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All Journal Jurnal Dedikasi Journal of Information Technology and Computer Science Jurnal Sains Dan Teknologi (SAINTEKBU) SMARTICS Journal Jurnal Bangun Abdimas Jurnal Pengabdian Harapan Bangsa Delta-Phi Jurnal Pendidikan Matematika Jurnal Inovasi dan Pengembangan Hasil Pengabdian Masyarakat Assyfa Journal of Islamic Studies Akiratech E-Amal: Jurnal Pengabdian Kepada Masyarakat International Journal of Technology and Education Research International Journal of Economics, Business and Innovation Research Ashlach : Journal of Islamic Education
Sapto Hadi Riono
Universitas PGRI Wiranegara Pasuruan, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : SMARTICS Journal

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Analisis Clustering Produktivitas Padi Daerah-Daerah Di Tiga Provinsi Besar Pulau Jawa Menggunakan Algoritma K-Means Berbasis Python Riono, Sapto Hadi; Rizdania; Henny May Indahsari
SMARTICS Journal Vol 10 No 2 (2024): SMARTICS Journal (Oktober 2024)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/smartics.v10i2.11826

Abstract

Rice plays a crucial role for the Indonesian people as their primary source of energy and carbohydrates. A decline in rice production can impact food availability. Rice, as the main food crop, and its processed products, are crucial in fulfilling more than 70% of the daily food needs for the Indonesian population. One of the methods that can be used to conduct Clustering analysis on rice productivity and rice in three major provinces of Java Island is by using K-Means algorithm. While the tools used in this research is Python. The evaluation result of Sum of Squared Error (SSE) is 3.4452012710511966, Davies-Bouldin Index (DBI) 0.5811451032787581, Silhouette Coefficient Index (SCI) 0.5581692872789441. The use of the K-Means method with Python successfully grouped rice productivity data into three clusters namely high, medium and low. By using fit_predict from the sklearn library, the rice productivity data in the regions of the three major provinces in Java Island were successfully grouped well and gained deep insights and were influenced by various factors such as cultivation techniques, soil quality, and climatic conditions.
Co-Authors Abdul Hamid Abdul Karim Akhmad Kavin Abda Al Farisi, Achmad Shofiyuddin Andianto, Mascun Anindita Verliana Ridho'i Azizah , Nur Fariana, Yudha Fatikh Inayahtur Rahma Fikri, Miftahul Firmansyah, Muhammad Nafi Hadiatullah, Dimas Rega Hadiatulloh, Dimas Rega Henny May Indahsari Hussain, Nazar Latipun M. Bayu Firmansyah, M. Bayu Maesaroh Lubis Muhammad Ainun Naim Mujiwati, Yuniar Nina Aulia, Sabrina Ningtyas, Sherly Zakia Nundiah Zuhrohfi Immaroh Nunuk Indarti Puji Utami Rakhmawati Rani Darmayanti Rizdania, Rizdania Shinta Dwi Ranti Silva, Samuel Da