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Record W2130269013 · doi:10.5539/ass.v7n10p255

Perceived Usefulness of ICT Usage among JKKK Members in Peninsular Malaysia

2011· article· en· W2130269013 on OpenAlexvenueno aff
Musa Abu Hassan, Bahaman Abu Samah, Hayrol Azril Mohamed Shaffril, Jeffrey Lawrence D’Silva

Bibliographic record

VenueAsian Social Science · 2011
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
FundersUniversiti Putra Malaysia
KeywordsInformation and Communications TechnologyGovernment (linguistics)BusinessVariance (accounting)PsychologyMarketingKnowledge managementComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.040
GPT teacher head0.254
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2011
Admission routes1
Has abstractyes

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