{"title":"设计一种商业情报系统,使用数据挖掘方法和立方体分析面包店产品的市场","authors":"Rina Fitriana, J. Saragih, Besty Afrah Hasyati","doi":"10.24961/J.TEK.IND.PERT.2018.28.1.113","DOIUrl":null,"url":null,"abstract":"Business intelligence systems participate to deliveran accurate and useful information to decision makers in marketing division of bakeries manufacture . The purpose of this study was to design business intelligence model to analyze the marketing product, de sign the data mining model, measure and analyze the marketing process of the product they sell . The methodology of this research was to analyze system requirements, design unified mod eling language, make process extract, transform, and load, design data warehouse, and data mining that integrate d with the o n l ine a nalytical p rocess cube webbased . The business intelligence model produced was a marketing data mining model and o n l ine a nalytical p rocess cube. The result from on line analytical process cube was the data warehouse of transaction in R Bakery. In designing the data mining, K-means clustering method was used. The results from data mining k-means clustering were there were 83% cluster 1 and 17% cluster 2. Cluster 1 wasthecategorize for low leftover breads and cluster 2 was the categorize for high leftover breads. The model cub e recency, frequency, and monetary and customer lifetime value resulted rank ed out of the most amount of sales in R Bakery. Keywords: business intelligence system, data mining, extract transform load, on line analitical process cube","PeriodicalId":14920,"journal":{"name":"Journal of Agroindustrial Technology","volume":"8 1","pages":"113-126"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"PERANCANGAN MODEL SISTEM INTELIJENSIA BISNIS UNTUK MENGANALISIS PEMASARAN PRODUK ROTI DI PABRIK ROTI MENGGUNAKAN METODE DATA MINING DAN CUBE\",\"authors\":\"Rina Fitriana, J. Saragih, Besty Afrah Hasyati\",\"doi\":\"10.24961/J.TEK.IND.PERT.2018.28.1.113\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Business intelligence systems participate to deliveran accurate and useful information to decision makers in marketing division of bakeries manufacture . The purpose of this study was to design business intelligence model to analyze the marketing product, de sign the data mining model, measure and analyze the marketing process of the product they sell . The methodology of this research was to analyze system requirements, design unified mod eling language, make process extract, transform, and load, design data warehouse, and data mining that integrate d with the o n l ine a nalytical p rocess cube webbased . The business intelligence model produced was a marketing data mining model and o n l ine a nalytical p rocess cube. The result from on line analytical process cube was the data warehouse of transaction in R Bakery. In designing the data mining, K-means clustering method was used. The results from data mining k-means clustering were there were 83% cluster 1 and 17% cluster 2. Cluster 1 wasthecategorize for low leftover breads and cluster 2 was the categorize for high leftover breads. The model cub e recency, frequency, and monetary and customer lifetime value resulted rank ed out of the most amount of sales in R Bakery. Keywords: business intelligence system, data mining, extract transform load, on line analitical process cube\",\"PeriodicalId\":14920,\"journal\":{\"name\":\"Journal of Agroindustrial Technology\",\"volume\":\"8 1\",\"pages\":\"113-126\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Agroindustrial Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24961/J.TEK.IND.PERT.2018.28.1.113\",\"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 Agroindustrial Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24961/J.TEK.IND.PERT.2018.28.1.113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PERANCANGAN MODEL SISTEM INTELIJENSIA BISNIS UNTUK MENGANALISIS PEMASARAN PRODUK ROTI DI PABRIK ROTI MENGGUNAKAN METODE DATA MINING DAN CUBE
Business intelligence systems participate to deliveran accurate and useful information to decision makers in marketing division of bakeries manufacture . The purpose of this study was to design business intelligence model to analyze the marketing product, de sign the data mining model, measure and analyze the marketing process of the product they sell . The methodology of this research was to analyze system requirements, design unified mod eling language, make process extract, transform, and load, design data warehouse, and data mining that integrate d with the o n l ine a nalytical p rocess cube webbased . The business intelligence model produced was a marketing data mining model and o n l ine a nalytical p rocess cube. The result from on line analytical process cube was the data warehouse of transaction in R Bakery. In designing the data mining, K-means clustering method was used. The results from data mining k-means clustering were there were 83% cluster 1 and 17% cluster 2. Cluster 1 wasthecategorize for low leftover breads and cluster 2 was the categorize for high leftover breads. The model cub e recency, frequency, and monetary and customer lifetime value resulted rank ed out of the most amount of sales in R Bakery. Keywords: business intelligence system, data mining, extract transform load, on line analitical process cube