The Decision-Support Modeling with Fuzzy Analytic Hierarchy Process (AHP) to Determine the Career Path for Bachelor Informatics Students

Ezra Karuna Wijaya, Ford Lumban Gaol, Tokuro Matsuo

Abstract


The pursuit of success in one's chosen profession is a universal aspiration that requires individuals to engage in competition, not just domestically but also internationally, particularly in today's era of globalization. The rapid advancement of technology presents both opportunities and challenges, necessitating proactive management to achieve professional success. In the field of Informatics Engineering, there is a wide range of professional pathways, each offering unique opportunities and requiring distinct skill sets. For university graduates, it is crucial to have a comprehensive understanding of the specific requirements and demands associated with various job paths to make informed decisions. This knowledge enables them to select a professional route that aligns with their individual aspirations and goals, thereby avoiding potential discontent in their chosen career. Lack of knowledge or awareness during the decision-making process can negatively impact productivity and overall performance. There is a growing demand among university graduates, especially at the undergraduate level, for career-related information. This has led to heightened competition among graduates in terms of skills, knowledge, and availability. To effectively navigate this competitive landscape and engage in meaningful competition with fellow graduates, individuals must possess a comprehensive understanding of their desired career trajectory. To address these challenges, the Decision Support Model (MPK) can be utilized, employing the Fuzzy Analytical Hierarchy Process methodology. This approach considers four primary criteria—Financial Compensation, Non-Financial Compensation, Soft Skills, and Hard Skills—each with several sub-criteria. These criteria are evaluated based on the perspectives of certified graduates of Informatics Engineering and industry specialists. The study successfully identified the primary criteria influencing career decisions, such as job conditions, incentives, and prospects. It also highlighted the most favorable career path, with the role of a Data Analyst being identified as particularly promising. This career path involves roles within the field of Informatics Engineering that focus on processing data according to specific requirements, highlighting the importance of understanding the evolving landscape of technology and its impact on professional opportunities.

 

Doi: 10.28991/ESJ-2024-08-01-011

Full Text: PDF


Keywords


Fuzzy AHP; Decision Support; Career Path.

References


Jackson, M. M. (2020). Overcoming the Myth of the Contemporary “Starving Artist”: An exploration into the fusion, and viability of a 21st-century career in art and design. Master of Fine Arts Thesis, Liberty University, Virginia, United States.

Haenggli, M., & Hirschi, A. (2020). Career adaptability and career success in the context of a broader career resources framework. Journal of Vocational Behavior, 119, 119. doi:10.1016/j.jvb.2020.103414.

Hirschi, A., Nagy, N., Baumeler, F., Johnston, C. S., & Spurk, D. (2018). Assessing Key Predictors of Career Success: Development and Validation of the Career Resources Questionnaire. Journal of Career Assessment, 26(2), 338–358. doi:10.1177/1069072717695584.

Jach, H. K., Bardach, L., & Murayama, K. (2023). How Personality Matters for Education Research. Educational Psychology Review, 35(3), 94. doi:10.1007/s10648-023-09807-4.

McKenzie, S., & Bennett, D. (2022). Understanding the career interests of Information Technology (IT) students: a focus on choice of major and career aspirations. Education and Information Technologies, 27(9), 12839–12853. doi:10.1007/s10639-022-11141-1.

Rene, R., & Wahyuni, S. (2018). The Influence of Work-Life Balance on Organizational Commitment, Job Satisfaction, and Work Motivation on Individual Performance of Insurance Company Employees in Jakarta. Jurnal Manajemen Dan Bisnis Sriwijaya, 16(1), 53–63. doi:10.29259/jmbs.v16i1.6247.

Sultana, T., & Kawsar, M. (2020). Exploring the influential stimulators of career choice: an empirical assessment by exploratory factor analysis. Asian Journal of Empirical Research, 10(5), 137–149. doi:10.18488/journal.1007/2020.10.5/1007.5.137.149.

Pordelan, N., & Hosseinian, S. (2021). Online career counseling success: the role of hardiness and psychological capital. International Journal for Educational and Vocational Guidance, 21(3), 531–549. doi:10.1007/s10775-020-09452-1.

Gayatri, G., Jaya, I. G. N. M., & Rumata, V. M. (2023). The Indonesian Digital Workforce Gaps in 2021–2025. Sustainability (Switzerland), 15(1), 754. doi:10.3390/su15010754.

Pronina, O., & Piatykop, O. (2021). The decision support system education career choice using fuzzy model. CEUR Workshop Proceedings, 2870, 1204–1214.

Myla, S., Marella, S. T., Goud, A. S., Ahammad, S. H., Kumar, G. N. S., & Inthiyaz, S. (2019). Design decision taking system for student career selection for accurate academic system. International Journal of Scientific and Technology Research, 8(9), 2199–2206.

Qamhieh, M., Sammaneh, H., & Demaidi, M. N. (2020). PCRS: Personalized Career-Path Recommender System for Engineering Students. IEEE Access, 8, 214039–214049. doi:10.1109/ACCESS.2020.3040338.

Santony, J., Amir, F., Sumijan, & Novita, R. (2019). Application of AHP Analysis to Increase Employee Career Paths in Decision Support Systems. Journal of Physics: Conference Series, 1339(1), 12030. doi:10.1088/1742-6596/1339/1/012030.

Gati, I., & Tal, S. (2008). Decision-Making Models and Career Guidance. International Handbook of Career Guidance, Springer, 157–185. doi:10.1007/978-1-4020-6230-8_8.

Li, G., & Li, G. (2021). The Best Summer Job Selection Based on AHP. International Conference on Information Technology, Education and Development, 384–391.

Hermansyah, M. (2021). Implementation of decision support systems in cement supplier evaluation using fuzzy analytical hierarchy process (F-AHP). JKIE (Journal Knowledge Industrial Engineering), 8(1), 28-39.

Napierala, J., & Kvetan, V. (2023). Changing Job Skills in a Changing World. Handbook of Computational Social Science for Policy, Springer, 243–259. doi:10.1007/978-3-031-16624-2_13.

Stojanov, A., & Daniel, B. K. (2023). A decade of research into the application of big data and analytics in higher education: A systematic review of the literature. Education and Information Technologies, 1-25. doi:10.1007/s10639-023-12033-8.

Berg, L. N., Pinheiro, R., Utomo, P. P., & Nurhayati, P. Y. (2019). The responsible university in Southeast Asia: A tale of the transition from an elite to a mass higher education system. The Responsible University: Exploring the Nordic Context and Beyond, Palgrave Macmillan, 257–287. doi:10.1007/978-3-030-25646-3_10.

Sojkin, B., Bartkowiak, P., & Skuza, A. (2012). Determinants of higher education choices and student satisfaction: The case of Poland. Higher Education, 63(5), 565–581. doi:10.1007/s10734-011-9459-2.

Papastergiou, M. (2008). Are computer science and information technology still masculine fields? High school students’ perceptions and career choices. Computers & education, 51(2), 594-608. doi:10.1016/j.compedu.2007.06.009.

Kumar, P., Shukla, B., & Passey, D. (2020). Impact of accreditation on quality and excellence of higher education institutions. Investigacion Operacional, 41(2), 151–167.

Alenezi, S., Al-Eadhy, A., Barasain, R., AlWakeel, T. S., AlEidan, A., & Abohumid, H. N. (2023). Impact of external accreditation on students’ performance: Insights from a full accreditation cycle. Heliyon 9(5), e15815. doi:10.1016/j.heliyon.2023.e15815.

Bubany, S. T., Krieshok, T. S., Black, M. D., & McKay, R. A. (2008). College students' perspectives on their career decision making. Journal of Career Assessment, 16(2), 177-197. doi:10.1177/1069072707313189.

Comendador, B. E. V., Becbec, W. F. C., & Guzman, J. R. P. de. (2020). Implementation of Fuzzy Logic Technique in a Decision Support Tool: Basis for Choosing Appropriate Career Path. International Journal of Machine Learning and Computing, 10(2), 339–345. doi:10.18178/ijmlc.2020.10.2.940.

Gestiada, G., Nazareno, A., & Roxas-Villanueva, R. M. (2017). Development of a senior high school career decision tool based on social cognitive career theory. Philippine Journal of Science, 146(4), 445–455.

Mainingsih, R. D., & Hamka, M. (2021). Decision Support System for Determining Scholarship Assistance Recipients using the AHP and TOPSIS Methods. SAINTEKS, 18(1), 65-74. doi:10.30595/sainteks.v18i1.9613.

Hananto, A. L., Priyatna, B., Fauzi, A., Rahman, A. Y., & Pangestika, Y. (2021). Analysis of the Best Employee Selection Decision Support System Using Analytical Hierarchy Process (AHP). IOP Publishing: Journal of Physics: Conference Series, 1908, 012023. doi:10.1088/1742-6596/1908/1/012023.

Saha, O., Chakraborty, A., & Banerjee, J. S. (2019). A fuzzy AHP approach to IT-based stream selection for admission in technical institutions in India. Advances in Intelligent Systems and Computing, 755, 847–858. doi:10.1007/978-981-13-1951-8_75.

Raco, J., Krejci, J., Ohoitimur, J., raton, yulius, Soputan, J., Ngenget, S., & Taroreh, F. (2020). Guidance for Higher Education To Provide the Necessary Soft Skills To Meet the Needs of Industrial Era 4.0 Using AHP and Fuzzy AHP, 1-28. doi:10.13033/isahp.y2020.036.

Chan, H. K., Sun, X., & Chung, S. H. (2019). When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems, 125, 113114. doi:10.1016/j.dss.2019.113114.

Sibarani, L., Magdalena, M., & Dharma, A. (2019). Comparative Analysis of Thesis Title Similarity Detection Systems Using the Winnowing Algorithm and the Rabin Karp Algorithm. REMIK: Research and E-Journal of Computer Information Management, 4(1), 69. doi:10.33395/remik.v4i1.10174.

Caspersen, M. E., Gal-ezer, J., Mcgettrick, A., & Nardelli, E. (2018). Informatics for All: The strategy. Association for Computing Machinery, New York, United States. doi:10.1145/3185594.

BAN-PT. (2019). Attachment to the National Accreditation Board for Higher Education Regulation Number 5 of 2019 concerning Study Program Accreditation Instruments. Jakarta, Indonesia.

EduSpiral. (2021). Jobs on the Rise in South East Asia 2021. EduSpiral Consultant Services. Available online: https://eduspiral.com/2021/06/26/jobs-rise-south-east-asia-malaysia-2021-linkedin/ (accessed on May 2023).

Khodashahri, N. G., & Sarabi, M. M. H. (2013). Decision Support System (DSS). Singaporean Journal of Business, Economics and Management Studies, 1(6), 95–102. doi:10.12816/0003780.

Yuhelmi, Effendi, Z. M., Ridwan, Syamsidar, R., & Musfawati. (2021). Decision Support System with Simple Additive Weighting Method for Selection of Organizational Leaders. Turkish Journal of Computer and Mathematics Education, 12(13), 1230–1235.

Chen, L. C., & Utama, D. N. (2022). Decision Support Model for Determining the Best Employee using Fuzzy Logic and Simple Additive Weighting. Journal of Computer Science, 18(6), 530–539. doi:10.3844/jcssp.2022.530.539.

Bertrand, A., Belloum, R., Eagan, J. R., & Maxwell, W. (2022). How cognitive biases affect XAI-Assisted decision-making: A systematic review. AIES 2022 - Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 78–91. doi:10.1145/3514094.3534164.

Amos Pah, C. E. (2020). Decision Support Model for Employee Recruitment Using Data Mining Classification. International Journal of Emerging Trends in Engineering Research, 8(5), 1511–1516. doi:10.30534/ijeter/2020/06852020.

Utama, D. N. (2021). Fuzzy Logic for Decision Support Models. Penerbit Garudhawaca, Indonesia.

Putra, M. S. D., Andryana, S., Fauziah, & Gunaryati, A. (2018). Fuzzy analytical hierarchy process method to determine the quality of gemstones. Advances in Fuzzy Systems, 9094380. doi:10.1155/2018/9094380.

Natarajan, N., Vasudevan, M., Dineshkumar, S. K., & Anuja, R. (2022). Comparison of analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (f-AHP) for the sustainability assessment of a water supply project. Journal of the Institution of Engineers (India): Series A, 103(4), 1029-1039. doi:10.1007/s40030-022-00665-x.

Mohammed, H. J., Al-Jubori, I. A. M., & Kasim, M. M. (2019). Evaluating project management criteria using fuzzy analytic hierarchy Process. AIP Conference Proceedings, 2138(1), 40018. doi:10.1063/1.5121097.

Kumalasari, L. D., & Susanto, A. (2020). Recommendation System of Information Technology Jobs using Collaborative Filtering Method Based on LinkedIn Skills Endorsement. Sisforma, 6(2), 63–72. doi:10.24167/sisforma.v6i2.2240.

Maulindar, J., & Aprimavista Cahyani, D. (2019). Analysis of Factors That Influence Students' Interest in Becoming Programmers. Jurnal Penelitian Dan Pengabdian Masyarakat, 5(2), 2442–7942.

Nur Irawan, M. R. (2018). The Influence of Salaries and Incentives on Employee Work Productivity at Pt. Mahkota Sakti Jaya Sidoarjo. Ecopreneur.12, 1(1), 36. doi:10.51804/econ12.v1i1.196.

Saputra, I., & Sudharma, I. (2021). The Influence of Position Promotion, Training and Work Environment on Employee Job Satisfaction. E-Jurnal Manajemen Universitas Udayana, 6(2), 1030–1054.

Patacsil, F. F., & Tablatin, C. L. S. (2017). Exploring the importance of soft and hard skills as perceived by it internship students and industry: A gap analysis. Journal of Technology and Science Education, 7(3), 347–368. doi:10.3926/jotse.271.


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DOI: 10.28991/ESJ-2024-08-01-011

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