Hierarchical Cluster Analysis Based on Waste Sources in Indonesia in 2022

Authors

  • Syarif Hidayatullah Universitas Negeri Surabaya
  • A’yunin Sofro Universitas Negeri Surabaya

DOI:

https://doi.org/10.21512/comtech.v15i2.11088

Keywords:

hierarchical cluster, waste sources, waste management

Abstract

Waste, as a result of human activities, is a complex issue that requires appropriate solutions. With the increasing volume of waste, waste management in Indonesia has become a major challenge. The research examined the waste problem in Indonesia, focusing on analyzing and grouping 311 regencies/cities based on waste sources in 2022. The research also aimed to provide an in-depth understanding of waste characteristics in each region as a basis for designing more effective waste management policies at the regional level. The research applied hierarchical clustering, combining Ward’s method with Euclidean distance analysis. The analysis shows 14 significant clusters with different waste composition characteristics. Interpretation of the cluster results identifies areas with low to high levels of waste. Clusters 1 to 4 have relatively little waste composition, while clusters 5 to 14 have increasing waste levels, with cluster 14 being an area with very high waste levels. The research results are expected to serve as a basis for the government to formulate more targeted and adaptive policies for handling waste in the future. The implications include improving waste management systems, recycling programs, and community education. By understanding the waste composition of each region, the government can implement solutions that suit its needs. The research provides an overview of the waste problem at the regional level in Indonesia and can be the basis for developing more effective policies. In future research, it is recommended to use more accurate and complete waste data in each regency/city for more in-depth results.

Dimensions

Plum Analytics

Author Biographies

Syarif Hidayatullah, Universitas Negeri Surabaya

Data Science Department, Faculty of Mathematics and Natural Sciences

A’yunin Sofro, Universitas Negeri Surabaya

Actuarial Science Department, Faculty of Mathematics and Natural Sciences

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Published

2024-11-12
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