, Elyza Gustri Wahyuni, Aridhanyati Arifin, Linda Rosita, Mutmainna Mutmainna

Aggregation Model to Determine Criteria Weights for Integrated Primary Health Care Information System (IPCIS) Implementation

Introduction

Aggregation model to determine criteria weights for integrated primary health care information system (ipcis) implementation. Determine key criteria weights for Integrated Primary Health Care Information System (IPCIS) implementation. Aggregation models reveal data security as paramount for program priorities.

Abstract

Implementation of the Integrated Primary Health Care Information System (IPCIS) in integrated community health posts (posyandu) is influenced by various factors, including technical aspects, human resources, policies, and data governance. Given the diverse field conditions, the impact of each factor can vary, so it is important to understand the relative importance of each criterion. This study aims to determine the weight of the criteria that influence the implementation of IPCIS in posyandu. Ten people answered the questions correctly (out of 22 respondents), including cadres, sub-district staff, and health workers from Tirtorahayu Village. Respondent preferences were collected using three approaches: rank-based aggregation (Borda, Condorcet, Copeland), score-based aggregation (average), and voting-based aggregation (plurality and majority) to obtain the criteria weights (w) and a comparative analysis between the approaches. The findings demonstrate that the IPCIS criteria for security and protection of personal data were consistently given the highest weights. In the ranking-based aggregation approaches (w_Borda=0.11, w_Condorcet=0.20, w_Copeland=0.19). In score-based aggregation approaches (w=0.11). In voting-based aggregation approaches (w=0.15). It is indicating a strong group consensus regarding the importance of these aspects in IPCIS implementation. The combination of ranking-based and score-based aggregation resulted in stable IPCIS implementation criterion weights that reflected group consensus, with voting-based aggregation acting as validation. The practical implication is that the obtained weighted criteria can be used as a basis for determining program priorities and resource allocation when implementing IPCIS.

Review

This study presents a timely and relevant investigation into prioritizing criteria for the successful implementation of an Integrated Primary Health Care Information System (IPCIS) in community health posts (posyandu). By systematically determining the weights of various influencing factors, the authors provide a valuable framework for resource allocation and strategic planning. The core contribution lies in its multi-pronged methodological approach, utilizing a diverse set of aggregation techniques—rank-based, score-based, and voting-based—to establish a robust consensus on criteria importance. The consistent finding that "security and protection of personal data" emerged as the highest-weighted criterion across all approaches is a critical insight, underscoring its foundational importance in healthcare information systems. Methodologically, the paper demonstrates a commendable effort to employ multiple aggregation models (Borda, Condorcet, Copeland, average, plurality, and majority) for comparative analysis, which strengthens the validity of the identified criteria weights and offers a nuanced understanding of stakeholder preferences. This comparative approach is a significant strength, providing internal validation for the consensus reached. However, a potential limitation that warrants further detail in the full paper is the respondent pool. While comprising diverse stakeholders (cadres, sub-district staff, health workers), the sample size of "Ten people answered the questions correctly (out of 22 respondents)" is relatively small. The phrase "answered correctly" also introduces ambiguity; clarification on what constitutes a 'correct' answer and the implications of the other 12 respondents' exclusion would be beneficial for understanding potential biases or limitations in representativeness. The practical implications of this research are significant and clearly articulated. The derived weighted criteria offer a tangible tool for policymakers and program managers to guide decision-making, optimize resource allocation, and prioritize efforts during IPCIS implementation. By highlighting data security as the paramount concern, the study provides actionable intelligence for system developers and implementers to focus on robust data protection mechanisms. Future research could expand upon this foundation by engaging a larger and more geographically diverse respondent base to enhance the generalizability of the findings and explore regional variations in criteria importance. Additionally, a detailed exposition of the specific criteria evaluated would further enrich the understanding and applicability of the study's results.

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