Analisis Data mining dengan Metode C.45 pada Klasifikasi Kenaikan Rata-Rata Volume Perikanan Tangkap - Muhammad Ridho Matondang; Muhammad Ridwan Lubis; Heru Satria Tambunan (LPPM STIKOM Tunas Bangsa, 2021)
Increasing the amount of demand for natural resource needs is increasing. One of them is natural resources in the sea and coast. The current condition of capture fisheries in Indonesia is not yet optimal. This is indicated by the increase in the volume of capture fisheries production which is very slow. The purpose of this study is to make data classification for the prediction of the average volume increase in capture fisheries with data mining techniques. Data mining techniques are applied to determine the data patterns of the capture fisheries dataset, so the results of the classification can be applied to evaluate the factors that affect the volume of capture fisheries. The classification algorithm used is C45. The results of the classification were tested with rapidminer in classifying data. The level of performance is indicated by the accuracy value. The accuracy value is obtained by testing the results of the classification of training data and testing data. Comparison of accuracy values between the algorithms used can be seen the best algorithm in making the classification of capture fisheries data.