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THE EFFECT OF LEARNING DISCIPLINE AND K3 UNDERSTANDING ON LEARNING OUTCOMES OF LATHE MACHINING Nikolaus Irahewa; Marsono
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 5 No. 10 (2026): SEPTEMBER
Publisher : RADJA PUBLIKA

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Abstract

This study aims to analyze the influence of learning discipline and understanding of Occupational Safety and Health (K3) on the learning outcomes of lathe machining practices of students at SMK Turen. This study uses a quantitative approach with an ex-post facto design. The research sample consisted of 32 students who participated in lathe machining practices. Data regarding learning discipline and understanding of K3 were collected using a questionnaire, while data on learning outcomes were obtained through documentation. The data were analyzed using multiple linear regression with the help of IBM SPSS Statistics. The results showed that learning discipline did not have a significant partial effect on learning outcomes of lathe machining practices, with a significance value of 0.075, while understanding of K3 also did not have a significant effect with a significance value of 0.074. Simultaneously, learning discipline and understanding of K3 did not have a significant effect on learning outcomes, as indicated by an F value of 1.718 and a significance value of 0.197. The regression model produced an R value of 0.326 and an R Square of 0.106, indicating that the model explains 10.6% of the variation in learning outcomes, while the remaining 89.4% is related to factors outside the model. The analysis also showed a very high correlation between learning discipline and understanding of K3 (r = 0.962) and a VIF value of 13.429 indicating high multicollinearity between the independent variables. These findings indicate that the learning outcomes of lathe machining practices in the analyzed sample cannot be significantly explained only through learning discipline and understanding of K3. Further research needs to consider other relevant variables and use larger and more representative samples.