Data Mining Pengembangan Klasifikasi Penentuan Teknik Budidaya Tanaman Padi Menggunakan Algoritma C4.5

BATA, Meysiliani Sidi (2020) Data Mining Pengembangan Klasifikasi Penentuan Teknik Budidaya Tanaman Padi Menggunakan Algoritma C4.5. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

As one of the provinces with the lowest Food Security Index (FSI) in Eastern Indonesia, Central Bureau of Statistics noted that the productivity of rice farmers in the province of East Nusa Tenggara in 2018 was only 3.98 tons of Milled Dried Unhulled (MDU) per hectare or 74% below the national productivity target is 5.34 tons / hectare. One of the causes of the inadequate production and productivity of rice-plant is because farmers still dominate using conventional systems. Limited knowledge of planting systems and crop patterns when choosing rice cultivation techniques makes some farmers confused about what techniques are suitable for their needs. The purpose of this research is to analyze the application of data mining in classifying cultivation techniques by utilizing existing criteria. The research data source came from East Nusa Tenggara Province Agricultural Technology Research Center (ATRC). The research data used is the variety description data released by the SRI and Jajar Legowo cultivation technique since the initial application to the land. This classification system uses the Decision Tree C4.5 Algorithm. From the test results using Rapidminer, as many as 370 data on rice-plant varieties with 259 training data and 111 testing data obtained an accuracy value of 95.50%.

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