Abstract
This study aims to analyze the factors influencing the preferences of 2021 Digital Business students from Medan State University in choosing a smartphone operating system, namely Android or iOS. Data were collected from 39 students through an online questionnaire containing variables such as the habit of taking photos, posting photos, playing games, watching videos (streaming), and the intensity of smartphone use. The analysis was conducted using the C4.5 algorithm to build a decision tree and identify the most influential attributes. The results showed that the habit of posting photos was the factor with the highest gain, followed by the activities of taking photos, streaming movies, and playing games. Decision patterns indicated that students with high digital activity—especially those who enjoy posting photos, taking photos, streaming movies, and playing games—were more likely to choose Android. Meanwhile, the choice of iOS appeared in groups with certain activity patterns, such as not liking to take photos but actively posting. These findings provide insights for smartphone manufacturers and technology industry players to formulate more targeted marketing strategies based on students' digital behavior. This study also expands understanding of the application of data mining, specifically the C4.5 algorithm, in consumer preference analysis.
References
Apriana, D., & Yuliansyah, C. (2024). Mengoptimalkan penjualan online melalui teknik data mining (studi kasus e-commerce). AL-MIKRAJ Jurnal Studi Islam Dan Humaniora, 4(2), 514-527. https://doi.org/10.37680/almikraj.v4i02.4774
Cholis, H. (2023). Analisis faktor yang mempengaruhi minat pembelian terhadap smartphone di yogyakarta. [Skripsi Sarjana, Universitas Islam Indonesia]. https://dspace.uii.ac.id/handle/123456789/42417
Gifary, S. (2015). Intensitas penggunaan smartphone dan perilaku komunikasi (Studi pada pengguna smartphone di kalangan mahasiswa program studi Ilmu Komunikasi Universitas Telkom). Jurnal Sosioteknologi, 14(2), 170-178. https://doi.org/10.5614/sostek.itbj.2015.14.2.7
Habibie, F. H., Aryapranata, A., & Sakti, P. J. (2024). Analisis keputusan pembelian smartphone pada generasi Z. REVITALISASI: Jurnal Ilmu Manajemen, 13(2), 343-351. https://doi.org/10.32503/revitalisasi.v13i2.6286
Hidayat, R., Hakim, A. B., & Nugraha, R. (2024). Perbandingan Metode Naïve Bayes Dan Decision Tree C4. 5 untuk Analisis Sentimen Produk Es Teh Indonesia di Media Sosial Twitter. Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan), 7(2), 88-98. https://doi.org/10.47970/siskom-kb.v7i1.537
Irawadi, J. A., & Sunendiari, S. (2021). Penerapan dan perbandingan tiga metode analisis pohon keputusan pada klasifikasi penderita kanker payudara. Journal Riset Statistika, 1, 19–27. https://doi.org/10.29313/jrs.v1i1.22
Kusrini, & Luthfi, E. T. (2021). Data mining: Konsep dan aplikasi menggunakan MATLAB. Andi Offset.
Larose, D. T. (2019). Data mining: The art and science of customer relationship management. Elex Media Komputindo.
Nasution, M. A., Ulumuddin, Z. A., & Fitri, A. (2024). Analisis faktor risiko diabetes melitus menggunakan algoritma c4. 5: implementasi pada aplikasi orange. Jurnal Sains, Teknologi & Komputer, 1(3), 75-79. https://doi.org/10.56495/saintek.v1i3.1345
Sriani, S., & Suhardi, S. (2024). Analisis sentimen pengguna aplikasi mobile jkn menggunakan algoritma naïve bayes classifier dan c4.5. Journal of Science and Social Research, 7(2), 555-563. https://doi.org/10.54314/jssr.v7i2.1873

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