The Importance of Arabic Language in Malaysian Tourism Industry: Trends during 1999-2004
Bibliographic record
Abstract
The tourism industry in Malaysia has faced a new trend of Arab tourists’ influx since year 2000. The Arabs spend the highest amount of expenses of RM 5,000.00 per trip. This has given a big benefit for the country’s income. Unfortunately, Malaysia lacks psychological faculties, which is related to the language barriers to cater to Arab needs. The Deputy Tourism Minister has launched a programme to provide Arabic speaking students to serve in five star hotels in the city. This phenomenon clearly indicates a low concern of the tourism industry in providing skilful trainees in the tourism industry in Arabic language and at present there are no Arabic Language courses in tourism programmes to emphasize on the language skills at university level. This paper will try to share the importance of Arabic language skills in tourism industry and tourism program in HLI (Higher Learning Institution). In conclusion, it is hoped that the paper will give some insight to promote courses in Arabic Language Skills for government servants especially the police, customs and others in order to increase their levels of efficiency concerning the language. Key words: Tourism; Arab; Arabic Language; tourists Resume: L'industrie du tourisme en Malaisie a vu des afflux de touristes arabes depuis l’annee 2000. Parmi les touristes etrangers, les Arabes depensent le plus par voyage, soit un montant de 5,000.00 RM. Cela a donne un grand profit aux revenus du pays. Malheureusement, la Malaisie n'a pas de facultes psychologiques, ce qui est liee a la barriere de la langue pour repondre aux besoins des Arabes. Le vice-ministre du Tourisme, a lance un programme visant a fournir aux eleves qui parlent l'arabe une opportunite de travailler dans les hotels a cinq etoiles dans la ville. Ce phenomene indique clairement une faible preoccupation de l'industrie du tourisme dans l’offre des stagiaires competents en langue arabe, et a l'heure actuelle, il n'y pas de cours de langue arabe dans le programme de formation du tourisme, donc il faut mettre l'accent sur les competences linguistiques pour atteindre le niveau universitaire. Ce document va essayer d’etudier l'importance des competences en langue arabe dans l'industrie du tourisme et dans le programme HLI (Higher Learning Institution). En conclusion, il est a esperer que le document donnera une idee de promouvoir des cours de langue arabe pour les fonctionnaires, en particulier la police, les douaniers et d'autres personnels afin d'accroitre leur efficacite liee a cette langue. Mots-Cles: tourisme; Arabe; langue arabe; touristes
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".