Factors related to the functionality of community-based rural water supply and sanitation program in Indonesia

Abstract

This study used multinomial logistic regression and Bayesian belief networks (BBN) to analyze factors influencing the functionality of the community-based rural drinking water supply and sanitation program (PAMSIMAS) in Indonesia. 28,936 PAMSIMAS projects in 33 provinces in Indonesia were analyzed. The data indicates that 85.4% of the water supply systems were fully functioning, 9.1% were partially functioning, and 5.5% were not functioning. In the regression analysis, good management is positively associated with functionality and a high investment per capita is negatively associated with the functionality. The latter suggests the need for comprehensive economic analysis in the feasibility study in scattered housing sites and remote-undeveloped areas. We also found that high community participation at the beginning of the project was associated with the not functioning system, while women’s participation was positively associated with the functionality. Furthermore, the household connection is more likely to be functioning than communal connection. BBN analysis shows if the beneficiaries do not pay for water, the probability of not functioning systems is 20 times higher than systems with fee collection. Moreover, the combination of strong management, strong financial status, and household connection rather than communal connection increases the probability of fully functioning to 98%. Improvement of data collection is also necessary to monitor the current conditions of all PAMSIMAS systems in Indonesia. This study offers a country-level perspective for better implementation of the community-based rural water supply and sanitation program in developing countries.

Keywords

Rural water supply / PAMSIMAS / Functionality / Indonesia / Bayesian belief networks / Logistic regression

Declaration of Competing Interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi: 10.1016/j.geosus.2022.12.002.

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