Oct 2026· Maeswara Jurnal Riset Ilmu Manajemen dan Kewirausahaan
Employee Performance and Management
Abstract
This study investigates the partial and simultaneous impact of digitalization and competence on employee performance within the Region 1 Education Sub-agency of East Jakarta Administrative City. The rationale for this research stems from the imperative for government agencies to ensure employees possess adequate competence to leverage digitalization effectively and enhance performance. A quantitative research methodology was employed, utilizing a saturated sampling technique that included all 56 active employees as the sample. Data were collected through questionnaires and subsequently analyzed using SPSS software. The analytical procedures encompassed validity and reliability tests, classical assumption tests, multiple linear regression analysis, t-tests, F-tests, and the coefficient of determination (R²) test. The findings reveal that, partially, digitalization does not significantly affect employee performance (significance value = 0.329 > 0.05; t-count = 0.985 < t-table = 1.674). Similarly, competence also demonstrates no significant effect on employee performance (significance value = 0.176 > 0.05; t-count = 1.372 < t-table = 1.674). Furthermore, the simultaneous analysis indicates that digitalization and competence collectively do not significantly influence employee performance (F-count = 1.859 < F-table = 3.17; significance value = 0.166 > 0.05). The coefficient of determination (R²) is 0.30, suggesting that digitalization and competence account for only 30% of the variance in employee performance, with the remaining 70% attributable to unexamined factors. These results underscore the necessity for a comprehensive evaluation of current digital system implementation and the ongoing development of employee competence programs.
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The Mobile-D approach is briefly outlined here and the experiences gained from four case studies are discussed, which helped develop an agile development approach for mobile application development.
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StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
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