USE AND EASY OF THE SYSTEM IN USING THE ONLINE PARTICIPANTS REPORTING INFORMATION SYSTEM (SIPP)
Bibliographic record
Abstract
Online Participant Reporting Information System (SIPP) is an online participant reporting website that was developed as a company tool for managing membership data in the form of company data, labor data, wage data and contribution calculation quickly and accurately. However, the performance of SIPP services online for the number of participants who use SIPP online is relatively smaller or very low than the total number of participating companies registered.This study aims to analyze the factors that influence the acceptance of Surabaya Darmo Branch Employee BPJS Darmo to SIPP online. Respondents in this study are company officers who have not used the online SIPP application registered at Surabaya Darmo Branch BPJS Surabaya as many as 150 using Structural Equation Modeling Partial Least Square (SEM-PLS) analysis.The results showed (1)Individual Perception has a Non Significant effect on Application Use, (2)Individual Perception has a Significantly Positive effect on Usefulness System, (3)Image of Non Significant effect on Usefulness System, (4)Self Capability has a Significant Effect on Ease of Use, (5)Anxiety Effect has a Significant Negative Effect on the Ease of Use,(6)Ease of Use has a Significant Positive Effect on Usefulness System,(7)Ease of Use has a Significant Positive Effect on Application Use, (8)The Usefulness System has a Significant Effect on the Use of the Application, and also an indirect effect is obtained, namely the effect of Individual Perception and Ease of Use on the Use of Applications through the Use of the System. Keywords: SIPP online, Usefulness System, Ease of Use, Use of Applications
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".