ANALISIS POLA PRESTASI AKADEMIK SISWA MENGGUNAKAN ALGORITMA APRIORI DI SMK SWASTA DEWI SARTIKA NEGERI LAMA

PUTRI KHAIRINNISA, NPM 2209100103 (2026) ANALISIS POLA PRESTASI AKADEMIK SISWA MENGGUNAKAN ALGORITMA APRIORI DI SMK SWASTA DEWI SARTIKA NEGERI LAMA. Skripsi thesis, Universitas Labuhanbatu.

	Text COVER.pdf Download (832kB)
	Text BAB I.pdf Download (83kB)
	Text BAB II.pdf Download (412kB)
	Text BAB III.pdf Restricted to Registered users only Download (682kB)
	Text BAB IV.pdf Restricted to Registered users only Download (710kB)
	Text BAB V.pdf Download (149kB)
	Text DAFTAR PUSTAKA.pdf Download (157kB)

Abstract

Prestasi akademik siswa merupakan salah satu indikator penting dalam mengevaluasi keberhasilan proses pembelajaran di sekolah. Data akademik yang tersimpan dalam jumlah besar sering kali hanya dimanfaatkan sebagai arsip sehingga informasi yang terkandung di dalamnya belum dimanfaatkan secara optimal. Penelitian ini bertujuan untuk menganalisis pola prestasi akademik siswa menggunakan metode Data Mining Association Rule dengan algoritma Apriori di SMK Swasta Dewi Sartika Negeri lama. Data yang digunakan berjumlah 110 data siswa yang terdiri atas nilai Matematika, Bahasa Indonesia, Bahasa Inggris, Produktif Kejuruan, dan kehadiran siswa. Tahapan penelitian meliputi pengumpulan data, data selection, preprocessing, transformasi data ke dalam bentuk kategorikal, pembentukan frequent itemset, serta pembentukan association rule berdasarkan nilai support, confidence, dan lift. Proses analisis dilakukan secara manual dan menggunakan perangkat lunak Orange Data Mining untuk memvalidasi hasil perhitungan. Hasil penelitian menunjukkan bahwa algoritma Apriori mampu menemukan pola hubungan antar atribut akademik siswa dengan baik. Beberapa aturan apriori yang dihasilkan memiliki nilai confidence mencapai 100% dan lift ratio lebih besar dari 1, yang menunjukkan adanya hubungan yang kuat antar atribut, khususnya antara nilai mata pelajaran dan kehadiran terhadap nilai Produktif Kejuruan. Pola yang dihasilkan dapat dimanfaatkan oleh pihak sekolah sebagai bahan evaluasi dalam memantau prestasi akademik siswa serta sebagai dasar pengambilan keputusan untuk meningkatkan kualitas pembelajaran. Kata kunci: Data Mining, Algoritma Apriori, Prestasi Akademik ============================================================================================= Academic achievement is one of the key indicators used to evaluate the effectiveness of the teaching and learning process in schools. However, large volumes of academic data are often stored merely as administrative records, leaving the valuable information embedded within them underutilized. This study aims to analyze patterns of students' academic achievement using the Association Rule data mining technique with the Apriori algorithm at SMK Swasta Dewi Sartika Negeri lama. The dataset consisted of 110 student records, including Mathematics, Indonesian Language, English, Vocational Subject scores, and attendance records. The research procedure involved data collection, data selection, preprocessing, data transformation into categorical transactions, frequent itemset generation, and association rule mining based on support, confidence, and lift values. The analysis was carried out through both manual calculations and the Orange Data Mining application to validate the generated association rules. The findings indicate that the Apriori algorithm effectively identifies meaningful relationships among students' academic attributes. Several association rules achieved a confidence value of 100% and a lift ratio greater than 1, indicating strong associations among academic variables, particularly between subject performance, attendance, and vocational subject achievement. The resulting association patterns can serve as valuable information for the school in evaluating students' academic performance and supporting data-driven decision-making to improve the quality of teaching and learning. Keywords: Data Mining, Apriori Algorithm, Academic Achievement

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	Data Mining, Algoritma Apriori, Prestasi Akademik=============Data Mining, Apriori Algorithm, Academic Achievement
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Divisions:	Fakultas Sains Dan Teknologi > Sistem Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	27 Aug 2026 03:09
Last Modified:	27 Aug 2026 03:09
URI:	http://repository.ulb.ac.id/id/eprint/2679

Actions (login required)

View Item