Published: 2026-10-01

Prediksi Ketuntasan Siswa Berbasis Data Multidimensi Menggunakan Metode K-Nearest Neighbor (KNN) di SMK NU Hasyim Asy'ari 2 Kudus

DOI: 10.35870/jtik.v10i4.7015

Muhammad Syafi’ul Huda, Harminto Mulyo, Gentur Wahyu Nyipto Wibowo
  • Muhammad Syafi’ul Huda: Universitas Islam Nahdlatul Ulama Jepara
  • Harminto Mulyo: Universitas Islam Nahdlatul Ulama Jepara
  • Gentur Wahyu Nyipto Wibowo: Universitas Islam Nahdlatul Ulama Jepara
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Abstract

This research implements the K-Nearest Neighbors (KNN) algorithm to predict student learning mastery at SMK NU Hasyim Asy’ari 2 Kudus for the 2025/2026 academic year using multidimensional data. Following data preprocessing and labeling via median thresholding, the results indicate that the best performance is achieved at $K$ values of 7, 9, and 10, with an accuracy of 58.62%. While the precision of 0.69 demonstrates reasonable accuracy in predicting students who achieve mastery, the recall of 0.50 highlights the model's limitations in identifying all students who actually pass. These results are primarily influenced by the limited sample size and imbalanced class distribution. Overall, KNN serves as an effective initial approach for objective academic prediction, though further optimization through parameter tuning or feature engineering is required to enhance future accuracy.

Keywords

Data Minings; K-Nearest Neighbors (KNN); Student Learning Mastery; Classification; Prediction

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How to Cite

Huda, M. S., Mulyo, H., & Wibowo, G. W. N. (2026). Prediksi Ketuntasan Siswa Berbasis Data Multidimensi Menggunakan Metode K-Nearest Neighbor (KNN) di SMK NU Hasyim Asy’ari 2 Kudus. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 10(4), 1535-1542. https://doi.org/10.35870/jtik.v10i4.7015
Article Information

This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.

  • Issue: Vol. 10 No. 4 (2026)

  • Section: Computer & Communication Science

  • Published: 2026-10-01

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Author Biographies
Muhammad Syafi’ul Huda, Universitas Islam Nahdlatul Ulama Jepara
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Sains Dan Teknologi, Universitas Islam Nahdlatul Ulama Jepara, Kabupaten Jepara, Provinsi Jawa Tengah, Indonesia.

Harminto Mulyo, Universitas Islam Nahdlatul Ulama Jepara
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Sains Dan Teknologi, Universitas Islam Nahdlatul Ulama Jepara, Kabupaten Jepara, Provinsi Jawa Tengah, Indonesia.

Gentur Wahyu Nyipto Wibowo, Universitas Islam Nahdlatul Ulama Jepara
Google Scholar ResearchGate ORCID

Program Studi Teknik Informatika, Fakultas Sains Dan Teknologi, Universitas Islam Nahdlatul Ulama Jepara, Kabupaten Jepara, Provinsi Jawa Tengah, Indonesia.

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