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All Journal Media Jurnal Informatika Universal Journal of Science and Technology
Gunawan , Rizki
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

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The Influence of Work Skills and Work Experience on Improving Employee Performance in the Product Creation Center at PT Adis Dimension Footwear in Tangerang Regency Gunawan , Rizki; Yulandari, Sri
UJoST- Universal Journal of Science and Technology Vol. 4 No. 3 (2025): October 2025
Publisher : Faculty of Science and Technology University of Pramita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11111/ujost.v5i1.151

Abstract

The purpose of this study is to determine the extent to which work ability and work experience influence the performance of employees in the Product Creation Center department at PT. Adis Dimension Footwear, Tangerang Regency.This research uses a descriptive quantitative method with a sample of 73 respondents. The problem phenomenon identified by the researcher is based on the results of a preliminary survey, which showed suboptimal outcomes related to a lack of experience and work-related skills. As a result, employees have not been able to meet the targets set by the organization. In addition, many employees have not yet mastered the tasks assigned to them due to insufficient work experience. This has led to difficulties in making sound decisions, and their work performance has not met the expectations of their superiors and colleagues. These issues have ultimately led to a decline in employee performance. Based on the results of the study, it can be concluded that both work ability and work experience variables, either partially or simultaneously, have a significant influence on the performance of employees in the Product Creation Center department at PT. Adis Dimension Footwear, Tangerang Regency.
Application of Named Entity Recognition (NER) in Job Vacancy Matching Using an Ontology-Based Approach (Case Study: Information Technology Sector) Gunawan , Rizki; Hodijah, Ade; Taqwim , Muhammad Ikhsan Maulana; Siti Ababil , Afyar; Setijohatmo, Urip Teguh; Wulan, Sri Ratna; Alifi , Muhammad Riza; Sari , Aprianti Nanda; Hayati, Hashri
Media Jurnal Informatika Vol 17 No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5675

Abstract

The dissemination of job vacancies through online platforms still faces limitations in understanding the semantic relationships between the skills possessed by job seekers and the qualifications required by a job position. This mismatch results in an inefficient search process and longer search times. This study aims to develop a semantic-based job vacancy recommendation application (talent matching) using a skill ontology approach. One of the main challenges in developing the ontology is the lack of standardized data structures in job vacancy postings, particularly in the job description section. To address this issue, Named Entity Recognition (NER) techniques are applied to automatically extract skill entities from job description texts. The extracted results are then classified into a taxonomy structure using SkillsGPT, thereby forming a hierarchical skill concept model semantically represented within the ontology using Protégé. The matching process between user skills and job qualifications is conducted through semantic similarity calculations employing the Sánchez Similarity method. Job vacancy data are collected via web scraping, while system development follows the Rational Unified Process (RUP) methodology and is evaluated using Black Box testing. Evaluation results demonstrate that the developed system is capable of providing semantically relevant job vacancy recommendations according to the user's skill profile. Therefore, this study contributes both theoretically and practically to the development of ontology-based recommendation systems, particularly in the automated modeling of skill taxonomies from unstructured data.
Co-Authors Ade Hodijah Alifi , Muhammad Riza Hayati, Hashri Sari , Aprianti Nanda Setijohatmo, Urip Teguh Siti Ababil , Afyar Taqwim , Muhammad Ikhsan Maulana Wulan, Sri Ratna Yulandari, Sri