Perceived Usefulness of ICT Usage among JKKK Members in Peninsular Malaysia
Bibliographic record
Abstract
Information and communication technology (ICT) is indeed an important tool to expose the rural community to development. Realizing the importance of ICT, a number of high impact ICT programs and projects have been introduced by the government. However, do the rural community especially their leaders which are the Village Development and Security Committee members (JKKK) use ICT? And more importantly do they perceive ICT as useful in their daily activities and tasks? This question brings us to the main objective of this paper which is to know the factors that influence the perceived usefulness towards ICT usage among the JKKK members in Peninsular Malaysia. Besides, this paper intends to investigate the level of perceived usefulness towards ICT usage among JKKK members and to reveal the most significant contributors for perceived usefulness towards ICT usage. This is a quantitative study whereby data were gathered using a questionnaire. Based on the multi stage random sampling, a total of 240 JKKK members have been selected as the respondents. Based on the analyses done, it can be concluded that respondents studied do have a high level of perceived usefulness towards ICT usage. All of the four factors studied have a positive and significant relationship towards ICT usage. Attitude was identified as the most significant contributor for perceived usefulness towards ICT usage while the four predictor variables explain about 60.0% of the variance/variation in perceived usefulness towards ICT usage.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".