PENERAPAN DATA MINING UNTUK PENGELOMPOKAN HASIL DIAGNOSA PASIEN DENGAN ALGORITMA K-MEANS CLUSTERING(STUDI KASUS: DOKTER DEWI DENTAL CLINIC LAHAT SUMATERA SELATAN)

GUNAWAN, DANDI and Lestarini, Dinda (2023) PENERAPAN DATA MINING UNTUK PENGELOMPOKAN HASIL DIAGNOSA PASIEN DENGAN ALGORITMA K-MEANS CLUSTERING(STUDI KASUS: DOKTER DEWI DENTAL CLINIC LAHAT SUMATERA SELATAN). Undergraduate thesis, Sriwijaya University.

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Abstract

Doctor Dewi Dental Clinic Lahat is a health worker engaged in dental and oral medicine. In the field of health, the medical record is a record of the patient's history of treatment in hospitals and other treatment centers. The result of the medical record is currently a pile of data that has not been processed and is always increasing every day. Data mining is the right solution to find information contained in these medical record activities. Data Mining is a data processing method to find hidden patterns from the data. This study used data mining techniques with the K-Means clustering method to cluster patient medical record data. From the results of the K=7 test with the parameters Measure Types (Bregman Divergence) and divergence (Mahalonobis Distance) as well as local random seed 1000 seen from the results of the Davies Bouldin Index (DBI). This grouping of diagnoses can later provide information for Doctor Dewi Dental Clinic to classify medical record results more precisely.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Data mining, K-means clustering, Rapidminer, DBI, Klinik gigi
Subjects:	T Technology > T Technology (General) > T57-57.97 Applied mathematics. Quantitative methods > T57.5 Data processing Cf. HF5548.125+ Business data processing Operations research. Systems analysis
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Dandi Gunawan
Date Deposited:	27 Sep 2023 08:26
Last Modified:	27 Sep 2023 08:26
URI:	http://repository.unsri.ac.id/id/eprint/129235

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