Quality prediction model has been developed in various industries to realize the faultless manufacturing. However, most of quality prediction model is developed in single-stage manufacturing. Previous studies show that single-stage quality system cannot solve quality problem in multi-stage manufacturing effectively. This study is intended to propose combination of multiple PCA+ID3 algorithm to develop quality prediction model in MMS. This technique is applied to a semiconductor manufacturing dataset using the cascade prediction approach. The result shows that the combination of multiple PCA+ID3 is manage to produce the more accurate prediction model in term of classifying both positive and negative classes. General TermsData Mining, Prediction Model.

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Small and medium-scale industries (SMI) have played a very important role in Malaysian economy. Particularly in terms of employment generation, better income distribution and as a training ground for entrepreneurs before investing in a larger scale businesses. However, there are many factors inhibiting the adoption of new technologies especially related to Information and Communication Technology (ICT) in the challenging world today. It is important to identify the primary obstacles they face with regard in adopting new technology. In order for them to survive in a long run, this study identifies problems and constraints faced by SMI inMalaysia. Then, focus on the challenges and barriers for them in adopting new technology. The researchers visited few foodprocessing SMI in the Southern Region of Malaysia and make comparison with few important publications on SMI development.

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