{"title":"基于药品总库存和总需求的k -均值聚类方法在Pajar Bulan卫生中心的药物数据聚类","authors":"Robi Saputra, L. Yulianti, Lena Elfianty","doi":"10.53697/jkomitek.v2i1.784","DOIUrl":null,"url":null,"abstract":"At Pajar Bulan Health Center, drug supply data processing is already using office application packages, namely Microsoft Word and Excel. The application package is used for making monthly usage reports, requests and drug supplies. Constraints that often occur are that it takes a long time to manage drug inventory data because they have to record one by one the amount of drug use and the number of drug requests to be made. The number of requests is carried out every month by looking at the latest drug supply, if the stock starts to run low then a request is made. However, it is possible that the stock has run out before making a request, this results in a lack of drug supply management. Drug data clustering is carried out based on the amount of supply and the number of requests for drugs at the Pajar Bulan Health Center through the K-Means Clustering Method approach. To help cluster the drug data, an application was built using the Visual Basic .Net programming language and SQL Server 2008r2 database. Clustering of drug data is carried out in units of pcs in 2021 where the amount of inventory is reduced by the number of requests for drugs, so that the results obtained are 2 drugs enter cluster I and 27 drugs enter cluster II. good and the application can help the Pajar Bulan Health Center in knowing the grouping of drug data based on 2 groups, namely the few clusters and the large clusters","PeriodicalId":371693,"journal":{"name":"Jurnal Komputer, Informasi dan Teknologi (JKOMITEK)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Drug Data Clustering Based on Total Inventory and Total Demand for Drugs Using the K-means Clustering Method at Pajar Bulan Health Center\",\"authors\":\"Robi Saputra, L. Yulianti, Lena Elfianty\",\"doi\":\"10.53697/jkomitek.v2i1.784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At Pajar Bulan Health Center, drug supply data processing is already using office application packages, namely Microsoft Word and Excel. The application package is used for making monthly usage reports, requests and drug supplies. Constraints that often occur are that it takes a long time to manage drug inventory data because they have to record one by one the amount of drug use and the number of drug requests to be made. The number of requests is carried out every month by looking at the latest drug supply, if the stock starts to run low then a request is made. However, it is possible that the stock has run out before making a request, this results in a lack of drug supply management. Drug data clustering is carried out based on the amount of supply and the number of requests for drugs at the Pajar Bulan Health Center through the K-Means Clustering Method approach. To help cluster the drug data, an application was built using the Visual Basic .Net programming language and SQL Server 2008r2 database. Clustering of drug data is carried out in units of pcs in 2021 where the amount of inventory is reduced by the number of requests for drugs, so that the results obtained are 2 drugs enter cluster I and 27 drugs enter cluster II. good and the application can help the Pajar Bulan Health Center in knowing the grouping of drug data based on 2 groups, namely the few clusters and the large clusters\",\"PeriodicalId\":371693,\"journal\":{\"name\":\"Jurnal Komputer, Informasi dan Teknologi (JKOMITEK)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Komputer, Informasi dan Teknologi (JKOMITEK)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53697/jkomitek.v2i1.784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Komputer, Informasi dan Teknologi (JKOMITEK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53697/jkomitek.v2i1.784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
在Pajar Bulan卫生中心,药品供应数据处理已经使用office应用程序包,即微软的Word和Excel。应用程序包用于制作每月使用报告,请求和药物供应。经常出现的制约因素是,管理药品库存数据需要很长时间,因为他们必须逐一记录药品使用量和药品申请数量。请求的数量是每个月通过查看最新的药品供应来执行的,如果库存开始减少,那么就会提出请求。然而,有可能在提出要求之前库存已用完,这导致缺乏药品供应管理。通过k -均值聚类方法,根据Pajar Bulan保健中心的药品供应数量和请求数量进行药物数据聚类。为了实现药物数据的聚类,使用Visual Basic . net编程语言和SQL Server 2008r2数据库构建了一个应用程序。2021年以pcs为单位对药品数据进行聚类,存货量按药品申请量减少,结果为2种药品进入聚类I, 27种药品进入聚类II。该应用程序可以帮助Pajar Bulan Health Center了解基于2组的药物数据分组,即小簇和大簇
Drug Data Clustering Based on Total Inventory and Total Demand for Drugs Using the K-means Clustering Method at Pajar Bulan Health Center
At Pajar Bulan Health Center, drug supply data processing is already using office application packages, namely Microsoft Word and Excel. The application package is used for making monthly usage reports, requests and drug supplies. Constraints that often occur are that it takes a long time to manage drug inventory data because they have to record one by one the amount of drug use and the number of drug requests to be made. The number of requests is carried out every month by looking at the latest drug supply, if the stock starts to run low then a request is made. However, it is possible that the stock has run out before making a request, this results in a lack of drug supply management. Drug data clustering is carried out based on the amount of supply and the number of requests for drugs at the Pajar Bulan Health Center through the K-Means Clustering Method approach. To help cluster the drug data, an application was built using the Visual Basic .Net programming language and SQL Server 2008r2 database. Clustering of drug data is carried out in units of pcs in 2021 where the amount of inventory is reduced by the number of requests for drugs, so that the results obtained are 2 drugs enter cluster I and 27 drugs enter cluster II. good and the application can help the Pajar Bulan Health Center in knowing the grouping of drug data based on 2 groups, namely the few clusters and the large clusters