Decision Support System Design and Development for Determine Graduate Phase of College Students with Naïve Bayes Algorithm Web-Based in Indonesia Institute of Business and Technology

Autor: I Kadek Dwi Gandika Supartha, I Gede Andika, Nia Maharani, Ayu Manik Dirgayusari, Andres Adyana
Rok vydání: 2023
Předmět:
Zdroj: BERKALA SAINSTEK. 11:12
ISSN: 2339-0069
DOI: 10.19184/bst.v11i1.33385
Popis: In the course of the lecture period, each student is different, various factors can affect the mental and academic achievement of students which have an impact on their graduation period. This things also impact on the campus of the Indonesian Institute of Business and Technology, until now there is no system that can determine the graduation period of students at the campus, therefore it is necessary to build a decision support system to determine the graduation period of students, especially students in the Informatics Engineering Study Program and Program Study of Computer Systems at the Indonesian Institute of Business and Technology (INSTIKI) using the Naïve Bayes algorithm that utilizes parameters, namely student academic data consisting of work status, Semester Achievement Index (IPS) scores semesters one untill four, and Grade Point Average (IPK). The system designed by using the GaussianNB library in python and website based. From the results of this study, the accuracy of the model made on the system produces an accuracy value of 87.5% with a dataset rule of 800 data and the data is divided and used as test data by 20%, while the accuracy value of classifying 250 test data on the system is 80.8%.
Databáze: OpenAIRE