# Student Career Preferences Segmentation Based on Personality, Interests, and Competencies
> Erna A.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_105032512004
Jurnal / Konferensi: 2025 7th International Conference on Cybernetics and Intelligent System Icoris 2025
Tahun terbit: 2025
DOI: https://doi.org/10.1109/ICORIS67789.2025.11296043
Citations: 0

## Authors
- Erna A.

## Abstract
The disparity between graduate capabilities and industrial needs has significant implications for higher education. Consequently, institutions are expected to produce graduates whose skills align with the evolving demands of labor market societies, thereby contributing to inclusive and sustainable economic growth. However, many Indonesian institutions still lack a structured, data-driven mechanism to align students' personalities, interests, and competencies with suitable career pathways. This study addresses this gap by applying the K-means algorithm to analyze career preference patterns among 100 students at Dipa University of Makassar. In segmentation research, this algorithm is a preferred method due to its balance of simplicity and power, particularly in areas like customer profiling, career guidance, and educational analytics. Our data on the 100 students included demographic profiles, personality types (introvert, extrovert, ambivert), dominant interests (analytical, creative, interpersonal), and competencies (data science, programming, intelligent systems, graphic design). The analysis identified three distinct profiles: Cluster 0, namely The Balanced Adaptors, characterized by a balanced mix of personalities with versatile interests and moderate technical skills; Cluster 1, namely The Creative Communicators, predominantly introverted, with strong creative and interpersonal inclinations and proficiency in graphic-related skills; and Cluster 2, namely The Analytical Ambiverts, mainly ambiverted, exhibiting pronounced analytical and computational strengths. These findings underscore the potential of cluster-based analysis techniques for generating actionable student profiles, enabling institutions to design data-informed career guidance policies. The proposed approach offers a viable model for reducing the skills-industry mismatch and enhancing graduate employability within the Indonesian higher education context.

## Keywords
- Employability
- Market segmentation
- Personality psychology
- Segmentation
- Higher education
- Personality
- Psychology
- Cluster (spacecraft)
- Computer science
- Career development
- Knowledge management
- Interpersonal communication
- Heuristics
- Preference
- Indonesian
- Productivity
- Marketing
- Proactivity
- Reliability (semiconductor)
- Transferable skills analysis
- Career portfolio
- Medical education
- Typology
- Big Five personality traits
- Graduate students
- Cognitive Information Processing
- Constructive
- TUTOR
- Applied psychology
- Public relations
- Assertiveness

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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