Dual water choices: the assessment of the influential factors on water sources choices using unsupervised machine learning market basket analysis

• Main Authors: Tiyasha, Tiyasha, Bhagat, Suraj Kumar, Fituma, Firaol, Tung, Tran Minh, Shahid, Shamsuddin, Yaseen, Zaher Mundher
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2021
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/95505/1/ShamsuddinShahid2021_DualWaterChoicestheAssessment.pdf; http://eprints.utm.my/id/eprint/95505/; http://dx.doi.org/10.1109/ACCESS.2021.3124817

An unsupervised machine learning model of association rule known as market basket analysis is proposed in this study to analyze the influence of various socio-economic factors on the choice of the water source. Data of 51 socio-economic factors collected from 295 individuals living in 65 households in Ambo city in the Oromia region of Ethiopians were used for this purpose. The results revealed (i) 64% of the family preferred multiple water sources (i.e., public tap and river water), (ii) the water was collected females in 92% of the households, and (iii) majority of people preferred bathing and laundering in the river (support = 32% and confidence = 87%). Direct utilization of river water is not a preferable choice for the user since it may lead to severe health issues and cause water pollution from bathing and laundering. Education and monthly income have a significant impact on the choices of water sources. Local management authorities can improve sanitation and public health management using the results obtained in the study. The paper only gives a glimpse of the important factors that should be considered for improving the way of life for the underdeveloped areas of the world using advanced machine learning techniques.