Investigating the role of information technology system integration, user acceptance and information technology satisfaction and security on efficiency and accuracy of immigration documents processing
Bibliographic record
Abstract
Technological transformation not only changes the way we communicate and do business but also changes the way the government provides public services to the community. One manifestation of this transformation is the implementation of Information Systems (IS) for public services, to provide services that are more efficient, transparent, and responsive. By implementing an IS, the administration and data management process becomes more efficient. This research method uses a quantitative method approach, The research data are obtained by distributing online questionnaires via the Google Form platform and the respondents for this research were 576 senior employees of the immigration department in Indonesia who were determined using a simple random sampling method. Research data analysis uses structural equation modeling (SEM). The variables in this research are the dependent variables, namely information Technology System integration and Information Technology System Security (ITSS). The dependent variable is the Efficiency and Accuracy of Immigration Documents (EAID) and User Acceptance and Satisfaction (UAS). Based on data analysis, it is concluded that TSS integration had a positive and significant relationship with EAID, Information technology system integration had a positive and significant relationship with UAS, ITSS had a positive and significant relationship with EAID, ITSS had a positive and significant relationship with UAS and user acceptance and satisfaction had a positive and substantial relationship with the EAID. Implementing IS opens the door to more efficient, transparent, and responsive public services. By leveraging technology, governments can streamline administrative processes, increase citizen participation, and create an environment where every citizen can benefit from better public services. In carrying out this transformation, the government must remain focused on data security, privacy, and community empowerment so that people truly feel the positive impact of technological developments in public services.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".