Sistem Pakar Dalam Mendiagnosa Penyakit Tubercolosis dengan mengimplementasikan Metode Case Based Reasoning
-
Aris Wijayanti
*
Universitas PGRI Ronggolawe, Tuban,
Indonesia
- Fatimah Nur Arifah STMIK Bina Patria Magelang, Magelang, Indonesia
- Desfita Eka Putri Politeknik LP3I Pekanbaru, Pekanbaru, Indonesia
- Muhammad Dwi Satriyanto , Universitas Abdurrab, Pekanbaru, Indonesia
- Sulfikar Sallu Universitas Sembilan Belas November, Kolaka, Indonesia (*) Corresponding Author
Abstract
Health is one of the most valuable parts of human life. So healthy is the goal of every human being. Many things cause the decline in human health, such as hereditary genes, sensitive immunity and exposure to viruses or bacteria. One of the diseases caused by bacteria is tuberculosis (TB). Tuberculosis is a disease caused by exposure to a bacterium called Mycobacterium tuberculosis. There are two types of tuberculosis, namely pulmonary tuberculosis and extra pulmonary tuberculosis. Pulmonary tuberculosis can be defined as a disease that attacks the lungs and affects the lung parenchyma [4]. It's just that this type of disease does not attack other organs. While extrapulmonary tuberculosis is a tuberculosis disease in which this type of disease can attack other related organs such as the hilum, pleura and various other organs. the lack of funds for health checks makes it too late for many people to get treatment. Therefore, the development of technology should be utilized in handling this problem. One of the technologies that can be used in dealing with these problems is to use an expert system. An expert system is a system that is developed using the development of the knowledge that is owned by many experts and is used as a reference in developing the technology. In using an expert system, a method is needed that can help solve existing problems, therefore in this study the method used is the Case-Based Reasoning (CBR) method. The Case-Based Reasoning (CBR) method is the most suitable method for use in this study because the main function of this method is to diagnose disease. Based on the results of the calculation process using the Case-Based Reasoning method for each type of TB disease, the results obtained are for pulmonary tuberculosis to obtain a value of 85%, while for tuberculosis with extra pulmonary tuberculosis it is 62%. So based on the results obtained in this study it was determined that the sample was diagnosed with pulmonary tuberculosis. With a similarity of 85%.
Downloads
References
V. K. Jain, K. P. Iyengar, D. A. Samy, and R. Vaishya, “Tuberculosis in the era of COVID-19 in India,” Diabetes Metab. Syndr. Clin. Res. Rev., vol. 14, no. 5, pp. 1439–1443, 2020.
F. Bangun, “Sistem Pakar Mendiagnosa Penyakit TBC Menggunakan Metode Teorema Bayes,” J. Tek. Dan Inform., vol. 6, no. 2, pp. 23–29, 2019.
A. Natarajan, P. M. Beena, A. V Devnikar, and S. Mali, “A systemic review on tuberculosis,” Indian J. Tuberc., vol. 67, no. 3, pp. 295–311, 2020.
E. Harding, “WHO global progress report on tuberculosis elimination,” Lancet Respir. Med., vol. 8, no. 1, p. 19, 2020.
H. K. Bharata and H. Sulistyowati, “Optimasi Sistem Penilaian Ujian Essay Online Menggunakan Support Vector Machine (SVM) Dan Latent Semantic Analysis (LSA) Dengan Bahasa R,” Sci. J. Inf. Syst. Technol. Appl. Comput. Eng, vol. 10, no. 2, pp. 63–70, 2020.
N. Vendyansyah and Y. A. Pranoto, “Perancangan dan Pembuatan Aplikasi untuk Mendeteksi Kemiripan Jawaban Menggunakan Cosine Similarity,” J. Tek. (Jurnal Fak. Tek. Univ. Islam Lamongan), vol. 13, no. 1, pp. 23–28, 2021.
D. Nofriansyah, R. Gunawan, and E. Elfitriani, “Sistem Pakar Untuk Mendiagnosa Penyakit Pertussis (Batuk Rejan) Dengan Menggunakan Metode Teorema Bayes,” J. Teknol. Sist. Inf. dan Sist. Komput. TGD, vol. 3, no. 1, pp. 41–54, 2020.
I. Syamsudin and E. Eko, “PENERAPAN METODE CERTAINTY FACTOR PADA SISTEM PAKAR MENDIAGNOSA PENYAKIT TUBERCULOSIS (TB) PARU BERBASIS WEB MOBILE,” JUSIM (Jurnal Sist. Inf. Musirawas), vol. 7, no. 2, pp. 127–136, 2022.
J.-B. Lamy, B. Sekar, G. Guezennec, J. Bouaud, and B. Séroussi, “Explainable artificial intelligence for breast cancer: A visual case-based reasoning approach,” Artif. Intell. Med., vol. 94, pp. 42–53, 2019.
S. W. Nasution, N. A. Hasibuan, and P. Ramadhani, “Sistem Pakar Diagnosa Anoreksia Nervosa Menerapkan Metode Case Based Reasoning,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 1, no. 1, 2017.
H. Sulistiani, I. Darwanto, and I. Ahmad, “Penerapan Metode Case Based Reasoning dan K-Nearest Neighbor untuk Diagnosa Penyakit dan Hama pada Tanaman Karet,” JEPIN (Jurnal Edukasi Dan Penelit. Inform., vol. 6, no. 1, pp. 23–28, 2020.
F. Tahel, S. Aliyah, and M. Adam, “Rancang Bangun Aplikasi PHP dalam Mendeteksi Penyakit Kelinci Menggunakan Metode Case-Based Reasoning (CBR),” J. Comput. Syst. Informatics, vol. 1, no. 4, pp. 293–302, 2020.
I. Nugraha and M. Siddik, “Penerapan Metode Case Based Reasoning (CBR) Dalam Sistem Pakar Untuk Menentukan Diagnosa Penyakit Pada Tanaman Hidroponik,” J. Mhs. Apl. Teknol. Komput. dan Inf., vol. 2, no. 2, pp. 91–96, 2021.
R. I. Borman, R. Napianto, P. Nurlandari, and Z. Abidin, “Implementasi Certainty Factor Dalam Mengatasi Ketidakpastian Pada Sistem Pakar Diagnosa Penyakit Kuda Laut,” Jurteksi (Jurnal Teknol. Dan Sist. Informasi), vol. 7, no. 1, pp. 1–8, 2020.
M. Lansley, N. Polatidis, S. Kapetanakis, K. Amin, G. Samakovitis, and M. Petridis, “Seen the villains: Detecting social engineering attacks using case-based reasoning and deep learning,” 2019.
C. Zeyen, L. Malburg, and R. Bergmann, “Adaptation of scientific workflows by means of process-oriented case-based reasoning,” in Case-Based Reasoning Research and Development: 27th International Conference, ICCBR 2019, Otzenhausen, Germany, September 8–12, 2019, Proceedings 27, 2019, pp. 388–403.
M. Pai, T. Kasaeva, and S. Swaminathan, “Covid-19’s devastating effect on tuberculosis care—A path to recovery,” N. Engl. J. Med., vol. 386, no. 16, pp. 1490–1493, 2022.
T. R. Sterling et al., “Guidelines for the treatment of latent tuberculosis infection: recommendations from the National Tuberculosis Controllers Association and CDC, 2020,” American Journal of Transplantation, vol. 20, no. 4. Elsevier, pp. 1196–1206, 2020.
A. Soleh, “Strategi Pengembangan Potensi Desa,” J. Sungkai, vol. 5, no. 1, pp. 35–52, 2017.
B. Riyanto, “Penerapan Algoritma K-Medoids Clustering Untuk Pengelompokkan Penyebaran Diare Di Kota Medan (Studi Kasus: Kantor Dinas Kesehatan Kota Medan),” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, 2019.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Sistem Pakar Dalam Mendiagnosa Penyakit Tubercolosis dengan mengimplementasikan Metode Case Based Reasoning
Pages: 570-577
Copyright (c) 2023 Aris Wijayanti, Fatimah Nur Arifah, Desfita Eka Putri, Muhammad Dwi Satriyanto, Sulfikar Sallu
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
