ANALISIS KOMPETENSI SDM DALAM PENINGKATAN KINERJA MELALUI PENGUASAAN TEKNOLOGI PADA KANTOR PERTANAHAN KABUPATEN BONE
Bibliographic record
Abstract
Penelitian ini dilakukan bertujuan untuk: (1) menganaliisis pengaruh langsung Kompetensi SDM, dan Penguasaan teknologi terhadap kinerja, (2) menganaliisis pengaruh langsung Penguasaan teknologi terhadap kinerja, (3) menganaliisis pengaruh langsung Kompetensi SDM terhadap kinerja, (4) menganaliisis pengaruh tidak langsung Kompetensi SDM terhadap kinerja melalui Penguasaan teknologi. Penelitian ini menggunakan data primer melalui survei sebanyak 52 Pegawai sebagai populasi. Adapun sampel dalam penelitian adalah sebanyak 50 orang dengan meteode penentuan sampel menggunakan rumus Slovin, penelitian dilakukan selama 2 (dua) bulan yaitu Februari s.d April 2025. Data dianalisis dengan menggunakan program SmartPLS. Hasil penelitian menunjukkan bahwa: (1) Pengaruh Kompetensi SDM berpengaruh langsung terhadap Kinerja Pegawai, (2) Kompetensi SDM berpengaruh terhadap implemenatsi teknologi, (3) Penguasaan teknologi berpengaruh terhjadap kinerja, (4) dan Kompetensi SDM berpengaruh tidak langsung terhadap kinerja Pegawai melalui Penguasaan teknologi. This research was conducted with the following objectives: (1) to analyze the direct influence of human resource competence and technology mastery on performance, (2) to analyze the direct influence of technology mastery on performance, (3) to analyze the direct influence of human resource competence on performance, and (4) to analyze the indirect influence of human resource competence on performance through technology mastery. This research used primary data obtained through a survey of 52 employees in the population. The sample in this research consisted of 50 people, with the sample determination method using the Slovin formula. The research was conducted for two months, from February to April 2025. The data was analyzed using the SmartPLS program. The results of the study show that (1) HR competency has a direct effect on employee performance, (2) HR competency affects technology implementation, (3) technology mastery affects performance, and (4) HR competency has an indirect effect on employee performance through technology mastery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".