Digitizing Paddy Harvest Productivity Based on K-Means Clustering
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Submitted
20 January 2021
Published
22 April 2021
Keywords:
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Clusterin, K-Means, Paddy, Cluster Clustering, K-Means, Padi, Cluster
Abstract
Paddy as an ingredient of staple food by people in Indonesia includes in East Java Province. Therefore attention to the production of paddy in East Java is necessary, and this attention will give a piece of knowledge about which region produces paddy optimally or less optimal. This study aim is to do a clustering about paddy production in each region in East Java. K-Means algorithm uses to do clustering. The result is 3 clusters obtained, high, medium, and less productivity cluster. There are six regions in high productivity cluster, 20 regions in medium productivity cluster, and 12 regions in less productivity cluster.
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Liyantono, Y. Almadani, Y. Adillah, M. Maulana Yusuf, M. N. Reza Mahbub, and A. Fatikhunnada, “Analysis of Paddy Productivity Using NDVI and K-means Clustering in Cibarusah Jaya, Bekasi Regency,†IOP Conf. Ser. Mater. Sci. Eng., vol. 557, no. 1, 2019, doi: 10.1088/1757-899X/557/1/012085.
Winarni, “Penerapan Metode Clustering Fuzzy C-Means Menggunakan Matlab Untuk Memetakan Potensi Tanaman Padi Di Kabupaten Bekasi,†J. Sist. Inf. Manaj. Basis Data, vol. 01, no. 02, pp. 116–127, 2018.
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H. Yuwafi, F. Marisa, and I. D. Wijaya, “Implementasi Data Mining Untuk Menentukan Santri Berprestasi Di Pp . Manaarulhuda Dengan Metode,†J. SPIRIT, vol. 11, no. 1, pp. 22–29, 2019.
A. Aquino, B. Millan, M. P. Diago, and J. Tardaguila, “Automated early yield prediction in vineyards from on-the-go image acquisition,†Comput. Electron. Agric., vol. 144, no. March 2017, pp. 26–36, 2018, doi: 10.1016/j.compag.2017.11.026.
N. P. Dharshinni, F. Azmi, I. Fawwaz, A. M. Husein, and S. D. Siregar, “Analysis of Accuracy K-Means and Apriori Algorithms for Patient Data Clusters,†J. Phys. Conf. Ser., vol. 1230, no. 1, 2019, doi: 10.1088/1742-6596/1230/1/012020.
A. Jamal, A. Handayani, A. A. Septiandri, E. Ripmiatin, and Y. Effendi, “Dimensionality Reduction using PCA and K-Means Clustering for Breast Cancer Prediction,†Lontar Komput. J. Ilm. Teknol. Inf., vol. 9, no. 3, p. 192, 2018, doi: 10.24843/lkjiti.2018.v09.i03.p08.
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Authors
[1]
F. Marisa, A. Zahma, A. Muit Bau, E. Noviansa, A. Semri Neno, and A. Anastasia, “Digitizing Paddy Harvest Productivity Based on K-Means Clustering ”, SMARTICS, vol. 7, no. 1, pp. 21–26, Apr. 2021.
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