Pengaruh Ketergantungan Kecerdasan Buatan terhadap Motivasi Belajar Siswa pada Sistem Persamaan Linear Dua Variabel

Lulu Karimatul Khusna; Failasuf Fadli

doi:10.24832/jpnk.v10i2.5903

Pengaruh Ketergantungan Kecerdasan Buatan terhadap Motivasi Belajar Siswa pada Sistem Persamaan Linear Dua Variabel

Lulu Karimatul Khusna

Universitas Islam Negeri KH Abdurrahman Wahid - Indonesia

Failasuf Fadli

Universitas Islam Negeri KH Abdurrahman Wahid - Indonesia

DOI: https://doi.org/10.24832/jpnk.v10i2.5903

Submitted

May 23, 2025

Published

Dec 30, 2025

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Citation

Khusna, L. K., & Fadli , F. (2025). Pengaruh Ketergantungan Kecerdasan Buatan terhadap Motivasi Belajar Siswa pada Sistem Persamaan Linear Dua Variabel . Jurnal Pendidikan Dan Kebudayaan, 10(2), 211–226. https://doi.org/10.24832/jpnk.v10i2.5903

Abstract

Pesatnya perkembangan kecerdasan buatan/artificial intelligence (AI) berdampak pada proses belajar mengajar, termasuk pada pembelajaran matematika. Ketergantungan siswa pada AI untuk menyelesaikan soal-soal matematika, seperti pada materi Sistem Persamaan Linear Dua Variabel (SPLDV) menimbulkan kekhawatiran akan menurunnya motivasi belajar mandiri dan pemahaman konsep. Tujuan penelitian ini untuk menguji sejauh mana pengaruh ketergantungan AI dalam menyelesaikan materi Sistem Persamaan Linier Dua Variabel terhadap motivasi belajar matematika siswa. Studi ini menggunakan metode kuantitatif dengan pengumpulan data melalui kuesioner dan tes. Subjek penelitian terdiri atas 66 siswa kelas 8A dan 8B di SMPN 15 Kota Pekalongan, Jawa Tengah. Tes kelas eksperimen dilakukan dengan bantuan AI, sedangkan tes kelas kontrol tanpa bantuan AI. Kuesioner digunakan untuk mengukur tingkat motivasi belajar serta tingkat ketergantungan siswa terhadap AI. Data dianalisis menggunakan uji independent sample t-test untuk membandingkan hasil tes antara kelas eksperimen dan kelas kontrol. Hasil analisis menunjukkan adanya pengaruh yang cukup signifikan antara ketergantungan siswa pada AI dan semangat belajar siswa dalam menyelesaikan materi SPLDV. Kesimpulan, penelitian ini menegaskan pentingnya mempertimbangkan dampak pemanfaatan AI dalam proses pendidikan. Penelitian ini menambah pengetahuan bagi pendidik dalam merancang strategi pengajaran yang lebih seimbang dalam penggunaan teknologi untuk meningkatkan motivasi siswa dalam belajar.

Keywords

Kecerdasan Buatan motivasi belajar pembelajaran matematika ketergantungan AI

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References

Abdullah, K., Jannah, M., Aiman, U., Hasda, S., Fadilla, Z., Taqwin, Masita, Ardiawan, K. N., & Sari, M. E. (2022). Metodologi Penelitian Kuantitatif. Yayasan Penerbit Muhammad Zaini.

Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education, 4, 100131. https://doi.org/10.1016/j.caeai.2023.100131

Al-Khassawneh, Y. A. (2023). A review of artificial intelligence in security and privacy: Research advances, applications, opportunities, and challenges. Indonesian Journal of Science and Technology, 8(1), 79 96. https://doi.org/10.17509/ijost.v8i1.52709

Attali, Y., & Kleij, F. Van Der. (2017). Effects of feedback elaboration and feedback timing during computer-based practice in mathematics problem solving Computer&Education, 110(3). https://doi.org/10.1016/j.compedu.2017.03.012

Bintang, R., Pratiwi, A., Naufal, M., & Prameswari, F. E. (2025). Transformasi konseling multibudaya: Penggunaan kecerdasan buatan ( AI) terhadap rasa percaya diri dan motivasi belajar generasi Z. Proseding Konseling Kearifan Nusantara (KKN), 943-958

Borba, M. C., Askar, P., Engelbrecht, J., Gadanidis, G., & Llinares, S. & Aguilar, M. S. (2016). Blended learning, e-learning, and mobile learning in mathematics education. ZDM. Mathematics Education, 48(5), 589–610.

Borboeva, G., Kalbekova, M., Seiitkazyeva, G., & Sarygulova, N. (2025). Mengevaluasi efektivitas teknologi pembelajaran interaktif dalam meningkatkan pemikiran spasial di kalangan siswa matematika. Jurnal Ilmiah Ilmu Terapan Universitas Jambi, 9(3). https://online-journal.unja.ac.id/JIITUJ/article/view/42557

Chakyarkandiyil, N., & Prakasha, G. S. (2025). Impact of online cooperative learning strategies on self-directed learning among pre-service teachers. Journal Of Education and Learning, 19(4), 1914–1921. https://doi.org/10.11591/edulearn.v19i4.23496

Dwijayani, N. M. (2019). Development of circle learning media to improve student learning outcomes. Journal of Physics: Conference Series, 1321(2), 1–7. https://doi.org/10.1088/1742-6596/1321/2/022099

Fatahillah, A., Istiqomah, M., & Dafik. (2021). Pemodelan Matematika pada kasus kecanduan game online menggunakan metode runge-kutta orde 14. Limits:Journal of Mathematics and its Aplication, 18(2), 129–141. https:// doi.org/http://dx.doi.org/10.12962/limits.v18i2.6854

Fiialka, S., Kornieva, Z., & Honcharuk, T. (2023). ChatGPT in Ukrainian Education: Problems and Prospects. International Journal of Emerging Technologies in Learning (IJET), 18(17), 236–250. https://doi.org/10.3991/ijet.v18i17.42215

Guan, L. (2024). A conformal test of linear models via permutation-augmented regressions. Ann Statist, 52(5), 2059–2080. https://doi.org/10.1214/24-AOS2421

Iterbeke, K., De Witte, K., & Schelfhout, W. (2020). The effects of computer assisted adaptive instruction and elaborated feedback on learning outcomes. A randomized control trial. Computer in Human Behaviour, 120(1), 9. https://doi.org/10.1016/j.chb.106666

Junisha, V., Kristiani, F., & Yong, B. (2019). Analisis perbandingan bilangan reproduksi dasar pada model penyebaran penyakit dengue dengan pengaruh faktor usiadi Kota Bandung. Limits: Journal of Mathematics and Its Applications, 16(2), 73–86. https://doi.org/http://dx.doi.org/10.12962/limits.v

Kasneci, E., Sessler, K., & Kucheman, S. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Difference, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Mesurado, B., Richaud, M. Christina, & Mateo, N. Jose. (2016). Engagement, Flow, Self-Efficacy, and Eustress of University Students: A Cross-National Comparison Between the Philippines and Argentina Title. The Journal of Psychology, 150(3), 281–299. https://doi.org/10.1080/00223980.2015.1024595

Nurkholisa, F, dan Rachm awati T.K.(2024). Analisis kesulitan siswa kelas X pada materi sistem persamaan linear dua variabel. Gunung Djati Conference Series Mathematics Education on Research Publication (MERP II), 40, 1–8. https://conferences.uinsgd.ac.id/index.php/gdcs/article/view/2134

Ouahi, M. Ben, Lamri, D., Hassouni, T., & Alibrahmi, E. Mahdi. (2022). Science teachers’ views on the use and effectiveness of interactive simulations in science teaching and learning. International Journal of Instruction, 15(1), 277–292. https://doi.org/10.29333/iji.2022.15116a

Oumelaid, N., El Boukari, B., & Ghordaf, J. El. (2025). Analyzing the impact of digital classrooms on mathematics calculation skills and learners’ motivation. Journal of Education and Learning (EduLearn), 19(3), 1270. https://doi.org/10.11591/edulearn.v19i3.22564

Salsabila, F. N., Bukhari, F., & Nurdiati, S. (2025). Mathematical study for proving correctness of the serial graph-validation queue scheme. Journal of The Indonesian Mathematical Society, 31(2), 13. https://doi.org/10.22342/jims.v31i2.1592

Sari, H. E., Tumanggor, B., & Efron, D. (2024). AI feedback in improving learning outcomes. International Transactions on Artificial Intelligence (ITALIC), 3(1), 21–31. https://doi.org/10.33050

Septiaseh, D., Munfariqoh, A., & Bayu Ibrahim, M. S. (2024). Constructivism theory in multidisciplinary elementary science learning environment. International Seminar on Student Research in Education, 3047, 599–609. https://www.issrestec.id/

Silitonga, L. M., Hawanti, S., Feisal, A., Furqon, M., Zain, D. S. M., & Anjarani. (2023). The impact of AI chatbot-based learning on students’ motivation in english writing classroom. Innovative Technologies and Learning, 14009, 542–549.

Siregar, S. (2017). Statistika terapan untuk mahasiswa peguruan tinggi (2nd ed.). PT. Kharisma Putra Utama.

Sugiyono. (2004). Metode Penelitian. Alfabeta.

Thesmar, D., Sraer, D., Pinheiro, L., Dadson, N., Veliche, R., & Greenberg, P. (2019). Combining the power of artificial intelligence with the richness of healthcare claims data: Opportunities and challenges. Pharmacoeconomics, 37(6), 745–752. https://doi.org/10.1007/s40273-019-00777-6

Uni, D., & Michael, B. (2011). Dynamics of change of mathematics education in Brazil and a scenario of current research. ZDM–The Mathematics Education, 42(3), 271–279.

Zirar, A., Ali, S. I., & Islam, N. (2023). Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda. Technovation,124, 102747. https://doi.org/10.1016/j.technovation.2023.102747