Exploratory data analysis of community behavior towards the generation of solid waste using k-means and social indicators

• Autores: Izquierdo Horna, Luis Antonio, Zevallos Ruiz, José Augusto, Damazo Amante, Miker, Yanayaco Lazo, Dayvis Junior
• Formato: artículo
• Fecha de Publicación: 2021
• Institución: Universidad Tecnológica del Perú
• Repositorio: UTP-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.utp.edu.pe:20.500.12867/4617
• Enlace del recurso: https://hdl.handle.net/20.500.12867/4617; https://doi.org/10.18280/ijsdp.160508
• Nivel de acceso: acceso abierto
• Materia: Machine learning; Social indicators; Waste management; Aprendizaje automático; Indicadores sociales; Residuos sólidos; https://purl.org/pe-repo/ocde/ford#5.00.00

In Peru, solid waste accumulation has been constant for decades and impacts 72% of local governments, affecting 42% of the population. These numbers show new tools are required to better understand this phenomenon and develop appropriate mitigation methods. In this light, this research proposes an exploratory analysis of the study population against the accumulation of solid waste. For this, the study proposes the segmentation of a specific population through a set of social indicators grouped into three categories of analysis (i.e., sociocultural, sociodemographic, and socioeconomic) and, in turn, assess the geographic proximity between each group of people segmented according to the parameters used for this study, and the informal points of accumulation of MSW. To segment the study population, an unsupervised classification model (i.e., K-means) was used. For methodological purposes, the Puente Piedra district was chosen as a case study. The results show that the predominant population is framed between the ages of 36 to 45, with an intermediate educational level (i.e., secondary school) and an approximate monthly income of $ 300. In addition, the predominant family structure includes up to four members living in the same household. Finally, it is observed that the behavior of people who live close as neighbors is similar and is also related to the geographic location of the dumps.