Rice is a staple food for Malaysian. Malaysian paddy farmers contributed up to 70% of the country’s needs. However, climate change impact to the agriculture activities. The aim of this study is to forecast the paddy production for four years in Kedah, Malaysia. Naïve forecasting method was used in this study. The forecasted results for the paddy production values from 2013 to 2016 are considered in this study. The finding shows that the decrease of paddy production in the year of 2013 but the paddy production increased from year 2014 until 2016. Overall, this research work forecasted gradual increments for the projection of four years rice’s production in Kedah.
A confidence interval is an interval estimate of a parameter of a population calculated from a sample drawn from the population. Bootstrapping method, which involves producing several new data sets that are resampled from the original data in order to estimate parameter for each newly created data set, allowing an empirical distribution for the parameter to be estimated. Since certain statistics are harder to estimate, confidence intervals are rarely employed. Several statistics might necessitate multi-step formulas assuming that are impractical for calculating confidence intervals. This paper reviews research on the concept of bootstrapping and bootstrap confidence interval. The current narrative analysis was developed to answer the main research question: (1) What is the concept of the bootstrap method and bootstrap confidence interval? (2) What are the methods of bootstrapping to obtain confidence interval? This study has found general bootstrap method idea, various techniques of bootstrap methods, its advantages and disadvantages, and its limitations. There are normal interval method, percentile bootstrap method, basic method, first-order normal approximation method, bias-corrected bootstrap, accelerated bias-corrected bootstrap and bootstrap-t method. This study concludes that the advantages of using bootstrap CI is that it does not require any assumptions about the shape of distribution and universality of the approach. Bootstrapping is a computer-intensive statistical technique that relies significantly on modern high-speed digital computers to do massive computations.
Shopee is one of the prominent online shopping platforms in Malaysia. Nonetheless, countless scam cases were reported on the platform, particularly on money fraudulent activities. This study constructed a quantitative model through linear programming that assessed sentiments based on customers’ reviews. Reviews from three selected Shopee products (‘M3 Smart Health Watch’, ‘Sony Headset Wired Gaming Headphone’, and ‘20000mAh Pineng 100% Original Powerbank’) were analysed using the proposed model. The data were converted into measurable metrics to enable quantitative fraud detection. The model enabled the early detection of possible money fraudulent activities on Shopee products based on customers’ reviews. Resultantly, ‘M3 Smart Health Watch’ is an authentic Shopee product. In contrast, ‘Sony Headset Wired Gaming Headphone’ and ‘20000mAh Pineng 100% Original Powerbank’ are money fraud products sold by scammers. The proposed model utilises free and readily available software, thus extending its usability to other small business owners.
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