Classification of Generation By Population by Region in Indonesia Using K-Means Algorithm

Ririn Restu Aria, Susi Susilowati
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Abstract

Population growth caused by the year of birth led to the classification of population groups into several generations. Classification is important because in each generation there is based on population growth has different characteristics and traits in each generation. This research was conducted to try to group generations based on provinces in Indonesia based on the number of residents owned. When researchers analyzed the data obtained from population census data conducted by the central statistics agency (BPS). The method used in generation classification grouping uses the K-Means algorithm method based on 3 clusters. Based on the results of calculations carried out for 3 clusters obtained cluster 1 has 25 provinces, cluster 2 has 3 provinces and cluster 3 has 6 provinces. Based on the 2020 census that has been conducted, the current population is generation Z, generation and Pre Boomer generation is last in line so that from the available data can provide information about mapping in 34 provinces to be able to improve communication patterns between generations and fulfill public facilities that can be used every generation
基于K-Means算法的印尼地区人口世代分类
由出生年份引起的人口增长导致了人口群体的几代划分。分类是很重要的,因为每一代都有基于人口增长的不同特征和特征。这项研究是试图根据拥有的居民数量,根据印度尼西亚的省份对代际进行分组。研究人员分析了由中央统计局(BPS)进行的人口普查数据。生成分类分组采用基于3聚类的K-Means算法方法。根据对3个聚类的计算结果,得到聚类1有25个省,聚类2有3个省,聚类3有6个省。根据已经进行的2020年人口普查,目前的人口是Z一代,前婴儿潮一代是最后一代,因此可以从现有的数据中提供34个省份的地图信息,以改善代际之间的沟通模式,并实现每一代人都可以使用的公共设施
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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