Implementation of C4.5 and K-Nearest Neighbor to Predict Palm Oil Fruit Production on Local Plantations
DOI:
10.29303/jppipa.v9i9.4498Published:
2023-09-25Issue:
Vol. 9 No. 9 (2023): SeptemberKeywords:
C4.5, K-Nearest Neighbor, Preprocessing, RapidMinerResearch Articles
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Abstract
The agricultural sector, especially oil palm plantations, has an important role in the Indonesian economy. Oil palm farming has increased the welfare of farmers and provided employment. In this study, researchers used the C4.5 and K-Nearest Neighbor algorithms in the RapidMiner application to analyze oil palm fruit production data after going through the data preprocessing process. The C4.5 algorithm produces a decision tree with an accuracy of 94.12%, while the KNN algorithm achieves an accuracy of 82.53%. Based on these results, it can be concluded that the C4.5 algorithm has a higher accuracy in classifying oil palm fruit production based on existing attributes.
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Author Biographies
Rahmahwati, Faculty of Computer Science, Darwan Ali University, Sampit, Indonesia.
Elika Thea Kirana, Faculty of Computer Science, Darwan Ali University, Sampit, Indonesia
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Copyright (c) 2023 Rahmahwati, Elika Thea Kirana
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