The Need Mapping of Motorcycle Automotive Industry & LSP-P1 Certification: A Collaboration between Professional Certification Institutions Vocational High School (SMK-LSP) to Improve the Competitiveness of TVET Graduates in West Java Province

The motorcycle automotive industry in West Java is growing rapidly. However, there is a gap between the skills of graduates of Vocational High School Teknik dan Bisnis Sepeda Motor (SMK-TBSM) and the specific needs of the motorcycle automotive industry that continues to grow. As a result, it is necessary to map the needs of the industry for graduates of vocational education. The use certification of the Professional Certification Institution (LSP-P1) can help overcome this gap, but it has not been optimized. The cooperation between Vocational High School and LSP-P1 can improve the competitiveness of graduates. In the context of the rapid growth of the automotive industry, the relevance of vocational education to industry needs is becoming increasingly important. The urgency of this research lies in the importance of identifying the competency gap between Vocational High School graduates and industry needs, and the need to improve the competitiveness of Vocational High School graduates. This study aims to map the needs of the motorcycle automotive industry for Vocational High School graduates, analyze the LSP-P1 certification scheme and its potential in improving the competitiveness of Vocational High School graduates, develop an ideal cooperation model between Vocational High School and LSP-P1, and make strategic recommendations to improve the competitiveness of Vocational High School graduates in West Java. This study uses descriptive and exploratory design, the sampling technique is purposive sampling, data collection through in-depth interviews with stakeholders (industry representatives, LSP, vocational education practitioners and vocational schools), and surveys to vocational school alumni who have LSP certification to assess the impact of certification on their competitiveness. The data analysis is done qualitatively.