Self, Eliyanda (2021) PENGELOMPOKAN SISWA PENYANDANG DISABILITAS BERDASARKAN TINGKAT TUNAGRAHITA MENGGUNAKAN METODE NAÏVE BAYES. S1 thesis, Universitas Malikussaleh.

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Abstract

PENGELOMPOKAN SISWA PENYANDANG DISABILITAS BERDASARKAN TINGKAT TUNAGRAHITA MENGGUNAKAN METODE NAÏVE BAYES ABSTRACT Data mining is a science that is used to analyze data, categorize, classify and conclude it, in some of these processes there are techniques for grouping data in data mining, which is classification. This study itself aims to build a system for classifying data on students with disabilities based on the level of mental retardation to determine which class is occupied so that the school can prepare for the needs of these students. Then to find out the application of the Naïve Bayes algorithm in grouping mild, moderate and severe mental retardation students. This research was conducted at the Special School (SLB) Lhokseumawe City. The criteria used in this study are NA (Academic Value), NK (Skill Value), IQ, Physical, Attitude, Group. Data collection techniques in this study used interview techniques (Interview), field observations (Observation), and literature studies. The data analysis technique is carried out by following the KDD (Knowledge Discovery in Database) stages to group students with disabilities based on the level of mental retardation. The amount of data amounted to 63 groups of mentally retarded students consisting of 10 groups of students with mild mental retardation, 35 groups of students with moderate mental retardation and 18 groups of students with severe mental retardation. The results of testing accuracy from all 63 student data using the Naïve Bayes algorithm resulted in an accuracy rate of 57.39% and an error of 47.61%. Keywords: Data Mining, Naïve Bayes, mental retardation.

Item Type:	Thesis (S1)
Subjects:	T Technology > T Technology (General)
Divisions:	Fakultas Teknik > 55201 - Jurusan Teknik Informatika
Depositing User:	Khairiati Khairiati
Date Deposited:	22 Jan 2025 08:59
Last Modified:	22 Jan 2025 08:59
URI:	https://rama.unimal.ac.id/id/eprint/9366

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