Open AccessImplementasi Data Mining dalam Mengelompokkan Rumah Tangga Kumuh di Perkotaan Berdasarkan Provinsi Menggunakan Algoritma K-Means
Author(s) -
Ranti Andini Margolang,
Sundari Retno Andani,
Muhammad Ridwan Lubis
Publication year - 2019
Publication title -
prosiding seminar nasional riset information science (senaris)
Language(s) - English
Resource type - Journals
ISSN - 2686-0260
DOI - 10.30645/senaris.v1i0.66
Subject(s) - slum , sanitation , cluster analysis , government (linguistics) , business , per capita , population , geography , computer science , environmental health , engineering , medicine , environmental engineering , machine learning , linguistics , philosophy
Slum is an area with a high population density levels in the city are generally inhabited by the poor and the unemployment rate is high, the slum also became a center of health problems because the conditions are not higenis. Slum slum household is is the home that do not have access to a source of drinking water, have no access to decent sanitation, have no access to floor area > = 7.2 m2 Per capita, and do not have access to conditions the roof, floor, and walls. This study used data sourced from the Central Bureau of statistics the year 2015 – 2016. The method used is Datamining the K-Means Clustering, Clustering is a method used in datamining the how it works find and classify data that has a semblance and characteristics of data between one another with the data. Using this algorithm the data already obtained can be grouped into Clusters based on this data. This data can be entered to the local Government to recommend to the Government so that the Government can handle the Spreader area development assistance to areas of slum households.