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All Journal KARSA: Jurnal Sosial dan Budaya Keislaman (Journal of Social and Islamic Culture) Management Analysis Journal Natural: Jurnal Ilmiah Pendidikan IPA Ihtifaz: Journal of Islamic Economics, Finance, and Banking Jurnal E-Bis: Ekonomi Bisnis Well Being MASAGI ( Jurnal Pendidikan Agama Islam ) AJER : Advanced Journal of Education and Religion Proceedings Series of Educational Studies Almantiq
Umi Azizah, Umi
UIN Sunan Kalijaga of Yogyakarta
Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences Other

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Journal : Almantiq

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Pengelompokan Siswa Smk Diponegoro Berdasarkan Kedisiplinan Pembayaran Spp Menggunakan Algoritma K-Nearest Neighbors Entropy Azizah, Umi; Hastuti, Dwi Issadari; sahri, sahri
Multidisciplinary Applications of Quantum Information Science (Al-Mantiq) Vol. 5 No. 2 (2025): Multidisciplinary Applications of Quantum Information Science (Al-Mantiq)
Publisher : Al-Mantiq

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/almantiq.v5i2.5313

Abstract

Discipline in the payment of tuition fees is an important aspect of school financial management, especially in private educational institutions. This research aims to optimize student grouping based on tuition payment discipline by applying the K-Nearest Neighbors (K-NN) algorithm integrated with the Entropy method as a feature weighting technique. The data used is historical data of tuition payments of students of SMK Diponegoro with attributes such as gender, number of siblings, profession and salary of parents, and status of aid recipients. After going through the preprocessing and normalization stages, the K-NN algorithm is applied with a value of K = 10 and distance calculation using Euclidean Distance. Test results with confusion matrix show an accuracy of 75.86%, recall 80%, and precision 61.54%. This proves that the K-NN algorithm optimized with the Entropy method is quite effective in classifying students into the “Right” or “Late” category in paying tuition fees.
Co-Authors Akhmad Arif Musadad Anam, Muhammad Syaiful Anshori, Faisal Basri, Junaidin Djono Djono Dwi Issadari Hastuti Eko Ariwidodo Fathurrahman, Ayif Fitriyah, Erna Tsalasatul Hartanto, Eko Budi Ida Maftukhah Kusyani, Asri LAILIYAH, IFFATUL Maharani Ekowati, Vivin Maulidiyah, Latifatul Mazza, M. Zahid Mufidah, Zuni Walidatul Mutoharoh, Alfoyatin Rachmad, Willy Sabita, Fidela Yasmine Sahri Sahri Salamudin, Ceceng Suwarni Suwarni