Analysis of the Feasibility Level of Determining Retail Prices of Staples Using the K-Means Clustering Method
Keywords:
Data Mining, K-Means, Clustering, PricesAbstract
The rate of economic growth in a region is highly dependent on the role and infrastructure of structured agriculture. Staples are also one of the state assets that can optimize state revenues through the success of a high production process so that staple commodities can be exported to other countries to increase economic competitiveness more optimally. One of the ways to stabilize the economy of a region is by determining proper retail prices for staple commodity commodities. This research examines the feasibility level analysis case for fixing the retail price of basic commodities in the city of Pematangsiantar using the methodK-Means Clusteringas a case solution. The source of the data in this study was obtained from official documents from the Central Bureau of Statistics in the city of Pematangsiantar with processing data on retail prices of basic commodities in 2018-2021 with data on 8 (eight) commodities. Data analysis in this study used 2 (two) cluster levels, namely the high cluster (C1) and the low cluster (C2). Based on the research results, it was found that 1 (one) commodity was included at a high level (cluster 1), namely salted fish. While t (seven) other commodities such as rice, cooking oil, sugar, salt, washing soap, wheat flour and cement are included in the low level cluster (C2). It is hoped that the research results can be input.
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Copyright (c) 2023 Akbar Fahri Hambali, M. Safiib
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.