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Journal : Journal of Artificial Intelligence and Engineering Applications (JAIEA)

Categorying Sugarcane Production Based On Factors Affecting Productivity With The K-Nearest Neighbor Algorithm Pratiwi, Anggi; Pardede, A M H; Prahmana, I Gusti
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.295

Abstract

Sugarcane (Saccharum Officanarum is an annual plantation crop, which has its own characteristics, because the stem contains sugar. To classify the results of sugarcane production, currently still using the manual method by only looking at the current conditions of sugarcane production. This is less efficient because there is no calculation process in grouping sugarcane. So that mistakes can occur in grouping sugarcane production to get good results or not in the assessment of sugarcane grouping at PTPN II Kwala Madu. For this reason, the author will create an alternative application system that can group sugarcane production with the K-Nearest Neighbor algorithm to find out the best type of sugarcane production based on the factors. The application made by the author uses the PHP programming language and uses the MySQL database as data storage. The system is made as easy as possible to make it easier for users to use and understand later.