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     Research Journal of Applied Sciences, Engineering and Technology


The Development of Predictive Model for Waste Generation Rates in Malaysia

1Zaini Sakawi and 2Simon Gerrard
1Earth Observation Centre, FSSK, Universiti Kebangsaan, Malaysia
2Department of Environmental Sciences, University of East Anglia, Norwich, UK
Research Journal of Applied Sciences, Engineering and Technology  2013  5:1774-1780
http://dx.doi.org/10.19026/rjaset.5.4937  |  © The Author(s) 2013
Received: July 31, 2012  |  Accepted: September 03, 2012  |  Published: 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.

Keywords:

Linear regression analysis, Malaysia, predictive modeling, SPSS, waste generation rate, waste management,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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