Open AccessNaive Bayes Algorithm Analysis to Determine the Percentage Level of visitors the Most Dominant Zoo Visit by Age Category
Author(s) -
Iin Parlina,
M. Yusuf Arnol,
Nur Ahlina Febriati,
Rafiqa Dewi,
Anjar Wanto,
Muhammad Ridwan Lubis,
_ Susiani
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1255/1/012031
Subject(s) - naive bayes classifier , visitor pattern , age groups , bayes' theorem , classifier (uml) , artificial intelligence , categorization , computer science , statistical classification , machine learning , mathematics , psychology , demography , bayesian probability , support vector machine , sociology , programming language
Classification is a method of data analysis that is used to create models that describe data classes that are considered important. For the classification of the classification process, the data used is THPS Visitor data which consists of 4 classes including Education, Gender, Age and Visit. The classification used as a comparison of results is the Naive Bayes Classifier. By classifying the number of visitors who are most dominant visiting by age category consisting of adults, adolescents and children. This study aims to classify the highest number of values for visitors by age category. This study was reviewed using the Naive Bayes algorithm. The results of this study indicate that the visitor data that is the most dominant visiting by age category is children who have 77% accuracy is the age of children. This accuracy value is the age that most often visits THPS.