A Mobile-based Expert System for Disease Diagnosis Child using Best-First Search Algorithm


  • Nurwahyuni Hasan Universitas Labuhanbatu, Indonesia
  • Gomal Juni Yanris Universitas Labuhanbatu, Indonesia
  • Elysa Rohayani Hasibuan Universitas Labuhanbatu, Indonesia




Currently, many parents want their children to be free from disease. Although this cannot be fully expected. Problems that often occur to parents are when their child is sick, lack of knowledge and limited sources of information about the disease that causes parents to leave their children without first aid. In other conditions, in areas that are far from the doctor's practice, the need for information on disease management is very necessary. Based on the problems that have been described previously, this expert system was created to assist parents in understanding the symptoms of skin diseases that occur in children. In the development of this expert system using the Best-First Search (BFS) algorithm as an inference engine. In this expert system application the user can choose the symptoms of the disease in children, then the output produced is the conclusion of the disease. From the test results based on Blackbox, it was found that 100% functionality runs according to the list of system requirements. After this research was completed, it was concluded that to design an expert system in detecting childhood diseases, starting from conducting interviews, followed by system design, the next process was implementing the system, then testing by experts for compatibility with the data that had been obtained. 

GS Cited Analysis


Download data is not yet available.


Alkaff, M., Khatimi, H., Sari, Y., Darmawan, P., & Primananda, R. (2019). Sistem Pakar Berbasis Android untuk Mendeteksi Jenis Perilaku ADHS pada Anak. Jurnal Teknologi Informasi Dan Ilmu Komputer (JTIIK), 6(2), 135–140. https://doi.org/10.25126/jtiik.201961265

Chen, Z., He, C., He, Z., & Chen, M. (2018). BD-ADOPT: a hybrid DCOP algorithm with best-first and depth-first search strategies. Artificial Intelligence Review, 50(2), 161–199. https://doi.org/10.1007/s10462-017-9540-z

Chimanga, K., Kalezhi, J., & Mumba, P. (2016). Application of best first search algorithm to demand control. 2016 IEEE PES PowerAfrica, 51–55. https://doi.org/10.1109/PowerAfrica.2016.7556568

Darmayunata, Y. (2018). Sistem Pakar Berbasis Web Menggunakan Metode Backward Chaining Untuk Menentukan Nutrisi Yang Tepat Bagi Ibu Hamil. INTECOMS: Journal of Information Technology and Computer Science, 1(2), 231–239. https://doi.org/10.31539/intecoms.v1i2.302

Efendi, D. M., & Sari, P. Y. (2020). Sistem Pakar Diagnosa Penyakit Kulit Wajah dengan Metode Certainy Factor pada Klinik Skin Rachel. Jurnal Informasi Dan Komputer, 1(8).

Ferdiansyah, W. R., Muflikhah, L., & Adinugroho, S. (2018). Sistem Pakar Diagnosis Penyakit Pada Kambing Menggunakan Metode Naive Bayes dan Certainty Factor. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 2(2), 451. Retrieved from http://j-ptiik.ub.ac.id

Ginting, N. S. W., & RMS, A. S. (2018). Sistem Pakar Diagnosa Penyakit Kacang Kedelai Menggunakan Metode Certainty Factor. Jurnal KomTekInfo, 5(1), 36–41.

Kurniawan, A. (2018). Sistem Pakar Mendiagnosa Penyakit Flu Burung Secara Online Dengan Metode Forward Chaining. JIKA (Jurnal Teknik Informatika), 2(1), 33–39. https://doi.org/10.31000/jika.v2i1.1414

Pujianti, W., & Sitti, Z. (2021). Sistem Pakar Diagnosa Penyakit Campak Rubella pada Anak Menggunakan Metode Certainty Factor Berbasis Website. Jurnal Teknologi Informasi Dan Ilmu Komputer (JTIIK), 8(1). https://doi.org/10.25126/jtiik.202182710

Sari, M., Defit, S., & Nurcahyo, G. W. (2020). Sistem Pakar Deteksi Penyakit pada Anak Menggunakan Metode Forward Chaining. Jurnal Sistim Informasi Dan Teknologi, 2, 130–135. https://doi.org/10.37034/jsisfotek.v2i4.34

Więckowski, J., Kizielewicz, B., & Kołodziejczyk, J. (2020). Application of Hill Climbing Algorithm in Determining the Characteristic Objects Preferences Based on the Reference Set of Alternatives BT - Intelligent Decision Technologies (I. Czarnowski, R. J. Howlett, & L. C. Jain, eds.). Singapore: Springer Singapore.


Crossmark Updates

How to Cite

Hasan, N., Yanris, G. J. ., & Hasibuan, E. R. . (2022). A Mobile-based Expert System for Disease Diagnosis Child using Best-First Search Algorithm. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(2), 701-707. https://doi.org/10.33395/sinkron.v7i2.11426

Most read articles by the same author(s)