{"title":"白古鲁市立法选举的样本测定和快速计数模拟","authors":"A. Gumilar, Sigit Nugroho, Buyung Keraman","doi":"10.33369/jsds.v1i1.21012","DOIUrl":null,"url":null,"abstract":"In this research illustrates the simulation of quick count of sampling for the year 2014 Legislative Election in Bengkulu City, which has a data acquisition result for 589 TPS. The problem in this research is how to know the sample size and the right sampling method for Legislative Election in Bengkulu City on Year 2014. The purpose of this research is to know the sample size and the quick count calculation sampling method that can predict the actual vote result for Legislative Election. The method used in the calculation of fast calculation consists of three methods, simple random sampling, cluster random sampling and multistage random sampling. From the population data of 589 polling stations (TPS) into the population, the sample size was taken as much as 120 TPS or about 20% of the population, based on the results of calculations for sample sizes in a limited population. After the sample was selected, a sample simulation of 100 times for each method and simulation results was tested for compatibility with the chi-squared test. Based on the test results, it can be concluded that for sample size 120 TPS taken by simple random sampling method, cluster random sampling or multistage random sampling can predict the actual vote result in Legislative Election Year 2014 in Bengkulu with margin of error 5%. For efficiency consideration simple random sampling method can be selected.","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simulation of Sample Determination Quick Count Legislative Elections In Bengkulu City\",\"authors\":\"A. Gumilar, Sigit Nugroho, Buyung Keraman\",\"doi\":\"10.33369/jsds.v1i1.21012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this research illustrates the simulation of quick count of sampling for the year 2014 Legislative Election in Bengkulu City, which has a data acquisition result for 589 TPS. The problem in this research is how to know the sample size and the right sampling method for Legislative Election in Bengkulu City on Year 2014. The purpose of this research is to know the sample size and the quick count calculation sampling method that can predict the actual vote result for Legislative Election. The method used in the calculation of fast calculation consists of three methods, simple random sampling, cluster random sampling and multistage random sampling. From the population data of 589 polling stations (TPS) into the population, the sample size was taken as much as 120 TPS or about 20% of the population, based on the results of calculations for sample sizes in a limited population. After the sample was selected, a sample simulation of 100 times for each method and simulation results was tested for compatibility with the chi-squared test. Based on the test results, it can be concluded that for sample size 120 TPS taken by simple random sampling method, cluster random sampling or multistage random sampling can predict the actual vote result in Legislative Election Year 2014 in Bengkulu with margin of error 5%. For efficiency consideration simple random sampling method can be selected.\",\"PeriodicalId\":29911,\"journal\":{\"name\":\"Japanese Journal of Statistics and Data Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2022-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Japanese Journal of Statistics and Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33369/jsds.v1i1.21012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Japanese Journal of Statistics and Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33369/jsds.v1i1.21012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Simulation of Sample Determination Quick Count Legislative Elections In Bengkulu City
In this research illustrates the simulation of quick count of sampling for the year 2014 Legislative Election in Bengkulu City, which has a data acquisition result for 589 TPS. The problem in this research is how to know the sample size and the right sampling method for Legislative Election in Bengkulu City on Year 2014. The purpose of this research is to know the sample size and the quick count calculation sampling method that can predict the actual vote result for Legislative Election. The method used in the calculation of fast calculation consists of three methods, simple random sampling, cluster random sampling and multistage random sampling. From the population data of 589 polling stations (TPS) into the population, the sample size was taken as much as 120 TPS or about 20% of the population, based on the results of calculations for sample sizes in a limited population. After the sample was selected, a sample simulation of 100 times for each method and simulation results was tested for compatibility with the chi-squared test. Based on the test results, it can be concluded that for sample size 120 TPS taken by simple random sampling method, cluster random sampling or multistage random sampling can predict the actual vote result in Legislative Election Year 2014 in Bengkulu with margin of error 5%. For efficiency consideration simple random sampling method can be selected.