Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Building of Informatics, Technology and Science
Yantria Gusta Nugraha
Universitas Muhammadiyah Magelang, Magelang
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Algoritma K-Means Clustering untuk Daerah Penyebaran Sampah Kelurahan Yantria Gusta Nugraha; Maimunah Maimunah; Pristi Sukmasetya
Building of Informatics, Technology and Science (BITS) Vol 5 No 2 (2023): September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i2.4158

Abstract

Waste in Indonesia, especially in Magelang City, has become a serious problem due to rapid population growth. Waste management issues, including landfills and collection, need effective handling. Data mining methods, such as K-Means clustering, can help identify areas with the highest levels of waste generation. This approach provides insights for the development of a more focused and efficient waste management strategy, a significant contribution to the improvement of Magelang City. By identifying the areas with the highest waste generation, waste management measures can be directed more efficiently and effectively. This includes increasing the transparency, capacity, and role of waste banks, as well as other efforts to reduce the negative impact of waste on the environment and human health. After clustering, the waste in Magelang City was grouped into 3 clusters according to the supplier area and the volume of waste. Then after the evaluation stage with the silhouette score displays a value of 0.79 which is a good value because it is close to the value of 1.0. With this method, it is expected that the city government in handling waste in Magelang city can be done optimally, efficiently, and on target
Co-Authors Maimunah Sukmasetya, Pristi