Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, Indonesia
This study investigates the factors influencing illegal waste dumping in Bangkalan District, a rapidly urbanizing rural area in Indonesia. Illegal dumping has become a significant environmental and public health concern due to inefficient waste management systems, irregular collection schedules, and...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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| Series: | Waste Management Bulletin |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2949750725000641 |
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| author | Christia Meidiana Florin-Constantin Mihai Tonni Agustiono Kurniawan Diva Avriska Septiana Hariyani Ratan Kumar Ghosh Kristianus Oktriono Wing Keung Wong Franca Brugman |
| author_facet | Christia Meidiana Florin-Constantin Mihai Tonni Agustiono Kurniawan Diva Avriska Septiana Hariyani Ratan Kumar Ghosh Kristianus Oktriono Wing Keung Wong Franca Brugman |
| author_sort | Christia Meidiana |
| collection | DOAJ |
| description | This study investigates the factors influencing illegal waste dumping in Bangkalan District, a rapidly urbanizing rural area in Indonesia. Illegal dumping has become a significant environmental and public health concern due to inefficient waste management systems, irregular collection schedules, and inadequate infrastructure. The research identifies key socio-economic, demographic, and technical factors contributing to illegal dumping behaviors. Through data collected from 387 households, a Multilinear Regression (MLR) analysis reveals that six factors such as low income, lower education levels, larger family sizes, irregular waste collection services, easy accessibility and short distance to illegal dump site (IDS) significantly increase illegal dumping rates. The findings emphasize the need for improving waste management infrastructure, enhancing public awareness, and addressing economic constraints to mitigate illegal dumping. By identifying the primary drivers of illegal dumping, this research contributes to achieving several United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 3 (Good Health and Well-being), and SDG 12 (Responsible Consumption and Production). The study concludes with policy recommendations for improved waste management and enforcement, offering insights for addressing this issue in other rapidly urbanizing rural areas. |
| format | Article |
| id | doaj-art-415ba2c71cd3439f8abc456624cc29c3 |
| institution | Kabale University |
| issn | 2949-7507 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Waste Management Bulletin |
| spelling | doaj-art-415ba2c71cd3439f8abc456624cc29c32025-08-20T05:08:26ZengElsevierWaste Management Bulletin2949-75072025-09-013310023510.1016/j.wmb.2025.100235Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, IndonesiaChristia Meidiana0Florin-Constantin Mihai1Tonni Agustiono Kurniawan2Diva Avriska3Septiana Hariyani4Ratan Kumar Ghosh5Kristianus Oktriono6Wing Keung Wong7Franca Brugman8Department of Regional and Urban Planning, Faculty of Engineering, Brawijaya University, Malang, Indonesia; Corresponding author at: Department of Regional and Urban Planning, Faculty of Engineering, Brawijaya University, Jl. MT. Haryono 167, Malang 64147, East Java Province, Indonesia.CERNESIM Environmental Research Center, Department of Exact Sciences and Natural Sciences, Institute of Interdisciplinary Research, Alexandru Ioan Cuza, University of Iasi, Iasi, RomaniaCollege of Environment and Ecology, Xiamen University, Xiamen, ChinaDepartment of Regional and Urban Planning, Faculty of Engineering, Brawijaya University, Malang, IndonesiaDepartment of Regional and Urban Planning, Faculty of Engineering, Brawijaya University, Malang, IndonesiaSustainable and Renewable Energy Development Authority (SREDA) Ministry of Power, Energy and Mineral Resources, BangladeshDepartment of Business Administration, Asia University, Taichung, TaiwanDepartment of Finance, Fintech & Blockchain Research Center, and Big Data Research Center, Asia University, TaiwanFaculty of Social and Behavioural Sciences, University of Amsterdam, the NetherlandsThis study investigates the factors influencing illegal waste dumping in Bangkalan District, a rapidly urbanizing rural area in Indonesia. Illegal dumping has become a significant environmental and public health concern due to inefficient waste management systems, irregular collection schedules, and inadequate infrastructure. The research identifies key socio-economic, demographic, and technical factors contributing to illegal dumping behaviors. Through data collected from 387 households, a Multilinear Regression (MLR) analysis reveals that six factors such as low income, lower education levels, larger family sizes, irregular waste collection services, easy accessibility and short distance to illegal dump site (IDS) significantly increase illegal dumping rates. The findings emphasize the need for improving waste management infrastructure, enhancing public awareness, and addressing economic constraints to mitigate illegal dumping. By identifying the primary drivers of illegal dumping, this research contributes to achieving several United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities), SDG 3 (Good Health and Well-being), and SDG 12 (Responsible Consumption and Production). The study concludes with policy recommendations for improved waste management and enforcement, offering insights for addressing this issue in other rapidly urbanizing rural areas.http://www.sciencedirect.com/science/article/pii/S2949750725000641Illegal dumpingWaste managementUrbanizationMulti-linear regressionBangkalan-Indonesia |
| spellingShingle | Christia Meidiana Florin-Constantin Mihai Tonni Agustiono Kurniawan Diva Avriska Septiana Hariyani Ratan Kumar Ghosh Kristianus Oktriono Wing Keung Wong Franca Brugman Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, Indonesia Waste Management Bulletin Illegal dumping Waste management Urbanization Multi-linear regression Bangkalan-Indonesia |
| title | Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, Indonesia |
| title_full | Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, Indonesia |
| title_fullStr | Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, Indonesia |
| title_full_unstemmed | Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, Indonesia |
| title_short | Application of Multi linear regression (MLR) analysis for determining predictors of illegal dumping in rapidly urbanized rural areas: A case study of Bangkalan District, Indonesia |
| title_sort | application of multi linear regression mlr analysis for determining predictors of illegal dumping in rapidly urbanized rural areas a case study of bangkalan district indonesia |
| topic | Illegal dumping Waste management Urbanization Multi-linear regression Bangkalan-Indonesia |
| url | http://www.sciencedirect.com/science/article/pii/S2949750725000641 |
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