The Suburbanisation of the Kuala Lumpur Metropolitan Region

Abdullah, Jamalunlaili

doi:10.21837/pmjournal.v1.i1.38

Cited by 8 publications

(11 citation statements)

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“…Most of the interviewees hardly able to brief (even rough estimation) agreeable percentages; except that citing zakat's amount (2.5% from the prescribed zakat formula3 F § ) as their bases. Likewise, zakat is only imposed to the shareholders' fund since the paid-up capital provided by them, if there is surplus (Abdullah et al 2012). A simple comparison between takaful operators and conventional insurers will signify that in term of contribution to the nation in forms of taxes -takaful operator contributes more due to zakat payment (pseudo religious tax) and corporate tax compared to conventional insurers, albeit in term of amount the latter might contribute more.…”

Section: Findings1 F †mentioning

confidence: 99%

Takaful Operators’ Corporate Social Performance (CSP): An Industry Perspective

2017

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Takaful operators which are part of Islamic financial institutions (IFIs) derive their fundamental principles from shariah. These religious based institutions are expected to fulfill the two important roles in their business operations: commercially profitable and socially responsible. Nevertheless, their societal role is rarely measured and discussed. Therefore, this study appraised the societal role of takaful operators by assessing the components which have been proposed under the corporate social performance (CSP) theme for IFIs. This study has arranged structured interview sessions with the Chief Investment Officers and Heads of Investment of each of the eleven takaful operators in Malaysia. The Delphi-style technique was adopted when developing the interview questions. The questions were developed in the form of a five-point Likert scale, addressing specific issues on CSP of takaful operators. In addition, information on takaful operators' CSR activities, zakat and tax payment were gathered from the companies' websites and annual report of takaful operators. The study concludes that takaful operators in Malaysia have achieved their societal role through two channels: CSP programmes financed from companies' profits and fulfillment of CSP as a result of business-community agenda. This study covers every takaful operator in Malaysia and the results reflect industry opinion.

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Section: Findings1 F †mentioning

confidence: 99%

Takaful Operators’ Corporate Social Performance (CSP): An Industry Perspective

2017

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“…In Malaysia, studies on the issues of urban growth and land use, sustainable urban development, urban planning and conservation had long used traditional regression approach (e.g. Abdullah, 2003;Jaafar, 2004;Rainis & Noresah, 2004;Tahir & Roe, 2006;Samat, 2007;Lee, Lim, & Nor'Aini, 2008;Osman et al, 2008;Tan, Lim, MatJafri, & Abdullah 2009). On the other hand, studies which used GWR include modelling urban spatial structure Noresah and Rainis, (2009), analyzing land use change (Noresah, Gairola, & Talib, 2010), assessing the rental value of shop houses (Eboy, Ibrahim, & Buang, 2006) and examining the locational attributes effect on residential property values (Dziauddin & Idris, 2017).…”

Section: Problem Statementmentioning

confidence: 99%

“…Malaysia is experiencing rapid urbanization resulting from population increase and in-migration to urban areas (Abdullah, 2003). Recent projections indicated that the urbanization process in Malaysia would result in urban population exceeding 65 percent by the year 2020 (Government of Malaysia, 2010).…”

Section: Introductionmentioning

confidence: 99%

Geographically Weighted Regression Model: A Potential Approach For Better Management Of Urban Growth

Shariff¹

2020

European Proceedings of Social and Behavioural Sciences

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“…Another example is a parallel language corpus as a resource for Malay language reported by [2] and a basic tokenizer tool for Jawi writing reported by [3]. The Malay language is categorised as an agglutinative or derivative language where most of the words are formed by merging affixes with root words [4][5]. Affixation is performed by adding the affix at the beginning (prefixes), middle (infixes) or at both the ends (circumfixes) of the root word.…”

Section: Introductionmentioning

confidence: 99%

Penalizing unknown words’ emissions in hmm pos tagger based on Malay affix morphemes

Mohamed¹,

Omar

Aziz

2018

J. Fundam and Appl Sci.

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The challenge in unsupervised Hidden Markov Model (HMM) training for a POS tagger is that the training depends on an untagged corpus; the only supervised data limiting possible tagging of words is a dictionary. Therefore, training cannot properly map possible tags. The exact morphemes of prefixes, suffixes and circumfixes in the agglutinative Malay language is examined to assign unknown words' probable tags based on linguistically meaningful affixes using a morpheme-based POS guessing algorithm for tagging. The algorithm has been integrated into Viterbi algorithm which uses HMM trained parameters for tagging new sentences. In the experiment, this tagger is first, uses character-based prediction to handle unknown words; next, uses morpheme-based POS guessing algorithm; lastly, combination of the first and second. Keywords PENALIZING UNKNOWN WORDS' EMISSIONS IN HMM POS TAGGER BASED ON MALAY AFFIX MORPHEMES ABSTRACTThe challenge in unsupervised Hidden Markov Model (HMM) training for a POS tagger is that the training depends on an untagged corpus; the only supervised data limiting possible tagging of words is a dictionary. Therefore, training cannot properly map possible tags. The exact morphemes of prefixes, suffixes and circumfixes in the agglutinative Malay language is examined to assign unknown words' probable tags based on linguistically meaningful affixes using a morpheme-based POS guessing algorithm for tagging. The algorithm has been integrated into Viterbi algorithm which uses HMM trained parameters for tagging new sentences. In the experiment, this tagger is first, uses character-based prediction to handle unknown words; next, uses morpheme-based POS guessing algorithm; lastly, combination of the first and second. PENALIZING UNKNOWN WORDS' EMISSIONS IN HMM POS TAGGER BASED ON MALAY AFFIX MORPHEMES ABSTRACTThe challenge in unsupervised Hidden Markov Model (HMM) training for a POS tagger is that the training depends on an untagged corpus; the only supervised data limiting possible tagging of words is a dictionary. Therefore, training cannot properly map possible tags. The exact morphemes of prefixes, suffixes and circumfixes in the agglutinative Malay language is examined to assign unknown words' probable tags based on linguistically meaningful affixes using a morpheme-based POS guessing algorithm for tagging. The algorithm has been integrated into Viterbi algorithm which uses HMM trained parameters for tagging new sentences. In the experiment, this tagger is first, uses character-based prediction to handle unknown words; next, uses morpheme-based POS guessing algorithm; lastly, combination of the first and second.

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The Suburbanisation of the Kuala Lumpur Metropolitan Region

Cited by 8 publications

References 0 publications

Takaful Operators’ Corporate Social Performance (CSP): An Industry Perspective

Takaful Operators’ Corporate Social Performance (CSP): An Industry Perspective

Geographically Weighted Regression Model: A Potential Approach For Better Management Of Urban Growth

Penalizing unknown words’ emissions in hmm pos tagger based on Malay affix morphemes

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