FAKTOR PENENTU KEPUASAN MASYARAKAT PADA PELAYANAN KARTU TANDA PENDUDUK ELEKTRONIK (E-KTP) DI KECAMATAN PRACIMANTORO, KABUPATEN WONOGIRI
Bibliographic record
Abstract
This research is used to know and analyze any determinant factors that affect Quality of Identity Card (E-KTP) Service to Satisfaction of Society in Pracimantoro Sub-district, Wonogiri Regency. The method used in this research is the method of observation and questionnaire by using Likert scale. Sampling method used using convenience sampling method as many as 100 samples. The method of analysis used is the test of validity, reliability test, classical assumption test, multiple linear regression test. The result of multiple linear regression test shows that the service quality consisting of Tangibles (X1), Assurance (X2) and Empathy (X3) partially or individually has a significant influence on the satisfaction of society. Where the regression equation Y = 1.853 + 0.251X1 + 0.106X2 + 0.162X3 + 0.207X4 + 0.196X5. The result of t test shows that the quality of service consisting of Tangibles (X1), Assurance (X2) and Empathy (X3) has significant effect on the satisfaction of the community is shown by significant of each variable <0,05. In the F test results obtained value obtained Fcount value of 22.732 with a significance level of 0.000 <0.05 this means that the variables together have a significant influence on community satisfaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 teacher head, 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".