Perbandingan Kerangka Model Klasifikasi untuk Pemilihan Metode Kontrasepsi dengan Pendekatan CRIPS-DM

Saeful Amri

Abstract


Rumah Sakit Ibu dan Anak (RSIA) Kusuma Pradja Semarang dalam kesehariannya memberikan pelayanan reproduksi terpadu di Semarang. Dari banyaknya kepesertaan keluarga berencana (KB) perlu diterapkan pengambilan keputusan menggunakan alat kontrasepsi, dalam hal ini perlu dilakukan pendekatan data mining dengan melakukan komparasi 05 kerangka model algoritma klasifikasi yaitu: Decision Tree, Naive Bayes, K-NN, Random Forest, dan Deep Learning demi mendapatkan algoritma terbaik dalam menentukan metode  kontrasepsi yang tepat untuk pasien RSIA Kusuma Pradja Semarang. 

Hasil penelitian menunjukkan bahwa Naive Bayes (NB) merupakan model terbaik dalam menentukan metode kontrasepsi.

Kusuma Pradja Semarang Mother and Child Hospital (RSIA) in its daily life provides integrated reproductive services in Semarang. Of the many members of family planning (KB) it is necessary to apply decision making using contraception, in this case a data mining approach needs to be done by comparing 05 framework classification algorithm models namely: Decision Tree, Naive Bayes, K-NN, Random Forest, and Deep Learning in order to get the best algorithm in determining the right method of contraception for RSIA Kusuma Pradja Semarang patients.

The results showed that Naive Bayes (NB) is the best model in determining contraceptive methods.


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DOI: http://dx.doi.org/10.26623/jisl.v1i1.2488

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[Journal Information Science and Library] adalah jurnal ilmiah yang di terbitkan oleh UPT. Perpustakaan Universitas Semarang - Jl. Soekarno Hatta, Tlogosari Kulon, Pedurungan, Semarang, Jawa Tengah, Indonesia

 

 

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.