Forecasting the Ambon City Consumer Price Index Using Arima Box-Jenkins

Jefry Esna T. Radjabaycole, Ronald John Djami, G. Haumahu
{"title":"Forecasting the Ambon City Consumer Price Index Using Arima Box-Jenkins","authors":"Jefry Esna T. Radjabaycole, Ronald John Djami, G. Haumahu","doi":"10.30598/tensorvol2iss2pp87-96","DOIUrl":null,"url":null,"abstract":"The Consumer Price Index is an index number that measures the average price of goods and services consumed by households. The index number is the price comparison in a certain month against the previous month, in which case the price in the previous month is the price in the base year in the CPI calculation. CPI is time series data, so CPI data in the next period can be known by forecasting through time series analysis. Arima is a technique for finding the most suitable pattern from a group of data (curve fitting). Based on the results of the analysis, the best ARIMA model used in forecasting CPI in Ambon city for the period January 2007 to December 2020 is the ARIMA model (1,1,1), namely 1 = 0.9000 and 1 = 0.9933.","PeriodicalId":294430,"journal":{"name":"Tensor: Pure and Applied Mathematics Journal","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tensor: Pure and Applied Mathematics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30598/tensorvol2iss2pp87-96","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The Consumer Price Index is an index number that measures the average price of goods and services consumed by households. The index number is the price comparison in a certain month against the previous month, in which case the price in the previous month is the price in the base year in the CPI calculation. CPI is time series data, so CPI data in the next period can be known by forecasting through time series analysis. Arima is a technique for finding the most suitable pattern from a group of data (curve fitting). Based on the results of the analysis, the best ARIMA model used in forecasting CPI in Ambon city for the period January 2007 to December 2020 is the ARIMA model (1,1,1), namely 1 = 0.9000 and 1 = 0.9933.
利用Arima Box-Jenkins预测安汶市消费者物价指数
消费者价格指数是衡量家庭消费商品和服务平均价格的指数。指数是某一个月与前一个月的价格比较,在这种情况下,前一个月的价格就是CPI计算中基准年的价格。CPI是时间序列数据,可以通过时间序列分析预测下一时期的CPI数据。Arima是从一组数据(曲线拟合)中找到最合适模式的技术。根据分析结果,2007年1月至2020年12月安本市CPI预测的最佳ARIMA模型为ARIMA模型(1,1,1),即1 = 0.9000,1 = 0.9933。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信