METODE PENALARAN BERBASIS KASUS (CASE BASE REASONING) DALAM PENENTUAN KELAYAKAN SEKOLAH PERAWATAN

Authors

  • I Wayan Supriana Universitas Udayana
  • Kiki Dwi Prebiana Universitas Udayana

DOI:

https://doi.org/10.31598/jurnalresistor.v3i1.554

Keywords:

dataset nursery, school of nursing, case-based reasoning (CBR), naive bayes

Abstract

Nurse is a job that has many roles in everyday life. Obtained from the ability to become a nurse. In 1980, there was an explosion in the number of registrants at the Ljubljana nursing school, Slovenia. The data is then collected in a data collected data that is a nursery dataset. There are several things related to health conditions, family status, financial conditions and other things that are considered feasible or not to enter the nursing school. A system that can be used for this problem needs to be created. In this study, a system will be made by applying the method of punishment based on cases and classifying domains to increase computational time. Each new case will be calculated the similarity value to the old case using the Bayes naive algorithm. The system built will produce a decision about whether or not the applicant is suitable in nursing school. Of the 100 data tested, 96 data were obtained that produced true values. With a computing time between 0.253 seconds - 0.607 seconds.

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References

N. S. E. Priyanti, “Implementasi Algoritma Naive Bayes Untuk Rekomendasi Sekolah Perawat,†J. Speed, vol. 10, pp. 1–9, 2018.

T. M. M. I. Saputra, “Agen Cerdas Untuk Penentuan Kelayakan Pemberian Kredit Koperasi Simpan Pinjam,†J. Tek. Inform. Amik BSI, pp. 245–252, 2015.

A. S. Aribowo, “Pengembangan Sistem Cerdas Menggunakan Penalaran Berbasis Kasus (Case Based Reasoning) Untuk Diagnosis Penyakit Akibat Virus Eksantema,†J. Telemat., vol. 7, no. Juli, pp. 11–2, 2010.

P. P. M. K. Sari, E. Ernawati, “Kombinasi Metode K-Nearest Neighbor dan Naive Bayes Untuk Klasifikasi Data,†J. SEMNASTEKNIMEDIA, vol. 3, pp. 37–41, 2015.

R. L. De Mantaras et al, Retrieval, Reuse, Revision dan Retention In Case Based Reasoning, vol. 20. 2005.

W. H. M. Minarni, I. Warman, “Case Based Reasoning (CBR) Pada Sistem Pakar Identifikasi Hama dan Penyakit Tanaman Singkong Dalam Usaha Meningkatkan Produktivitas Tanaman Pangan,†J. Teknoif, vol. 5, pp. 42–47, 2017.

Sankar K. Pal and Simon C. K. Shiu, Foundations Of Soft Case-Based Reasoning, Canada. 2004.

A. Y. Kencana, “Metode Klasifikasi Dengan Algoritma Naive Bayes Untuk Rekomendasi Penjurusan SMA Terang Bangsa,†J. Techno.Com, vol. 15, no. June, pp. 195–200, 2016.

A. Saputra, “Klasifikasi Pengenalan Buah Menggunakan Algoritma Naive Bayes,†J. Resist., vol. 2, no. 2, pp. 83–88, 2019.

C. S. Fatoni, “Case Based Reasoning Diagnosis Penyakit Difteri Dengan Algoritma K-Nearest Neighbor,†Citec J., vol. 4, pp. 220–232, 2017.

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Published

2020-04-17

How to Cite

I Wayan Supriana, & Kiki Dwi Prebiana. (2020). METODE PENALARAN BERBASIS KASUS (CASE BASE REASONING) DALAM PENENTUAN KELAYAKAN SEKOLAH PERAWATAN . Jurnal RESISTOR (Rekayasa Sistem Komputer), 3(1), 57-65. https://doi.org/10.31598/jurnalresistor.v3i1.554

Issue

Vol. 3 No. 1 (2020): Jurnal RESISTOR Edisi April 2020

Section

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