Naive Bayes and Simple Additive Weighting (SAW) Method for Whey Protein Product Selection in Fitness

Aditya Maulana Azanzi Girsang; Abdul Halim Hasugian

doi:10.47709/cnahpc.v6i3.4022

Authors

Aditya Maulana Azanzi Girsang Universitas Islam Negeri Sumatera Utara
Abdul Halim Hasugian Universitas Islam Negeri Sumatera Utara

DOI:

10.47709/cnahpc.v6i3.4022

Keywords:

Naive Bayes, SAW, Product, Protein, Fitness

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Abstract

Fitness is one of the most popular muscle-building sports for people of all ages. Meeting the body's protein needs can be through real food (daily food) such as meat, fish, nuts. However, it is not easy to meet daily protein through daily food alone, so with the existence of whey protein products everyone can meet their daily protein needs without having to add more food portions. The number of whey protein products on the market causes confusion among users in choosing the right product for their daily protein needs. The purpose of the research conducted by the author is to classify the types of whey protein products using the Naïve Bayes method and make recommendations for the best whey protein products based on their type using the Simple Additive Weighting (SAW) method. The results showed that in the classification of whey protein product types using the Naïve Bayes method, the Naïve Bayes method can classify well. The accuracy value obtained by the Naïve Bayes method in this study is 66.67%. This value is obtained because there are two products whose classification does not match the predetermined label. Things like this are natural because the probabilities used between products have a range that is not far away. The Simple Additive Weighting method succeeded in ranking the best whey protein products based on the Simple Additive Weighting method where the first rank was occupied by Optimum Nutrition Whey Gold Standard (WGS) with a value of 82.5 and the product with the lowest value was BSN Syntha 6 Ultra Premium Protein Matrix with a value of 22.5.

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