PREDIKSI CLUSTERING, CALCULATION DAN CLASSIFICATION FRUIT AND VEGETABLE CONSUMPTION
DOI:
https://doi.org/10.31958/js.v7i2.135Abstract
Prediction model using combination of K-Means Clustering, Excel Function, and Naïve Bayes Classifier. Process is dataset, clustering, calculation, classification and prediction. Dataset source on BPS 2013 about consumption of fruit and vegetable. Clustering using K-Means Clustering. Clustering by output Cluster 1, Cluster 2, and Cluster 3. Calculation using Excel. Calculation by output Priority Yes and Priority No. Classification using Naïve Bayes Classifier. Classification by output Class Good and Class Bad. All data processing for clustering, calculation, and classification using Excel. Experimental results on BPS 2013 Dataset show percentage of fruit consumption 42,42% Class Good (class above average) and percentage fruit consumption of fruit consumption 57,58% Class Bad (class below average). Percentage of vegetable consumption 45,45% Clas Good (class above average) and percentage of vegetable consumption 54,55% Class Bad (class below average). Clustering, calculation and classification can be combined becamed prediction model.
Key words: clustering, calculation, classification, fruit and vegetable consumptionReferences
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