Prediksi Tingkat Persaingan Siswa Dalam Seleksi Nasional Masuk Perguruan Tinggi Negeri Menggunakan Data Mining pada SMAN 6 Surabaya. (Prediction Of Student Competition Level In National Selection To Enter State University Using Data Mining At SMAN 6 Surabaya).

Giovanni, Rafif (2023) Prediksi Tingkat Persaingan Siswa Dalam Seleksi Nasional Masuk Perguruan Tinggi Negeri Menggunakan Data Mining pada SMAN 6 Surabaya. (Prediction Of Student Competition Level In National Selection To Enter State University Using Data Mining At SMAN 6 Surabaya). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

This research aims to develop a method for predicting the level of student competition in the national selection to enter state universities using data mining techniques at SMAN 6 Surabaya. National selection to enter state universities is a very competitive process and is important for students to get the opportunity to enter the desired university. In this research, we use data mining techniques to analyze data about students who will take part in the national selection at SMAN 6 Surabaya. The data used includes exam results, report cards, and other factors that can influence the level of student competition. The main goal of this data analysis is to identify patterns or trends that can be used to predict the level of student competition in the future. It is hoped that the results of this research can help students, teachers and related parties in understanding and anticipating the level of competition in the national selection to enter state universities. From this research, the results of testing with Data Mining using the Naïve Bayes algorithm obtained results for students who got SNMPTN at 55.5% and those who did not got 44.5% with an accuracy of 87%, Precision 89%, Recall 86.71% and F1 -Score 87.84%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Prediction, SMAN 6 Surabaya, SNMPTN, Data Mining
Subjects:	Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science Z Bibliography. Library Science. Information Resources > ZA Information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Divisions:	Fakultas Teknik > Program Studi Teknik Informatika
Depositing User:	1461900239 Rafif Giovanni
Date Deposited:	10 Jul 2024 01:48
Last Modified:	10 Jul 2024 01:48
URI:	http://repository.untag-sby.ac.id/id/eprint/29463

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