Impact of High Vocational Education Revitalizationon the Quality of Information Technology

Gunawan Budi Santoso,Akhmad Nuriyanis,Sri Tutie Rahayu,Yayat Ruhiat

Polimarin as an organizer of vocational education in the maritime field under the Ministry of Research, Technology and Higher Education needs to improve the quality of information technology owned. Revitalization is one of the efforts to improve the quality of information technology in Polimarin. The research method used is quantitative and uses the type of explanatory research, which aims to examine the impact of two variables, namely the independent variable (revitalization of higher education in maritime vocational) and non-independent variables (quality of human resources). The data taken were 50 respondents Polimarin respondents. Data collected through questionnaires answered by respondents, each answer in the questionnaire answered by respondents was scored based on a Likert scale. For the purposes of data analysis, the linear regression analysis technique was used in the SPSS program (Statistical Package for Social Science). The formulation of the problem in this study is whether there is an impact of revitalizing higher education on maritime vocational education on the quality of information technology in Polimarin Semarang. The measurement of the impact used a regression analysis between revitalization variables with Polimarin Semarang human resources. In addition, other measurements use significance values. With the results of regression analysis and significance values it will show a positive or negative impact. The results of this study are regression statistical tests showing the results of the t count value of 2.447 and a significance value of 0.018. Then there is a significant (significant) impact on the variable of revitalization of vocational higher education (variable X) on the variable quality of information technology (variable Y). The impact of the variable revitalization of vocational higher education (variable X) on the information technology quality variable (Y variable) is 11.1%, while the rest is impacted by other factors.

Volume 11 | 05-Special Issue

Pages: 1815-1820