Determining The Location Of RMU, Using K-Means Clustering, Evaluate The Location Of Existing RMU, Using R-Programming

Authors

DOI:

https://doi.org/10.31289/jite.v6i1.6126

Keywords:

K-Means, R Language, RMU,

Abstract

Rice milling into rice, (Rice Milling Unit, RMU) is needed to process the harvested grain into rice. In determining the location, the consideration of road access to consumers is still used and it is often far from the rice fields, the source of the grain material to be milled. This paper aims to analyze the ideal location with the consideration of being in a rice field cluster and the area of the rice field, so that it can accommodate crop yields around the cluster, namely the location of the spatial coordinates and the area (hectare). Primary data was obtained by the author from the Department of Agriculture of Malang Regency and the data was processed as input for analysis. Analysis of determining the location of the center of the rice field cluster using the Weighted K-Means Clustering method by comparing several alternative cluster points (K) and the area of rice fields, testing the variation of K is, K = 5, 6, 7 and 8. Optimal test results at K = 7. Calculations using the R language. The test results obtained that the cluster center suggested 7 clusters to accommodate the rice harvest in 7 regions, namely in the west, north (1), middle (2), south (3), east (1) and west (1 ) . Evaluation of the location of the existing RMU, there are 5 locations, so that for the next planning, you can add 2 more clusters to build the RMU and accommodate a more even rice harvest.

Author Biography

Moehammad Masri abdoel Wahid, STIE Indonesia Malang

Sebagai lektor di Jurusan Manajemen, STIE, mengampu kuliah Aplikasi Komputer, SIM dan matematika ekbis. Alumni S1 dari ITS, Ir. 1985, S2 dari UNSW Sydney, M.ENg.Sc, 1997 dan S2 Teknik Informatika dari STTS Surabaya, M.Kom 2006. Hobby pemrograman Data Science menggunakan Python, R, Matlab dan Octave.

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Published

2022-07-21