Implementasi Metode Naïve Bayes untuk Pemilihan Pengobatan Tumor Tulang

  • Siti Ernawati Universitas Nusa Mandiri
  • Aisyah Putri Faisal Universitas Nusa Mandiri
Keywords: Naïve Bayes, Rapid Miner, Decision Support System, Osteosarcoma

Abstract

Decision support system is an interactive system that helps decision making through the use of data and decision models to solve problems that are semi-structured and unstructured. This study implements the Naive Bayes method because this method has advantages compared to other methods, and the Naive Bayes method is a decision-making to predict probability-based using the values entered, in the form of criteria needed. Bone Tumor is a primary malignancy in children and adolescents, which attacks in adolescents aged 10 to 20 years. Treatment of osteosarcoma can be done by radical amputation or limb salvage procedure, depending on the severity of the tumor. The purpose of this study was to obtain treatment information selected by bone tumor patients using medical record data with sample collection method. In the hope that this information can be a consideration for bone tumor patients who are still hesitant to complete treatment in order to be eager to complete treatment. The results obtained the number of cases of bone tumors is as many as 19 cases, and Limb Salvage is the most widely chosen treatment by bone tumor patients. This study also used rapidminer to see the results of validation. The classification results obtained are accuracy value 80%.

Downloads

Download data is not yet available.

References

I. G. N. Desrianta and I. G. E. Wiratnaya, “Prevalensi Tumor Tulang Jinak Di Rumah Sakit Umum Pusat Sanglah Denpasar Tahun 2013-2015,” Medika Udayana, vol. 9, no. 11, pp. 110–114, 2020.

Y. D. Ismiarto and G. L. Sitanggang, “Karakteristik Pasien dengan Osteosarkoma Pada Ekstremitas di Rumah Sakit Umum Pusat dr . Hasan Sadikin Bandung Periode Januari-Desember 2014,” Syifa Medika, vol. 10, no. 1, pp. 23–29, 2019.

F. Mahyudin, M. Edward, and Dkk, “Osteosarcoma Has Not Become Attention To Society,” Journal Orthopaedi and Traumatology Surabaya JOINTS, vol. 7, no. 1, pp. 20–30, 2018.

Budiman and Windy Indriani, “Sistem Pendukung Keputusan Pengambilan Keputusan Pemilihan Obat Alternatif Dengan Metode Electre Dan Topsis,” 2006.

D. Dahri, F. Agus, and D. M. Khairina, “Metode Naive Bayes Untuk Penentuan Penerima Beasiswa Bidikmisi Universitas Mulawarman,” Junal Informatika Mulawarman, vol. 11, no. 2, pp. 29–36, 2016.

S. Bagas, Sabrang, “Sistem Pendukung Keputusan Pemilihan Obat Diare,” 2018.

Bayu Setyaji and Pujiono, “Sistem Pendukung Keputusan Penentuan Kelayakan Calon Tenaga Kerja Menggunakan Metode Naïve Bayes Classification(Studi Kasus CV. Lingkar Aksi),” Bayu Setyaji, Pujiono, p. 4, 2006.

V. Marudut and Siregar, “Sistem Pendukung Keputusan Penentuan Insentif Bulanan Pegawai Dengan Menggunakan Metode Naïve Bayes,” Jurnal SISTEMASI, vol. 7, pp. 87–94, 2018.

K. Ayu Milati Nur Azizah, “Sistem Pendukung Keputusan Penyeleksian Mahasiswa Penerima Beasiswa Menggunakan Metode Naive Bayes Berbasis Web,” Antivirus : Jurnal Ilmiah Teknik Informatika, vol. 10, no. 1, pp. 6–10, 2016.

Published
2022-03-16
How to Cite
Ernawati, S., & Faisal, A. P. (2022). Implementasi Metode Naïve Bayes untuk Pemilihan Pengobatan Tumor Tulang. BIOS : Jurnal Teknologi Informasi Dan Rekayasa Komputer, 3(1), 1-8. https://doi.org/10.37148/bios.v3i1.34