Perak State Government Case Study

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ABSTRACT ‘Sistem Permohonan dan Pemantauan P.02’ Perak State Government is an online system that used by members of state legislative assembly (ADUN), district and land offices, ‘menteri besar’ and executive council (EXCO) in Perak. They use the system to apply budget from the state government for the development and contribution to the people in their respective branches. State Economic Planning Unit of Perak (UPEN) is the one who is responsible to manage the system. The system helps UPEN to know the progress of the projects done by the district office and make it easier to approve the applications of the budget by ADUN and others. Users of the system must actively use the system to keep it updated. However, there are still users who rarely…show more content…
A total of 40 respondents had answered the questionnaire. Out of the 40 respondents, 20 were from district and land offices, 15 from ADUN offices, 3 from EXCO offices and 2 from other offices. Materials The quantitative research methodology was used for this study. The information was gained through a questionnaire that consists of 12 questions. The types of questions used in the questionnaire were ranking question, multiple choices question, yes-no questions and an open ended question. Procedures The questionnaire was made using Microsoft Word and then fax to the respondents. The questionnaire also was mailed and for offices in the Perak Darul Ridzuan Building, the questionnaire was send by hand. They were given two weeks to response to the questionnaire. All the responses were recorded in SPSS software. The methods used were multiple linear regressions and hypothesis testing. Multiple linear regressions Multiple linear regressions analysis is a statistical method used to analyse the relationship between dependent variable and a set of independent variables. The independent variables are the factors that affect the dependent variable. This method could help to examine all factors simultaneously rather than examining every factor separately. The multiple linear regression equation is as

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