Penerapan Naïve Bayes Pada Penentuan Lokasi Waralaba

Evy Priyanti, Nining Suryani, Girman Sihombing

Abstract


Franchising is currently one of the solutions in developing the economy, various sectors already have types of franchises including food and retail. In this study, the researcher applied the naïve Bayes algorithm in determining franchise locations according to several attributes including road conditions, amount of investment, parking area, existing barriers, visibility, traffic patterns, workforce, age, workforce, types of consumers. The probability obtained from the results of the study shows that food franchises are the best result with a probability value of 0.605 and franchises with a high prospect label are at Alfamart with a probability value of 0.368. In the franchise dataset research with the naïve Bayes algorithm, an accuracy value of 88.10% is obtained, thus Naïve Bayes can accurately predict the most profitable franchises

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DOI: https://doi.org/10.31294/evolusi.v11i2.16346

ISSN: 2657-0793 (online). ISSN: 2338-8161 (print)

Published By LPPM Universitas Bina Sarana Informatika

Jl. Kramat Raya No.98, Kwitang, Kec. Senen, Kota Jakarta Pusat, DKI Jakarta 10450
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