Correlation Between Technological Advances On Employee Performance Using A PRIORI Method (Case Study: PLN City of Binjai)
Bibliographic record
Abstract
Technology is a set of tools that can be used or utilized by humans to facilitate various forms of work. Employee performance is the ability to achieve job requirements, where a work target can be completed in a timely manner or does not exceed the time limit provided so that the goal will be in accordance with company morals and ethics. This study aims to determine the correlation of technological progress on employee performance. In this study using RapidMiner as a test of 230 data on employees of PLN Binjai City. By using the Apriori algorithm method with a minimum support value of 10% and confidence of 50%, 44 association rules are obtained in the entire set and there are 2 rules in 4 itemsets. From the test results, the best rule with the highest value is obtained, namely if the data is T7, A3, F7 then SB, which means if using Ms.Word and Ms.Excel and Ms.PPT, using FSO Mobile and PLN Mobile, using Computers and Printers and Fax Machines then employee performance is Very Good with a support value of 30% and a confidence value of 96%.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".