{"title":"该算法在预测消解设备和办公室机器时的应用","authors":"Isfida Tyas Monowati, Resad Setyadi","doi":"10.47065/josh.v4i2.2674","DOIUrl":null,"url":null,"abstract":"Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency is the implementing element of the regional government in the areas of regional taxes, financial management and assets led by a Head of Agency who is located under and is responsible to the Mayor through the Regional Secretary. Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency. has various types of Kartu Inventaris Barang (KIB) which are still not well managed, namely office equipment and machines, so a decision support system is needed to predict the removal of office equipment and machines. The use of data mining is done to help find out what equipment and machines are still suitable for use or not suitable for use every year in an institution. Data collection that is not careful in managing data can cause the allocation of funds not to be focused on replacing goods that are no longer feasible. Searching for information on datasets can be done with one of the Data Mining methods, namely the Naïve Bayes Algorithm using RapidMiner tools. The data set consists of 24 records with 3 attributes, namely the year of purchase or procurement, materials and conditions. The dataset is processed using the Naive Bayes algorithm and tested using a confusion matrix. An accuracy value of 100% is obtained which is categorized as a good classification.","PeriodicalId":233506,"journal":{"name":"Journal of Information System Research (JOSH)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Penerapan Algoritma Naïve Bayes Dalam Memprediksi Pengusulan Penghapusan Peralatan dan Mesin Kantor\",\"authors\":\"Isfida Tyas Monowati, Resad Setyadi\",\"doi\":\"10.47065/josh.v4i2.2674\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency is the implementing element of the regional government in the areas of regional taxes, financial management and assets led by a Head of Agency who is located under and is responsible to the Mayor through the Regional Secretary. Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency. has various types of Kartu Inventaris Barang (KIB) which are still not well managed, namely office equipment and machines, so a decision support system is needed to predict the removal of office equipment and machines. The use of data mining is done to help find out what equipment and machines are still suitable for use or not suitable for use every year in an institution. Data collection that is not careful in managing data can cause the allocation of funds not to be focused on replacing goods that are no longer feasible. Searching for information on datasets can be done with one of the Data Mining methods, namely the Naïve Bayes Algorithm using RapidMiner tools. The data set consists of 24 records with 3 attributes, namely the year of purchase or procurement, materials and conditions. The dataset is processed using the Naive Bayes algorithm and tested using a confusion matrix. An accuracy value of 100% is obtained which is categorized as a good classification.\",\"PeriodicalId\":233506,\"journal\":{\"name\":\"Journal of Information System Research (JOSH)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Information System Research (JOSH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47065/josh.v4i2.2674\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Information System Research (JOSH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47065/josh.v4i2.2674","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
Banyumas县的Badan Keuangan dan Aset Daerah (BKAD)是区域政府在区域税收、财务管理和资产领域的执行部门,由一名机构负责人领导,该机构负责人位于市长之下,并通过区域秘书向市长负责。Banyumas摄政的Badan Keuangan dan Aset Daerah (BKAD)。有各种类型的Kartu Inventaris Barang (KIB)仍然没有得到很好的管理,即办公设备和机器,因此需要一个决策支持系统来预测办公设备和机器的移除。数据挖掘的使用是为了帮助找出一个机构每年仍然适合使用或不适合使用的设备和机器。如果收集数据时不小心管理数据,可能会导致资金分配不集中在替换不再可行的货物上。搜索数据集的信息可以用数据挖掘方法之一来完成,即使用RapidMiner工具的Naïve贝叶斯算法。数据集由24条记录组成,这些记录有3个属性,分别是购买或采购年份、材料和条件。使用朴素贝叶斯算法处理数据集,并使用混淆矩阵进行测试。得到的准确率值为100%,属于良好的分类。
Penerapan Algoritma Naïve Bayes Dalam Memprediksi Pengusulan Penghapusan Peralatan dan Mesin Kantor
Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency is the implementing element of the regional government in the areas of regional taxes, financial management and assets led by a Head of Agency who is located under and is responsible to the Mayor through the Regional Secretary. Badan Keuangan dan Aset Daerah (BKAD) of Banyumas Regency. has various types of Kartu Inventaris Barang (KIB) which are still not well managed, namely office equipment and machines, so a decision support system is needed to predict the removal of office equipment and machines. The use of data mining is done to help find out what equipment and machines are still suitable for use or not suitable for use every year in an institution. Data collection that is not careful in managing data can cause the allocation of funds not to be focused on replacing goods that are no longer feasible. Searching for information on datasets can be done with one of the Data Mining methods, namely the Naïve Bayes Algorithm using RapidMiner tools. The data set consists of 24 records with 3 attributes, namely the year of purchase or procurement, materials and conditions. The dataset is processed using the Naive Bayes algorithm and tested using a confusion matrix. An accuracy value of 100% is obtained which is categorized as a good classification.