Predicting Community Participation of Waste Separation for Informal Waste Recycling Facility using Binary Logistic Regression Model


  • Miftakhul Azis Universitas Brawijaya, Indonesia
  • Christia Meidiana Universitas Brawijaya, Indonesia
  • Abdul Wahid Hasyim Universitas Brawijaya, Indonesia
  • Tran Nguyet Hanoi School of Business & Management, Vietnam
  • Maria Evelyn Universitas Brawijaya, Indonesia
  • Wildan Suhartini Debrecen University, Hungary



Waste Bank, Community Participation, Logistic Regression


Waste bank is informal waste recycling facility using the principle of community participation in reducing waste generation. Berkah Bersatu Waste bank was established in 2021 but the number of registered customers remains constant. Therefore, this study investigates participation decisions made by the villager. This cross-sectional study used data collected from 148 households randomly. Through a series of analysis, the impact of 24 influential factors on participation decision-making was explored using logistic regression analyses. The results showed seven variables are positively related to community participation in waste bank i.e. age, residence status, trash bin availability, knowledge of environmental issues, individual’s interest, intrinsic motivation, and norm existence. Probability calculation using the model shows the maximum probability is 99% if all determinants play role in the area indicating that most villagers are willing to participate in waste separation and reduction as they become WB member.


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How to Cite

M. Azis, C. Meidiana, A. W. Hasyim, T. Nguyet, M. Evelyn, and Wildan Suhartini, “Predicting Community Participation of Waste Separation for Informal Waste Recycling Facility using Binary Logistic Regression Model”, CIVENSE, vol. 7, no. 1, pp. 71–80, Apr. 2024.