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Adiddo Restiady
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Computer Science & IT

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Naive Bayes Algorithm Classification for Predicting Graduation Rate Purnama, Pradani Ayu Widya; Pohan, Nurmaliana; Adiddo Restiady
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3866

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).
Predicting New Student Admissions with the SVM Regression Model in Data Mining Purnama, Pradani Ayu Widya; Pohan, Nurmaliana; Adiddo Restiady
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.5035

Abstract

Prediction is an action to predict future conditions based on past data. One method for making predictions that can be used is the linear regression method. The linear regression method itself consists of two types, simple linear regression and multiple linear regression. One method that uses past data to make predictions is the linear regression method. Regression is a statistical calculation to test how closely the relationship between variables. The simplest and most frequently used regression analysis is simple linear regression. In regression analysis, there is one dependent variable usually written with the symbol Y and one or more independent variables usually written with the symbol X. The relationship between the two variables has a linear nature according to its name. The SVM method was chosen for data mining analysis in this study. There are two parameters used: Exam Scores and Admission Status. This research uses recapitulation data on the acceptance of new students at Play Group & Kindergarten Rahmah Abadi with a total of 50 people. Based on the analysis results, an accuracy rate of 91%.
Co-Authors Pohan, Nurmaliana Purnama, Pradani Ayu Widya