Prediction of Academic Achievement of Vocational School Students Based on Tiktok Usage Patterns and Cognitive Styles: Multiple Linear Regression Model (Case Study: SMKS YPIS MAJU)

Khairi Syalwana Amin

doi:10.59934/jaiea.v5i1.1533

Authors

Khairi Syalwana Amin STMIK Kaputama

DOI:

https://doi.org/10.59934/jaiea.v5i1.1533

Keywords:

Academic Achievement, Cognitive Style, Multiple Linear Regression, Prediction, Tiktok

Abstract

This study aimed to predict vocational high school students’ academic achievement by analyzing the influence of TikTok usage patterns and cognitive styles using a multiple linear regression model. The research was conducted at SMKS YPIS Maju Binjai with a sample of 100 students selected through purposive sampling. Data were obtained through questionnaires on TikTok usage patterns and cognitive styles, as well as students’ academic records. TikTok usage (X1) was measured by frequency, duration, and its impact on study habits, while cognitive style (X2) was measured based on visual, verbal, and mixed learning preferences. Academic achievement (Y) was represented by students’ average report card scores. The regression analysis produced the equation Ŷ = 85.869 +(- 0.3495X1) + (0.1993X2). The results showed that TikTok usage had a significant negative effect on academic achievement, whereas cognitive style had a significant positive effect. The model demonstrated good predictive accuracy with R² = 0.392, MAE = 1.77, MSE = 5.26, RMSE = 2.29, and MAPE = 2.16%. This study contributes by integrating social media usage patterns and cognitive factors to predict students’ academic achievement and provides practical insights for educators in guiding students to balance social media use with academic learning.

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References

Q. Aini, “Hubungan Media Sosial TikTok Terhadap Konsentrasi Belajar Siswa,” At-Taujih J. Bimbing. dan Konseling Islam, vol. 2, no. 1, p. 3, 2023.

S. R. Berliana, D. Mulyana, and C. Cahyono, “Pengaruh Penggunaan Media Sosial Tiktok Terhadap Hasil Belajar Peserta Didik Pada Mata Pelajaran Pendidikan Pancasila Dan Kewarganegaraan,” Melior J. Ris. Pendidik. dan Pembelajaran Indones., vol. 3, no. 2, pp. 39–48, 2023, doi: 10.56393/melior.v3i2.1720.

M. G. Nugraha and S. Awalliyah, “Analisis Gaya Kognitif Field Dependent Dan Field Independent Terhadap Penguasaan Konsep Fisika Siswa Kelas Vii,” no. February, pp. SNF2016-EER-71-SNF2016-EER-76, 2016, doi: 10.21009/0305010312.

D. P. Wiguna, “Pemodelan Prediksi Mahasiswa Berprestasi Akademik Dengan Multi-Linear Regression ( Studi Kasus : Prodi Sistem Informasi ) Complex : Jurnal Multidisiplin Ilmu Nasional,” vol. 2, pp. 53–58, 2025.

M. Sholeh, S. Suraya, and D. Andayati, “Machine Linear untuk Analisis Regresi Linier Biaya Asuransi Kesehatan dengan Menggunakan Python Jupyter Notebook,” J. Edukasi dan Penelit. Inform., vol. 8, no. 1, p. 20, 2022, doi: 10.26418/jp.v8i1.48822.

E. Hasibuan et al., “Implementasi Machine Learning untuk Prediksi Harga Mobil Bekas dengan Algoritma Regresi Linear berbasis Web,” J. Ilm. Komputasi, vol. 21, no. 4, pp. 595–602, 2022, doi: 10.32409/jikstik.21.4.3327.

Astuti, S. B. Waluya, and M. Asikin, “Strategi Pembelajaran dalam Menghadapi Tantangan Era Revolusi Industri 4.0,” Semin. Nas. Pascasarj. 2019, pp. 469–473, 2019, [Online]. Available: https://proceeding.unnes.ac.id/index.php/snpasca/article/view/327

D. Maulud and A. M. Abdulazeez, “A Review on Linear Regression Comprehensive in Machine Learning,” J. Appl. Sci. Technol. Trends, vol. 1, no. 2, pp. 140–147, 2020, doi: 10.38094/jastt1457.

A. Anggara, K. Auliasari, and Y. Agus Pranoto, “Metode Regresi Linier Berganda Untuk Prediksi Omset Penyewaan Kamera Di Joe Kamera,” JATI (Jurnal Mhs. Tek. Inform., vol. 7, no. 1, pp. 852–858, 2023, doi: 10.36040/jati.v7i1.6158.

L. S. Ihzaniah, A. Setiawan, and R. W. N. Wijaya, “Perbandingan Kinerja Metode Regresi K-Nearest Neighbor dan Metode Regresi Linear Berganda pada Data Boston Housing,” Jambura J. Probab. Stat., vol. 4, no. 1, pp. 17–29, 2023, doi: 10.34312/jjps.v4i1.18948.

H. Sulastri, G. S. Anwar, and E. N. F. Dewi, “Peramalan Stok Barang Percetakan dan ATK Menggunakan Single Moving Average,” J. Rekayasa Teknol. Inf., vol. 7, no. 1, p. 59, 2023, doi: 10.30872/jurti.v7i1.11876.