Diagnosis of Asthma Disease and The Levels using  Forward Chaining and Certainty Factor

Mohamad Irfan; Pebri Alkautsar; Aldy Rialdy Atmadja; Wildan Budiawan Zulfikar

doi:10.29207/resti.v6i5.4123

Mohamad Irfan UIN Sunan Gunung Djati Bandung
Pebri Alkautsar UIN Sunan Gunung Djati Bandung
Aldy Rialdy Atmadja UIN Sunan Gunung Djati Bandung https://orcid.org/0000-0001-7798-8078
Wildan Budiawan Zulfikar UIN Sunan Gunung Djati Bandung

DOI: https://doi.org/10.29207/resti.v6i5.4123

Keywords: Asthma Disease, Certainty Factor, Expert System, Forward Chaining

Abstract

Asthma disease is a major global health issue that affects at least 300 million people worldwide. Even for clinicians working in emergency rooms, predicting the severity of asthma is difficult. Predicting the intensity of an asthma attack is much more challenging because it is dependent on several factors, including the person's illness's features and severity. Forward Chaining and Certainty Factor algorithms can be implemented to diagnose the degree of asthma control, so the consultation process through the system becomes more detailed. The expert system can be used as an initial reference for the diagnosis process. The forward Chaining algorithm is useful for reasoning, starting from a fact to a solution. On the other hand, the Certainty Factor algorithm is used to provide a level of confidence in the conclusions by generating from the Forward Chaining algorithm. The research implemented several phases as follows analysis, data preparation, modeling, and evaluation. On evaluation, this research conduct three stages and tested using 80 medical record data. The result of the study has produced an expert system and generated an accuracy level of 65%, a precision value of 58.3%, and a recall also produced 57.13%. Therefore, the Chaining and Certainty Factor performs reasonably well in the diagnosis of asthma disease.

Downloads

Download data is not yet available.

Author Biography

Aldy Rialdy Atmadja, UIN Sunan Gunung Djati Bandung

Informatics, Faculty of Science and Technology

References

Asthma UK, “Diagnosing asthma: A 21st century challenge,” 2017.

H. J, P. Padila, J. Andri, M. B. Andrianto, and L. Yanti, “Frekuensi Pernafasan Anak Penderita Asma Menggunakan Intervensi Tiup Super Bubbles dan Meniup Baling Baling Bambu,” J. Telenursing, vol. 2, no. 2, pp. 119–126, Sep. 2020, doi: 10.31539/JOTING.V2I2.1409.

Q. Do, T. C. Son, and J. Chaudri, “Classification of Asthma Severity and Medication Using TensorFlow and Multilevel Databases,” Procedia Comput. Sci., vol. 113, pp. 344–351, Jan. 2017, doi: 10.1016/J.PROCS.2017.08.343.

Q. T. Do, A. K. Doig, T. C. Son, and J. M. Chaudri, “Personalized Prediction of Asthma Severity and Asthma Attack for a Personalized Treatment Regimen,” Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, vol. 2018-July, pp. 1–5, Oct. 2018, doi: 10.1109/EMBC.2018.8513281.

A. Djamil, N. S. A. Hermawan, F. Febriani, and W. Arisandi, “Faktor yang Berhubungan dengan Kekambuhan Asma pada Pasien Dewasa,” Wellness Heal. Mag., vol. 2, no. 1, pp. 29–40, 2020, doi: 10.30604/well.48212020.

D. A. WP, “Expert System with Forward Chaining Method to Estimated Cost of Small and Medium Building Development in Indonesia,” Int. J. Adv. Sci. Res. Eng. (IJASRE), ISSN2454-8006, DOI 10.31695/IJASRE, vol. 4, no. 10, pp. 5–12, Oct. 2018, doi: 10.31695/IJASRE.2018.32899.

Y. Purnama, I. Ismail, D. Noviandri, Y. Hendriyani, P. T. Nguyen, and I. P. A. Darmawan, “Expert System in Detecting Children’s Intelligence using Certainty Factor,” J. Crit. Rev., vol. 7, no. 1, pp. 52–55, 2020, doi: 10.22159/jcr.07.01.09.

P. Oktavia et al., “Asma Dengan Solusinya the Design Expert System Diagnosis Asma Using,” vol. 2, pp. 413–422, 2017.

S. Khosyi’Ah, M. Irfan, D. S. Maylawati, and O. S. Mukhlas, “Analysis of Rules for Islamic Inheritance Law in Indonesia Using Hybrid Rule Based Learning,” in IOP Conference Series: Materials Science and Engineering, 2018, vol. 288, no. 1. doi: 10.1088/1757-899X/288/1/012133.

N. Ratama, “Analisa Dan Perbandingan Sistem Aplikasi Diagnosa Penyakit Asma Dengan Algoritma Certainty Factor Dan Algoritma Decision Tree Berbasis Android,” J. Inform. J. Pengemb. IT, vol. 3, no. 2, pp. 177–183, 2018, doi: 10.30591/jpit.v3i2.848.

J. A. Widians and I. Hidayati, “Sistem Pendiagnosa Penyakit Asma Pada Anak Dengan Metode Certainty Factor,” Semin. Nas. Teknol. Inf. dan Multimed. 2016, no. sistem pakar, pp. 6–7, 2016.

A. Wijaya and R. Toyib, “Sistem Pakar Diagnosis Penyakit Asma Dengan Menggunakan Algoritme Genetik,” Stud. Kasus RSUD Kabupaten Kepahiang, vol. 5, no. 2, pp. 2–11, 2018.

GINA, “Asthma Patient Guide,” Glob. Initiat. Asthma, 2021, [Online]. Available: www.ginasthma.org

K. M. Ting, “Confusion Matrix,” Encycl. Mach. Learn. Data Min., no. October, pp. 260–260, 2017, doi: 10.1007/978-1-4899-7687-1_50.

S. Arlis, “SATIN – Sains dan Teknologi Informasi Diagnosis Penyakit Radang Sendi Dengan Metode Certainty Factor,” SATIN-Sains dan Teknol. Inf., vol. 3, no. 1, pp. 43–47, 2017.

M. D. Sinaga, B. S. Riza, J. Iriani, I. Lazuly, Daifiria, and E. H. Victor, “A Forward Chaining Trace Analysis in Diagnosing Tamarillo Disease,” 2018 6th Int. Conf. Cyber IT Serv. Manag. CITSM 2018, no. Citsm, pp. 1–4, 2019, doi: 10.1109/CITSM.2018.8674292.

G. A. D. Sugiharni and D. G. H. Divayana, “Pemanfaatan Metode Forward Chaining Dalam Pengembangan Sistem Pakar Pendiagnosa Kerusakan Televisi Berwarna,” J. Nas. Pendidik. Tek. Inform., vol. 6, no. 1, p. 20, 2017, doi: 10.23887/janapati.v6i1.9926.

A. A. Perbawawati, E. Sugiharti, and M. A. Muslim, “Bayes Theorem and Forward Chaining Method On Expert System for Determine Hypercholesterolemia Drugs,” Sci. J. Informatics, vol. 6, no. 1, pp. 116–124, 2019, doi: 10.15294/sji.v6i1.14149.

I. Efendi, R. K. Niswatin, and I. N. Farida, “Penerapan Metode Certainty Factor untuk Sistem Pakar Diagnosa Penyakit Burung Putuh Berbasis Web,” Semin. Nas. Inov. Teknol., 2020.

Darussalam and G. Arief, “Jurnal Resti,” Resti, vol. 1, no. 1, pp. 19–25, 2017.

I. M. Shofi, L. K. Wardhani, and G. Anisa, “Android application for diagnosing general symptoms of disease using forward chaining method,” Proc. 2016 4th Int. Conf. Cyber IT Serv. Manag. CITSM 2016, 2016, doi: 10.1109/CITSM.2016.7577588.

K. Rukun, “Diagnosis of Toddler Digestion Disorder using Forward Chaining Method,” 2017 5th Int. Conf. Cyber IT Serv. Manag., 2017.

M. Irfan, A. L. M. Rizal, D. S. adillah Maylawati, W. Darmalaksana, and M. A. Ramdhani, “Decision support system of scientific publication awards using forward chaining algorithm,” ACM Int. Conf. Proceeding Ser., pp. 391–395, 2018, doi: 10.1145/3282373.3282397.

I. Ardiansah, F. Efatmi, E. Mardawati, and S. H. Putri, “Feasibility Testing of a Household Industry Food Production Certificate Using an Expert System with Forward Chaining Method,” J. Online Inform., vol. 5, no. 2, p. 137, 2020, doi: 10.15575/join.v5i2.579.

I. Taufik, Y. A. Gerhana, A. I. Ramdani, and M. Irfan, “Implementation K-nearest neighbour for student expertise recommendation system,” in Journal of Physics: Conference Series, 2019, vol. 1402, no. 7. doi: 10.1088/1742-6596/1402/7/077004.