PENERAPAN ALGORITMA NAIVE BAYES DALAM MENENTUKAN POTENSI MENGUNTUNGKAN PADA MENU MAKANAN (STUDI KASUS: KEDAI SEKUL, KOPI MANING)
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
SALSABILA, NADIA
Aziza, Rosida Nur
Munir, Buyung Sofianto
Aziza, Rosida Nur
Munir, Buyung Sofianto
Subject
Teknik Informatika
Datestamp
2022-09-20 03:06:39
Abstract :
Technological developments are growing very rapidly in various fields of life, including in the fields of business and economics. Utilization of technology in the business field, namely being able to process data such as classifying purchase transaction data. This study will discuss the application of the Naïve Bayes algorithm on the menus available at Kedai SEKUL, as well as implementing it into a web-based application model. The data used is purchase transaction data from March to May as data training, and September to October as data testing. Testing using the confusion matrix method is carried out in two kinds of data, namely for all data testing and data testing per menu. Research using a quantitative approach and collecting data through indirect interviews, observation, and literature studies resulted in all data testing having 8 menus which were considered profitable, while data testing per menu consisted of four menus. This study has the same level of accuracy, memory, and precision, namely the proportion of 100%.
Technological developments are growing very rapidly in various fields of life, including in the fields of business and economics. Utilization of technology in the business field, namely being able to process data such as classifying purchase transaction data. This study will discuss the application of the Naïve Bayes algorithm on the menus available at Kedai SEKUL, as well as implementing it into a web-based application model. The data used is purchase transaction data from March to May as data training, and September to October as data testing. Testing using the confusion matrix method is carried out in two kinds of data, namely for all data testing and data testing per menu. Research using a quantitative approach and collecting data through indirect interviews, observation, and literature studies resulted in all data testing having 8 menus which were considered profitable, while data testing per menu consisted of four menus. This study has the same level of accuracy, memory, and precision, namely the proportion of 100%.
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