ANALISIS KLASIFIKASI ALGORITMA C.45 DALAM MEMPREDIKSI TINGKAT PENJUALAN PERLENGKAPAN IBADAH
DOI:
https://doi.org/10.33884/comasiejournal.v11i1.8987Kata Kunci:
Datamining, Prediction, C4.5 Algorithm, Weka, SalesAbstrak
This research was conducted at a shop that sells goods or equipment for Buddhist worship called the Sinar Mas Indah shop. The Sinar Mas Indah shop operates every day except major holidays such as Chinese New Year. So far, the Sinar Mas Indah store has never used sales transaction data for analysis for the benefit of future business progress, sales transaction data is only stored in archive form, if it is old and feels no longer needed, it will simply be thrown away. , if used to predict future sales then decisions to increase sales in the future can be easily achieved. This research utilized datamining techniques with the C4.5 algorithm by testing the results using Weka software, from the 5 variables tested, category, brand, quantity, quality and price with a total of 160 test data. After calculating the entropy and gain values, the highest gain value was obtained. making consideration of consumer purchasing factors, namely Price, Quality, Quantity and category, into the main factors in decision making and there are results for Correctly Classified Instances 109 Data with a percentage value of 68.125% then for Incorrectly Classified Instances 51 data with a percentage value of 31.875%.
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