Home           Contact us           FAQs           
 
   Journal Page   |   Aims & Scope   |   Author Guideline   |   Editorial Board   |   Search
    Abstract
2013 (Vol. 5, Issue: 05)
Article Information:

The Development of Predictive Model for Waste Generation Rates in Malaysia

Zaini Sakawi and Simon Gerrard
Corresponding Author:  Zaini Sakawi 

Key words:  Linear regression analysis, Malaysia, predictive modeling, SPSS, waste generation rate, waste management,
Vol. 5 , (05): 1774-1780
Submitted Accepted Published
July 31, 2012 September 03, 2012 February 11, 2013
Abstract:

The purpose of this study is to describe the empirical method (statistical method) used to test the predictive model, which was developed for the survey on waste generation. The model used different types of houses such as Bungalow (), Double Terrace (DT), Low Cost (LC), Flats (FL) and Village Type (VL) as variables. Using the predictive model, a comparison was made against actual data obtained from local authorities and data obtained from estimates manually calculated by the Ministry of Housing and Local Government. This comparison was to establish the accuracy of the prediction and the variation between the waste collected monthly and the predicted value of waste generated. The finding showed that the difference between actual amount of waste collected and the predicted amount was approximately 27%. The explanation from linear regression analysis showed that the quantity of waste generation using predictive model explains 63% of the variables selected for the regression gave good indicators for the analysis of waste generation rates in the study area.
Abstract PDF HTML
  Cite this Reference:
Zaini Sakawi and Simon Gerrard, 2013. The Development of Predictive Model for Waste Generation Rates in Malaysia.  Research Journal of Applied Sciences, Engineering and Technology, 5(05): 1774-1780.
    Advertise with us
 
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Current Information
   Sales & Services
   Contact Information
  Executive Managing Editor
  Email: admin@maxwellsci.com
  Publishing Editor
  Email: support@maxwellsci.com
  Account Manager
  Email: faisalm@maxwellsci.com
  Journal Editor
  Email: admin@maxwellsci.com
  Press Department
  Email: press@maxwellsci.com
Home  |  Contact us  |  About us  |  Privacy Policy
Copyright © 2009. MAXWELL Science Publication, a division of MAXWELLl Scientific Organization. All rights reserved