{"title":"模式发现与关联分析识别易感染HIV/AIDS的顾客:以Marie Stopes Gonder分院为例","authors":"Fistume Tamene, Fediu Akmel, E. Birhanu, B. Siraj","doi":"10.9790/0661-1904020107","DOIUrl":null,"url":null,"abstract":"In the 30 years since HIV/AIDS was first discovered, the disease has become a disturbing pandemic, taking the lives of 30 million people around the world. In 2010 alone, HIV/AIDS killed 1.8 million people, 1.2 million of whom were living in sub-Saharan Africa. In Ethiopia,HIV/AIDS is one of the key challenges for the overall development of Ethiopia, as it has led to a seven-year decrease in life expectancy and a greatly reduced workforce. Even if there are a number of voluntarily counseling and testing centers that work on HIV/AIDS prevention located in several cities of the country, they didn’t change and solve the problem related with HIV/AIDS. In addition in most of Countries counseling and Testing centers ,the data collected is simply put together and maximum used for statics purpose rather than analyzing to discover relevant and interesting previously unknown data characteristics,relationships,dependencies etc . The main objective of this study was pattern discovery and generating interesting hidden association rules from data which is taken from Marie stopes Gondar branch clinic. The contribution of this Study is by analyzing customer’s data that did HIV/AIDS test on the clinic, to identify which customer is more vulnerable to HIV/AIDS. It helps counselors in VCT centers in predicting some hidden but interesting relationships among the attributes they use during the course of counseling. For doing this, methodology such as data collection and tool selection was used. After data was collected, the main data preprocessing tasks are applied on data sets to clean data and to make it ready for experiment purpose. Out of 1992 instances of original data 1861 was made ready for the experiment. Weka3.4. tool is used for experiment and the well known association rule mining algorithm Apriori was used to extract those interesting rules from data. In order to get those interesting rules three basic experiment was conducted .Experiment I was conducted by using the whole data set. Experiment II was conducted by considering only those positive classes. Experiment III was done by only considering those positive classes but with the absence of positive class attribute. One of the result of experiments showed that customers that donot use condom during sexual intercourse and non employed person are vulnerable to HIV/AIDS.","PeriodicalId":91890,"journal":{"name":"IOSR journal of computer engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Pattern Discovery and Association Analysis To Identify Customer Vulnerable To HIV/AIDS: Case of Marie Stopes Gonder Branch Clinic\",\"authors\":\"Fistume Tamene, Fediu Akmel, E. Birhanu, B. Siraj\",\"doi\":\"10.9790/0661-1904020107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the 30 years since HIV/AIDS was first discovered, the disease has become a disturbing pandemic, taking the lives of 30 million people around the world. In 2010 alone, HIV/AIDS killed 1.8 million people, 1.2 million of whom were living in sub-Saharan Africa. In Ethiopia,HIV/AIDS is one of the key challenges for the overall development of Ethiopia, as it has led to a seven-year decrease in life expectancy and a greatly reduced workforce. Even if there are a number of voluntarily counseling and testing centers that work on HIV/AIDS prevention located in several cities of the country, they didn’t change and solve the problem related with HIV/AIDS. In addition in most of Countries counseling and Testing centers ,the data collected is simply put together and maximum used for statics purpose rather than analyzing to discover relevant and interesting previously unknown data characteristics,relationships,dependencies etc . The main objective of this study was pattern discovery and generating interesting hidden association rules from data which is taken from Marie stopes Gondar branch clinic. The contribution of this Study is by analyzing customer’s data that did HIV/AIDS test on the clinic, to identify which customer is more vulnerable to HIV/AIDS. It helps counselors in VCT centers in predicting some hidden but interesting relationships among the attributes they use during the course of counseling. For doing this, methodology such as data collection and tool selection was used. After data was collected, the main data preprocessing tasks are applied on data sets to clean data and to make it ready for experiment purpose. Out of 1992 instances of original data 1861 was made ready for the experiment. Weka3.4. tool is used for experiment and the well known association rule mining algorithm Apriori was used to extract those interesting rules from data. In order to get those interesting rules three basic experiment was conducted .Experiment I was conducted by using the whole data set. Experiment II was conducted by considering only those positive classes. Experiment III was done by only considering those positive classes but with the absence of positive class attribute. One of the result of experiments showed that customers that donot use condom during sexual intercourse and non employed person are vulnerable to HIV/AIDS.\",\"PeriodicalId\":91890,\"journal\":{\"name\":\"IOSR journal of computer engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IOSR journal of computer engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9790/0661-1904020107\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IOSR journal of computer engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9790/0661-1904020107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pattern Discovery and Association Analysis To Identify Customer Vulnerable To HIV/AIDS: Case of Marie Stopes Gonder Branch Clinic
In the 30 years since HIV/AIDS was first discovered, the disease has become a disturbing pandemic, taking the lives of 30 million people around the world. In 2010 alone, HIV/AIDS killed 1.8 million people, 1.2 million of whom were living in sub-Saharan Africa. In Ethiopia,HIV/AIDS is one of the key challenges for the overall development of Ethiopia, as it has led to a seven-year decrease in life expectancy and a greatly reduced workforce. Even if there are a number of voluntarily counseling and testing centers that work on HIV/AIDS prevention located in several cities of the country, they didn’t change and solve the problem related with HIV/AIDS. In addition in most of Countries counseling and Testing centers ,the data collected is simply put together and maximum used for statics purpose rather than analyzing to discover relevant and interesting previously unknown data characteristics,relationships,dependencies etc . The main objective of this study was pattern discovery and generating interesting hidden association rules from data which is taken from Marie stopes Gondar branch clinic. The contribution of this Study is by analyzing customer’s data that did HIV/AIDS test on the clinic, to identify which customer is more vulnerable to HIV/AIDS. It helps counselors in VCT centers in predicting some hidden but interesting relationships among the attributes they use during the course of counseling. For doing this, methodology such as data collection and tool selection was used. After data was collected, the main data preprocessing tasks are applied on data sets to clean data and to make it ready for experiment purpose. Out of 1992 instances of original data 1861 was made ready for the experiment. Weka3.4. tool is used for experiment and the well known association rule mining algorithm Apriori was used to extract those interesting rules from data. In order to get those interesting rules three basic experiment was conducted .Experiment I was conducted by using the whole data set. Experiment II was conducted by considering only those positive classes. Experiment III was done by only considering those positive classes but with the absence of positive class attribute. One of the result of experiments showed that customers that donot use condom during sexual intercourse and non employed person are vulnerable to HIV/AIDS.