Development of a Smart Career Path System for Recommending Entrepreneurship Types Using a Mobile-First Approach

This study explores the development of a Smart Career Path System aimed at addressing the gap in career planning among Indonesian university students, particularly in aligning their interests and competencies with entrepreneurial career opportunities. Grounded in the increasing significance of entrepreneurship education and the growing use of technology in personalized career guidance, this research investigates how a mobile-first system can support informed decision-making for students. The system is designed using DevOps methodology and machine learning techniques, including content-based filtering and the CRISP-DM approach, to provide personalized entrepreneurship recommendations based on user profiles. This paper outlines the system's design, development process, and potential contributions to career planning and entrepreneurship readiness among university students.

Authors

Institutions

Publication Details

Journal
TEM Journal
Published
2025-08-27
DOI
https://doi.org/10.18421/tem143-28
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a Smart Career Path System for Recommending Entrepreneurship Types Using a Mobile-First Approach

Yudha Aditya Fiandra, Geovanne Farell, Elfizon Elfizon, Feri Ferdian et al.
TEM Journal
Education and Learning Interventions
article

Development of a Smart Career Path System for Recommending Entrepreneurship Types Using a Mobile-First Approach

Yudha Aditya Fiandra, Geovanne Farell, Elfizon Elfizon, Feri Ferdian, Ganefri Ganefri, Asmar Yulastri
article en

Abstract

This study explores the development of a Smart Career Path System aimed at addressing the gap in career planning among Indonesian university students, particularly in aligning their interests and competencies with entrepreneurial career opportunities. Grounded in the increasing significance of entrepreneurship education and the growing use of technology in personalized career guidance, this research investigates how a mobile-first system can support informed decision-making for students. The system is designed using DevOps methodology and machine learning techniques, including content-based filtering and the CRISP-DM approach, to provide personalized entrepreneurship recommendations based on user profiles. This paper outlines the system's design, development process, and potential contributions to career planning and entrepreneurship readiness among university students.

TEM Journal
State University of Padang (ID)
Openalex Percentile: Top 67%
Education and Learning Interventions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development of a Smart Career Path System for Recommending Entrepreneurship Types Using a Mobile-First Approach — Yudha Aditya Fiandra, Geovanne Farell, et al. · TEM Journal (2025) | TGRS Research Map | TGRS