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

  • Muhammad Syafi’ul Huda1*
  • Harminto Mulyo2
  • Gentur Wahyu Nyipto Wibowo3
1,2,3 Universitas Islam Nahdlatul Ulama Jepara image/svg+xml
* Corresponding Author: Muhammad Syafi’ul Huda
Cover JTIK VOLUME 10 NO 4 OKTOBER 2026

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

How to Cite

Citation Format
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

References

14 References
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Author Biographies

Muhammad Syafi’ul Huda, Universitas Islam Nahdlatul Ulama Jepara

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

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

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

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Copyright (c) 2026 Muhammad Syafi’ul Huda, Harminto Mulyo, Gentur Wahyu Nyipto Wibowo

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This work is licensed under a Creative Commons Attribution 4.0 International License.

This is an open-access journal distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, reproduction, and adaptation in any medium (even commercially), provided appropriate credit is given to the original author(s), a link to the license is provided, and any changes made are indicated. Authors retain copyright without restrictions and grant the journal the right of first publication as well as non-exclusive publishing rights for archiving, indexing, and scholarly dissemination.

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