Analysis of student interest in choosing manual methods and computer applications in linear programming courses

Authors

  • Depriwana Rahmi Mathematics Education Study Program, Universitas Islam Negeri Sultan Syarif Kasim Riau, Riau, Indonesia
  • Suci Yuniati Mathematics Education Study Program, Universitas Islam Negeri Sultan Syarif Kasim Riau, Riau, Indonesia
  • Annisa Kurniati Mathematics Education Study Program, Universitas Islam Negeri Sultan Syarif Kasim Riau, Riau, Indonesia
  • Andie Tangonan Capinding Mathematics Department, Nueva Ecija University of Science and Technology-Gabaldon Campus, Nueva Ecija, Philippines
  • Mohamad Firdaus Ahmad Faculty of Sports Science and Recreation, UiTM Cawangan Negeri Sembilan, Seremban, Malaysia

DOI:

https://doi.org/10.30762/f_m.v9i1.6893

Keywords:

Student Interests, Manual Methods, Computer Applications, Linear Programming

Abstract

The rapid development of information technology has had a significant impact on education, including in the teaching of linear programming courses. Lecturers are required to teach both manual and computer-based application methods. However, the level of student interest in both methods remains unclear, necessitating a more in-depth analysis. This study employed a quantitative descriptive approach using a survey technique, in which the questionnaire was developed around five main indicators: ease of understanding the steps, perceived time efficiency, confidence in the final result, personal preference in solving problems, and perceived challenges or obstacles. Respondents consisted of 31 fourth-semester Mathematics Education students who had taken the Linear Programming course. The analysis indicates that software such as POM-QM for Windows and AtoZmath is more efficient and time-saving for solving linear programming problems. A total of 74.2% of students strongly agreed that these applications are more time-efficient. Students tend to prefer these tools because they enable automatic calculations that yield optimal solutions and minimize the risk of manual computation errors, thereby increasing confidence in the accuracy of the results. However, manual methods remain essential, as they promote students’ conceptual understanding, particularly in model formulation and constraint identification. Moreover, this approach strengthens mathematical reasoning and logical thinking skills, which serve as a fundamental basis for problem-solving before utilizing technological assistance. Therefore, both methods are important to teach in the classroom due to their respective advantages.

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References

Ababil, F. R. U., & Septianawati, E. (2021). Analisis kecenderungan mahasiswa tadris matematika dalam memilih aplikasi belajar berbasis e-learning berdasarkan minat belajar [Analysis of mathematics education students' tendencies in choosing e-learning-based learning applications based on learning interest]. Journal Focus Action of Research Mathematic (Factor M), 4(1), 21–30. https://doi.org/10.30762/factor_m.v4i1.3418

Abdelati, M. H., Abd-el-tawwab, A. M., Ellimony, E. E. M., & Rabie, M. (2024). Efficient and versatile methodology for solving solid transportation problem using Excel Solver: A comparative study with LINGO. MSA Engineering Journal, 3(1), 71–79. https://doi.org/10.21608/msaeng.2023.220434.1324

Abdelwali, H. A., Swilem, S. M., Shiaty, R. El., & Murad, M. M. (2019). Solving a transportation problem actual problem using Excel Solver. International Journal of Engineering and Technical Research (IJETR), 8(12), 13–17. https://www.erpublication.org/published_paper/IJETR2837.pdf

Afwat, M. A. E., Salama, A. A. M., & Farouk, N. (2018). A new efficient approach to solve multi-objective transportation problem in the fuzzy environment (product approach). International Journal of Applied Engineering Research, 13(18), 13660–13664. https://www.ripublication.com/ijaer18/ijaerv13n18_36.pdf

Al-Fraihat, D., Joy, M., Masa'deh, R., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004

Astuti, I. P., Untari, E., & Susanto, D. (2022). Pengaruh minat belajar siswa dengan sistem daring menggunakan aplikasi Simpel pada pembelajaran matematika kelas X SMA PSM 1 Kedunggalar [The effect of students' learning interest in online systems using the Simpel application in mathematics learning for grade X SMA PSM 1 Kedunggalar]. Journal Focus Action of Research Mathematic (Factor M), 5(1), 142–153. https://doi.org/10.30762/f_m.v5i1.554

Azwar, S. (2019). Penyusunan skala psikologi [Psychological scale construction] (2nd ed.). Pustaka Pelajar.

Bahri, S., & Husna, R. (2022). Application of project-based learning method for acquisition of student expertise in solving the industrial world problems. Advances in Social Science, Education and Humanities Research, 650, 114–118. https://doi.org/10.2991/assehr.k.220303.022

Bakhievish, S. O. (2023). Digital technologies in mathematics education advantages. Eurasian Journal of Learning and Academic Teaching, 19, 13–15. https://geniusjournals.org/index.php/ejlat/article/view/4292

Balogun, O. S., Emiola, R. B., & Akingbade, T. J. (2021, April 1–2). On the application of linear programming on a transportation problem [Paper presentation]. 37th International Business Information Management Association (IBIMA) Conference, Cordoba, Spain.

Bazine. (2025). Exploring the development of the Technology Acceptance Model (TAM): A chronological overview. International Journal of Research and Scientific Innovation (IJRSI), 12(2321), 1643–1655. https://doi.org/10.51244/IJRSI.2025.120600138

Danfulani, U. B., Joshua, A. Y., Oludele, R. A., Hassan, M., & Jonathan, T. (2022). Application of linear programming model for optimal production planning: A case study of Adama Beverages, Jimeta Yola, Adamawa State, Nigeria. Jewel Journal of Scientific Research (JJSR), 7(2), 268–278. https://journals.fukashere.edu.ng/index.php/jjsr/article/view/141

Davis, F. D. (1993). User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts. International Journal of Man-Machine Studies, 38(3), 475-487. https://doi.org/10.1006/imms.1993.1022

Guo, Z., & Fryer, L. K. (2024). What really elicits learners' situational interest in learning activities: A scoping review of six most commonly researched types of situational interest sources in educational settings. Current Psychology, 44, 587–601. https://doi.org/10.1007/s12144-024-07176-x

Hermawanti, E., Prasetya, G. A. A., Purnamasari, N. D., Utami, R. D., & Maulidah, N. L. (2025). Classroom action research: increasing learning interest of Grade IV students through the TGT model assisted by Quizwhizzer. Journal Focus Action of Research Mathematic (Factor M), 8(1), 17–34. https://doi.org/10.30762/f_m.v8i1.4916

Hillmayr, D., Ziernwald, L., Reinhold, F., Hofer, S. I., & Reiss, K. M. (2020). The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education, 153, Article 103897. https://doi.org/10.1016/j.compedu.2020.103897

Jha, A., Sahani, S. K., Jha, A., & Sahani, K. (2023). Business insights unveiled: A journey through linear programming problems. Mikailalsys Journal of Mathematics and Statistics, 1(1), 1–14. https://doi.org/10.58578/mjms.v1i1.1948

Krynke, M., & Mielczarek, K. (2018). Applications of linear programming to optimize the cost-benefit criterion in production processes. MATEC Web of Conferences, 183, Article 04004. https://doi.org/10.1051/matecconf/201818304004

Kurniawati, A. D., Saputra, M. R., & Fiangga, S. (2025). A quantitative investigation of mathematical identity and its components in prospective mathematics teachers. Journal Focus Action of Research Mathematic (Factor M), 8(2), 262–287. https://doi.org/10.30762/f_m.v8i2.6373

Kusi, P., Boateng, F. O., & Teku, E. (2025). The effect of technology integration on college of education students' achievement in quadratic equations: The perspective of Photo Math utilization. EURASIA Journal of Mathematics, Science and Technology Education, 21(1), 1–14. https://doi.org/10.29333/ejmste/15799

Laksmiwati, P. A. (2018). Enhancing Indonesian students' self-confidence through the integration of problem-based learning (PBL) and technology. Southeast Asian Mathematics Education Journal, 8(1), 13–27. https://doi.org/10.46517/seamej.v8i1.60

Legramante, D., Azevedo, A., & Azevedo, J. M. (2023). Integration of the Technology Acceptance Model and the Information Systems Success Model in the analysis of Moodle's satisfaction and continuity of use. International Journal of Information and Learning Technology, 40(5), 467–484. https://doi.org/10.1108/IJILT-12-2022-0231

Munot, D. A., & Ghadle, K. P. (2022). A GM method for solving solid transportation problem. Journal of Algebraic Statistics, 13(3), 4841–4846. https://publishoa.com/index_php/journal/article/view/1328

Padalko, A., Padalko, N., Padalko, H., & Yakovlev, S. (2021). Application of information and communication technologies during linear programming learning. Proceedings of the Symposium on Information Technologies & Applied Sciences (IT&AS 2021), 192–201.

Pannen, P. (2015). Integrating technology in teaching and learning mathematics. Southeast Asian Mathematics Education Journal, 5(1), 31–47. https://doi.org/10.46517/seamej.v5i1.31

Patalatu, J. S., & Boari, Y. (2024). Buku ajar metodologi penelitian [Teaching book on research methodology]. PT. Sonpedia Publishing Indonesia.

Petkovi, I. (2021). Computer tools for solving mathematical problems: A review. Mathematics and Informatics, 36(1), 205–236. https://doi.org/10.22190/FUMI201203017P

Prifti, V., Dervishi, I., Doska, K., Markja, I., & Pramono, A. (2020). Minimization of transport costs in an industrial company through linear programming. IOP Conference Series, 909(1), Article 012040. https://doi.org/10.1088/1757-899X/909/1/012040

Rachmatika, R. (2022). Penerapan aplikasi program linear dengan menggunakan metode simpleks untuk mendukung kegiatan UMKM [Application of linear programming using the simplex method to support MSME activities]. KLIK: Kajian Ilmiah Informatika dan Komputer, 3(2), 194-202. https://doi.org/10.30865/klik.v3i2.596

Rashidov, A. (2020). Use of differentiation technology in teaching. European Journal of Research and Reflection in Educational Sciences, 8(7), 163–167.

Renninger, K. A., & Hidi, S. (2022). Interest development, self-related information processing, and practice. Theory into Practice, 61(1), 23–34. https://doi.org/10.1080/00405841.2021.1932159

Renninger, K. A., Elias, R. C., Kamiya, M. J., Paige, J. N., & Youngblood, R. (2025). Supporting CS and math integration: Implications of teacher interest and confidence for workshop design. Computer Science Education, 35(3), 1–30. https://doi.org/10.1080/08993408.2024.2433334

Riandari, F., & Sihotang, H. T. (2025). Distribution cost optimization: Comparison of NWC, MODI, and stepping stone methods in transportation problems. International Journal of Basic and Applied Science, 14(2), 85–96. https://doi.org/10.35335/ijobas.v14i2.688

Rushiti, E., Beqiri, A., Iseni, E., & Rexhepi, S. (2022). SimplexAlgo software for solving problems in linear programming. Journal of Mathematics, Computer Science and Education, 5(1), 9–18. https://doi.org/10.54664/YGJS5089

Sojobi, O. A., Adedipupo, O. O., Ajobo, J. A., Adedayo, A. A., & Fadare, A. (2022). Application of linear programming to minimize transportation cost in Nigeria Breweries Plc, Ibadan, Oyo State, Nigeria. African Journal of Mathematics and Statistics Studies, 5(3), 75–86. https://doi.org/10.52589/AJMSS-TILFQZRZ

Tiwow, D., Wongkar, V., Mangelep, N. O., & Lomban, E. A. (2022). Pengaruh media pembelajaran animasi Powtoon terhadap hasil belajar ditinjau dari minat belajar peserta didik [The effect of Powtoon animation learning media on learning outcomes in terms of students' learning interest]. Journal Focus Action of Research Mathematic (Factor M), 4(2), 107–122. https://doi.org/10.30762/factor_m.v4i2.4219

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926

Victor-Edema, U. A., & Akehwe, O. E. (2024). Application of linear programming in the minimization of transportation cost in Dangote Cement, Port Harcourt. African Journal of Mathematics and Statistics Studies, 7(1), 20–32. https://doi.org/10.52589/AJMSS-YZHCHSBO

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Published

30-06-2026

How to Cite

Rahmi, D., Yuniati, S., Kurniati, A., Capinding, A. T., & Ahmad, M. F. (2026). Analysis of student interest in choosing manual methods and computer applications in linear programming courses. Journal Focus Action of Research Mathematic (Factor M), 9(1), 244–258. https://doi.org/10.30762/f_m.v9i1.6893

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