Analisis Algoritma Apriori Untuk Segmentasi Calon Mahasiswa Dalam Mendukung Strategi Promosi Perguruan Tinggi UMNU Kebumen - Miftahul Azhar; Fahmi Fachri (Impression : Jurnal Teknologi dan Informasi, 2026)
Penelitian ini bertujuan menganalisis pola asosiasi calon mahasiswa menggunakan algoritma Apriori untuk mendukung strategi promosi yang lebih efektif di Universitas Ma’arif Nahdlatul Ulama Kebumen. Penelitian menggunakan pendekatan kuantitatif dengan metode data mining terhadap 350 data calon mahasiswa periode 2022–2024. Data yang dianalisis mencakup asal sekolah, jurusan, wilayah asal, program studi pilihan, dan sumber informasi promosi. Proses analisis meliputi pembersihan data, transformasi data, pembentukan data transaksi, dan association rule mining dengan minimum support 20% dan minimum confidence 60%. Hasil penelitian menunjukkan bahwa media sosial merupakan sumber promosi paling efektif (45%). Aturan asosiasi terkuat ditemukan pada siswa SMK jurusan Teknik Komputer dan Jaringan (TKJ) yang memperoleh informasi melalui media sosial dan memilih Program Studi Informatika, dengan confidence 86% dan lift ratio 2,3. Temuan juga menunjukkan bahwa promosi melalui teman dan brosur masih berpengaruh terhadap pilihan program studi. Penelitian ini menghasilkan model segmentasi calon mahasiswa berbasis association rule yang dapat digunakan untuk meningkatkan efektivitas dan ketepatan sasaran strategi promosi perguruan tinggi.   This study aims to analyze prospective student association patterns using the Apriori algorithm to support more effective promotional strategies at Universitas Ma’arif Nahdlatul Ulama Kebumen. A quantitative approach with data mining techniques was employed using 350 prospective student records from the 2022–2024 admission periods. The analyzed data included school origin, academic major, region of origin, chosen study program, and source of promotional information. The analysis process consisted of data cleaning, data transformation, transaction data formation, and association rule mining with a minimum support of 20% and a minimum confidence of 60%. The results indicate that social media is the most effective promotional channel, accounting for 45% of information sources. The strongest association rule was identified among vocational high school students majoring in Computer and Network Engineering (TKJ), who obtained information through social media and selected the Informatics Study Program, with a confidence value of 86% and a lift ratio of 2.3. The findings also show that recommendations from friends and brochures continue to influence study program selection. This study contributes a prospective student segmentation model based on association rules that can support more targeted, efficient, and effective promotional decision-making in higher education institutions.