Penerapan Knowledge-based system untuk Identifikasi Penyakit Pencernaan dan Pernapasan Manusia

Hafid Arjul Prasetya, Suastika Yulia Riska

Abstract

Digestive and respiratory diseases are often considered common, but if left untreated, they can lead to death. Lack of public awareness regarding the importance of medical consultation and limited operational time of health services cause many individuals to self-diagnose diseases. This research aims to develop a knowledge-based system to diagnose digestive and respiratory diseases in humans. This system is expected to provide accurate and relevant diagnosis solutions, as well as support the prevention and early treatment of these diseases. This research includes 8 types of diseases analyzed along with 29 symptoms. The process started with identifying the problem area and determining the decision target based on the data of 8 diseases, followed by the creation of a dependency diagram. Next, IF-THEN rules were developed, and after the rules were formed, the next step was to structure the Backward Chaining and Certainty factor process. This process resulted in the conclusion of the diagnosis of digestive and respiratory diseases. During system testing, the diagnosis results are compared with the expert's knowledge. This test aims to ensure a match between the system results and expert knowledge and to test the accuracy of the data obtained. Based on the results of testing 10 samples of processed data, the system showed an accuracy rate of 100%, which proves that this knowledge-based system works well and in accordance with expert knowledge.

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References

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DOI: https://doi.org/10.31284/j.integer.2024.v10i1.7580

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