PENENTUAN TINGKAT KEKUMUHAN PERMUKIMAN KUMUH KOTA PALEMBANG DENGAN METODE ALGORITMA K-MEANS CLUSTERING DAN ALGORITMA ID3

Intech Pub Date : 2021-06-26 DOI:10.54895/intech.v2i1.869
Lastri Widya Astuti, Endah Puspita Sari, Imelda Saluza, Faradillah Faradillah, Rini Yunita
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Abstract

Slum settlers are a condition of uninhabitable settlements. Slums are devided into 4 levels, namely : high slums, medium, light and not slum. To produce these four levels, method is used namely K-Means Clustering Algorithm and the ID3 Algorithm is used to give priority with pre determined attributes then accumulated with the results of clustering classified as slum level. The accuracy test is performe by using the confusion matrix method, where the data results from the K-Means Clustering method compared to the baseline data. The results obtained from the accuracy with confusion matrix is 0,70%, which means the level of truth (accuracy) between the result of the baseline data with research data is 70%.
用d -累积算法和ID3算法来定义帕伦邦贫民窟的老城区能力
贫民窟居民是一种不适合居住的定居点。贫民窟分为4个级别,即:高贫民窟、中等贫民窟、低贫民窟和非贫民窟。为了产生这四个级别,使用了K-Means聚类算法,并使用ID3算法对预先确定的属性进行优先级排序,然后将聚类结果累积为贫民窟级别。通过使用混淆矩阵方法执行准确性测试,其中K-Means聚类方法的数据结果与基线数据进行比较。通过混淆矩阵的准确度得到的结果为0,70%,即基线数据的结果与研究数据之间的真值(准确度)水平为70%。
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