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A Method of Discovering Interesting Association Rules from Student Admission Dataset
Wiwik Novitasari,Arief Hermawan,Zailani Abdullah,Rahmat Widia Sembiring,Tutut Herawan 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.8
For the past decades and until now, association rule mining is one of the most prominent research topics in data mining. However, the main challenge among public or private practitioners is to find the interesting rule from data repository. As a result, many efforts have been put forward to explore this rule by applying several methods and interesting measures. Therefore, in this paper, we introduced an enhanced association rule mining method namely Significant Least Pattern Growth (SLP-Growth), where the algorithm embeds with two interesting measures called Critical Relative Support (CRS) and Correlation (Corr). The experiment uses the dataset that contains the records of preferred programs being selected by post-matriculation or post-STPM students of Malaysia via Electronic Management of Admission System (e-MAS) for the year 2008/2009. The experimental results show that the SLP-Algorithm with the embedded measures can successfully in categorizing the association rules. In addition, this information can be used by educators and higher university authority personnel in the university to understand the programs’ patterns being selected by the students. More importantly, it can assist them as a basis to offer more relevant programs to the potential students rather than by chance technique.
Distribution of HPV Genotypes in Cervical Cancer in Multiethnic Malaysia
Raub, Sayyidi Hamzi Abdul,Isa, Nurismah Md.,Zailani, Hatta Ahmad,Omar, Baharudin,Abdullah, Mohamad Farouk,Amin, Wan Anna Mohd,Noor, Rushdan Md.,Ayub, Mukarramah Che,Abidin, Zainal,Kassim, Fauziah,Vick Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.2
Background: Cervical cancer is the third commonest type of cancer among women in Malaysia. Our aim was to determine the distribution of human papilloma virus (HPV) genotypes in cervical cancer in our multi-ethnic population. Materials and Methods: This was a multicentre study with a total of 280 cases of cervical cancer from 4 referral centres in Malaysia, studied using real-time polymerase chain reaction (qPCR) detection of 12 high risk-HPV genotypes. Results: Overall HPV was detected in 92.5% of cases, in 95.9% of squamous cell carcinomas and 84.3%of adenocarcinomas. The five most prevalent high-risk HPV genotypes were HPV 16 (68.2%), 18 (40%), 58 (10.7%), 33 (10.4%) and 52 (10.4%). Multiple HPV infections were more prevalent (55.7%) than single HPV infections (36.8%). The percentage of HPV positive cases in Chinese, Malays and Indians were 95.5%, 91.9% and 80.0%, respectively. HPV 16 and 18 genotypes were the commonest in all ethnic groups. We found that the percentage of HPV 16 infection was significantly higher in Chinese (75.9%) compared to Malays (63.7%) and Indians (52.0%) (p<0.05), while HPV 18 was significantly higher in Malays (52.6%) compared to Chinese (25.0%) and Indians (28%) (p<0.05). Meanwhile, HPV 33 (17.9%) and 52 (15.2%) were also more commonly detected in the Chinese (p<0.05). Conclusions: This study showed that the distribution of HPV genotype in Malaysia is similar to other Asian countries. Importantly, we found that different ethnic groups in Malaysia have different HPV genotype infection rates, which is a point to consider during the implementation of HPV vaccination.