Pengaruh Knowledge Management Terhadap Kinerja Pegawai di Jurusan MIPA - Ketut Agustini; I Gde Wawan Sudatha; I Wayan Sukra Warpala; Ida Ermiana (Jurnal Penelitian Pendidikan IPA, 2022)
Knowledge management is a concrete form of knowledge management in the Mathematics and Natural Sciences department. The components of knowledge management that want to see the effect are humans, process and technology on employee performance. The aim is to determine the effect of knowledge management (people, process and technology) on employee performance. This type of research is experimental and research instruments questionnaire sheets and interview sheets. The significance value of knowledge management on employee performance is 0.260 > 0.05. This means that there is no effect of knowledge management (X) on employee performance (Y). The correlation value (R) is 0.353, meaning that the correlation between the two variables is weak and the R value is positive, meaning that there is a positive and unidirectional relationship between the knowledge management variable and employee performance. The people indicator on employee performance has a significance value of 0.158 > 0.05. This means that there is no effect of the people indicator on employee performance. Correlation of 0.456 means that the relationship between the two variables is weak. The process indicator obtained a significance value of 0.471 > 0.05. This means that there is no effect of process indicators on employee performance. The correlation value (R) is 0.243, meaning that the correlation between the two variables is weak. The significance value of technology indicators on employee performance is 0.3 > 0.05. This means that there is no effect of technology indicators on employee performance. The correlation value (R) is 0.344, meaning that the correlation between the two variables is weak. Then the R value for the people, process and technology indicators is positive, meaning that there is a positive and unidirectional relationship between the people, process and technology variables and employee performance.