International Journal for Applied Information Management
Vol. 4 No. 3 (2024): Regular Issue: September 2024

Applying K-Means Clustering to Group Jobs Based on Location and Experience Level: Analysis of the Job Recommendation

Kumar, Vinoth (Unknown)
S, Priya (Unknown)



Article Info

Publish Date
01 Sep 2024

Abstract

Labor market analysis plays a crucial role in helping job seekers identify employment opportunities that align with their qualifications, location, and experience level. This study uses the K-Means clustering algorithm to group jobs based on these critical factors. By analyzing job market data, the research identifies the most sought-after skills across various industries and highlights the geographic and experience-level disparities in job availability. Key findings include the high demand for foundational skills such as customer service, sales, and production planning, as well as more specialized skills like Medical Research in certain sectors. The study provides actionable insights for job seekers and policymakers, suggesting that targeted skill development and training programs are essential for improving job match quality. However, the study also acknowledges its limitations, such as the lack of consideration for broader economic and social factors that influence labor market trends. Future research is recommended to address these gaps, using more comprehensive datasets and advanced analytical techniques.

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Journal Info

Abbrev

ijaim

Publisher

Subject

Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Social Sciences

Description

Journal menerbitkan penelitian tentang semua aspek manajemen informasi. Informasi dilihat di sini secara luas untuk mencakup tidak hanya produk/layanan dan proses tetapi juga pasar, dan organisasi serta informasi sosial. Ini termasuk studi tentang proses secara keseluruhan atau tahap individu, ...