2019•AIP conference proceedingsRequires access

Classification of teak wood production in Central Java using the C5.0 algorithm

Yuliana Susanti, N.A. Respatiwulan, Sri Sulistijowati Handajani, Hasih Pratiwi, İsnandar Slamet, Hartatik Hartatik, Firstiana Istiqomah

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Abstract

Central Java has the largest teak land area in Java Island. It is about two-thirds of teak land area on Java Island is located in Central Java. The purpose of this study is to determine the classification of factors that influence the production of teak trees in Central Java with the Commercial Version 5.0 (C5.0) algorithm. This algorithm is a refinement of the ID3 and C4.5 algorithms. The C5.0 algorithm works by separating samples based on attributes that have the highest information gain. The results of the study show that there are three classification rules produced with an 81.8% accuracy rate.

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What this paper is about

Central Java has the largest teak land area in Java Island. It is about two-thirds of teak land area on Java Island is located in Central Java. The purpose of this study is to determine the classification of factors that influence the production of teak trees in Central Java with the Commercial Version 5.0 (C5.0) algorithm. This algorithm is a refinement of the ID3 and C4.5 algorithms. The C5.0 algorithm works by separating samples based on attributes that have the highest information gain. The results of the study show that there are three classification rules produced with an 81.8% accuracy rate.

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Available abstract

Central Java has the largest teak land area in Java Island. It is about two-thirds of teak land area on Java Island is located in Central Java. The purpose of this study is to determine the classification of factors that influence the production of teak trees in Central Java with the Commercial Version 5.0 (C5.0) algorithm. This algorithm is a refinement of the ID3 and C4.5 algorithms. The C5.0 algorithm works by separating samples based on attributes that have the highest information gain. The results of the study show that there are three classification rules produced with an 81.8% accuracy rate.

Key concepts: Java, Computer science, Algorithm, Production (economics), Operating system, Economics, Macroeconomics

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