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E-Filing System Practiced by Inland Revenue Board (IRB): Perception towards Malaysian Taxpayers

2010· article· en· W1898925797 on OpenAlexvenueno aff
Zaherawati Zakaria, Zaliha Hj Hussin, Zuriawati Zakaria, Nazni Noordin, Mohd Zool Hilmie Bin Mohamed Sawal, Shahrul Faizah Bt Md Saad, Suhaili Bt Osman Kamil

Bibliographic record

VenueCross-cultural communication · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTaxpayerRevenueBusinessSample (material)Data collectionPerceptionPopulationDescriptive statisticsAccountingActuarial sciencePsychologyPolitical scienceStatisticsMedicineEnvironmental healthLawMathematics

Abstract

fetched live from OpenAlex

This research is about the Perception of Tax Payers toward E-Filing System introduced by Inland Revenue Board in Malaysia. The objective of the study is to determine factors that will lead the taxpayer’s perception toward internet for tax filing system. The factors that lead the tax payers to use internet for tax filing are being identified by four independent variables which are perceive usefulness, perceive risk, perceive ease of use and facilitating conditions. This study was conducted in Sungai Petani, Kedah area. Data were collected from 97 respondents as a sample of this research in Sungai Petani, Kedah. This research used quantitative research method, obtaining data through questionnaires and information from secondary data. The sample was randomly selected from population by using convenience random sampling technique. The data collected were analyzed by using frequency, descriptive statistic, independent sample test and ANOVA. Findings indicated that major factors that lead to the perception of the tax payers toward e-filing system is perceive usefulness of the tax filing system itself. For the future research, this study suggested boosting the positive perception toward e-filing system of the tax payer to give the tax payers more exposure on how to use the e-filing system. Keywords: E-Filing; Inland Revenue Board; Perception; Tax and Taxpayers Resume: Cette recherche est sur la perception des contribuables a l’egard du systeme de depot electronique mis en place par Inland Revenue Board en Malaisie. L'objectif de cette etude est de determiner les facteurs qui meneront la les contribuables a utiliser le systeme de declaration de revenus sur Internet. Les facteurs qui menent les contribuables a utiliser Internet pour les declarations fiscales sont en cours d'identification par quatre independantes variables qui sont la perception de l'utilite, la perception des risques, la simplicite de l’utilisation et la facilitation des conditions. Cette etude a ete menee a Sungai Petani, de la region de Kedah. On a utilise des donnees recueillies aupres de 97 sondes a Sungai Petani, dans la region de Kedah comme un echantillon de cette recherche, qui a utilise la methode de recherche quantitative, en obtenant des donnees par des questionnaires et des informations provenant des donnees secondaires. L'echantillon a ete tire au sort de la population en utilisant la technique pratique d'echantillonnage aleatoire. Les donnees recueillies ont ete analysees en utilisant la frequence, les statistiques descriptives, le teste d'echantillon independant et ANOVA. Les conclusions montrent que les facteurs principaux qui conduisent a la perception des contribuables envers le systeme de depot electronique est la perception de l'utilite du systeme fiscal de depot lui-meme. Pour les recherches a venir, cette etude suggere de renforcer la perception positive des contribuables a l'egard du systeme de depot electronique et leur donner plus d’explication sur la facon d'utiliser le systeme de depot electronique. Mots-cles: depot electronique; Inland Revenue Board; perception; taxes et contribuables

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.035
GPT teacher head0.303
Teacher spread0.268 · 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 teacher head, 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

Citations8
Published2010
Admission routes1
Has abstractyes

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