IMPLEMENTASI TEORI NAIVE BAYES DALAM KLASIFIKASI CALON MAHASISWA BARU STMIK KHARISMA MAKASSAR

Autor:	Irayori Loelianto, Moh. Sofyan S. Thayf, Husni Angriani
Rok vydání:	2020
Předmět:	Naive Bayes classifier Training set Design stage Computer science business.industry Artificial intelligence Python (programming language) Machine learning computer.software_genre business computer Test data computer.programming_language
Zdroj:	SINTECH (Science and Information Technology) Journal. 3:110-117
ISSN:	2598-9642 2598-7305
DOI:	10.31598/sintechjournal.v3i2.651
Popis:	STMIK KHARISMA Makassar has graduated thousands of alumni since it was founded. However, the number of students registering is uncertain every year, although from 2016 to 2019 there has been an increase in the number of registrations. The problem is the percentage of the number of prospective students registering has actually decreased significantly. The purpose of this research is to implement the Naive Bayes theory in classification of STMIK KHARISMA Makassar prospective students. This research basically uses the Naive Bayes theory as a classifier, and is made using the Python programming language. At the classifier design stage, there were a total of 499 data collected from 2016 to 2019. The data was divided by a ratio of 80:20 for training data and test data. The result from the research indicate the level of accuracy of the classifier reaches 73%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d8c6c61767b30d5414a8f50c7c50a8a9 https://doi.org/10.31598/sintechjournal.v3i2.651 Zobrazit plný text záznamu