JURNAL TEKNOLOGI DAN OPEN SOURCE
Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024

Naive Bayes Algorithm Classification for Predicting Graduation Rate

Pradani Ayu Widya Purnama (Universitas Putra Indonesia YPTK Padang)
Nurmaliana Pohan (Universitas Putra Indonesia YPTK)



Article Info

Publish Date
03 Dec 2024

Abstract

Classification refers to the process of identifying a model or function that clarifies or differentiates concepts or categories of data, with the goal of predicting the class of an object. Naïve Bayes is a machine learning technique that employs probability computations. In this case study, various algorithms are used for modeling classification, and the naïve bayes algorithm is applied to examine the graduation rate. By utilizing this method, accuracy is assessed, which allows for an analysis based on criteria such as School Major, First Choice of College, Second Choice of College, Average Graduation Value, and Graduation Information. The outcome of the computation utilizing the Naïve Bayes Algorithm (Information Systems | Option 1) > (Information Engineering | Option 2) is 53.32% > 0%, which allows us to infer that the First Option of Information Systems and the Second Option of Informatics Engineering yield an Average Score of 75.00, resulting in a Graduation Information status of PASS, thus, Information Pass (Option 1-Information Systems).

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Journal Info

Abbrev

JTOS

Publisher

Subject

Computer Science & IT

Description

Jurnal Teknologi dan Open Source menerbitkan naskah ilmiah. yang berkaitan dengan sistem informasi, teknologi informasi dan aplikasi open source secara berkala (2 kali setahun). Jurnal ini dikelola dan diterbitkan oleh Program Studi Teknik Informatika Fakultas Teknik, Universitas Islam Kuantan ...