Clustering k-means untuk menentukan zona pasar tanah pada penilaian KJPP Rija Husaeni dan Rekan

Elsa Fitri Surya (Universitas Nusa Mandiri)

Jurnal Widya
Vol. 2 No. 2 (2021): Jurnal Widya (awl) : October 2021

One of the jobs is Appraisal Service, whice is determined by this fee is fixed costs such as : land, buildings, vehicles, machinery, and other buildings. In this report, one of which requires information as information as management and producing reports, in KJPP Rija Husaeni and Partners, the published production reports are recapitulated by the admin as market information data, currently market data information is recapitulated by the admin division in the form of The data entered is based on published report numbers and has not been grouped based on the area’s land market zone to make it easier if there are employees of KJPP Rija Husaeni and Partners who need information about the area’s land market zone. On the basis of identifying the problems described above, a data processing process using a data mining technique is required. The data mining technique used in this research is clustering with the K-Means algorithm to determine the land market zone in the KJPP Rija Husaeni and Partners assessment.