{"title":"Analisis Regresi Faktor-Faktor Yang Mempengaruhi Hasil Produksi Padi Di Indonesia Bagian Barat","authors":"Jeni Marianti Loban","doi":"10.33541/edumatsains.v8i1.4856","DOIUrl":null,"url":null,"abstract":"This study aims to measure the influence of factors affecting rice production in the western part of Indonesia. Data analysis used multiple linear regression analysis, using the independent variable X1 = land area (Ha), X2 = rainfall (mm) and X3 = rainy days (days) on the dependent variable, namely the amount of rice production (Y). In this study, it was analyzed how much influence the land area (Ha), rainfall (mm), rainy days (days) had on the amount of rice production (tons). Data analysis using the help of RStudio software. The regression model obtained is Y=61.6+0.000007917X_1-0.1541X_2+0.0002555X_3 with a value of R2=0.9268.","PeriodicalId":33723,"journal":{"name":"Edu Sains Jurnal Pendidikan Sains dan Matematika","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Edu Sains Jurnal Pendidikan Sains dan Matematika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33541/edumatsains.v8i1.4856","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to measure the influence of factors affecting rice production in the western part of Indonesia. Data analysis used multiple linear regression analysis, using the independent variable X1 = land area (Ha), X2 = rainfall (mm) and X3 = rainy days (days) on the dependent variable, namely the amount of rice production (Y). In this study, it was analyzed how much influence the land area (Ha), rainfall (mm), rainy days (days) had on the amount of rice production (tons). Data analysis using the help of RStudio software. The regression model obtained is Y=61.6+0.000007917X_1-0.1541X_2+0.0002555X_3 with a value of R2=0.9268.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
