Sistem Pakar Pengklasifikasi Stadium Kanker Serviks Berbasis Mobile Menggunakan Metode Decision Tree


  • Maryam Maryam Universitas Muhammadiyah Surakarta
  • Huan Wendy Ariono Fakultas Komunikasi dan Informatika; Universitas Muhammadiyah Surakarta



World Cancer Observation states that in Indonesia cervical cancer ranks second with a total of 9.2% of all cancer cases, which is cervical cancer which continues to increase in percentage every year due to the addition of new cases. It is important for the public to be aware of the symptoms that arise from cervical cancer. Lack of knowledge about cervical cancer from an early age increases the risk of death. This is because the patient knows cervical cancer when it is at an advanced stage. So it is important to know the symptoms of cervical cancer sufferers and their stage level in order to get the appropriate treatment. This study aims to create an expert system that can help the public know the classification of cervical cancer stages. The method used to develop an expert system is the Decision Tree method. One of the decision analysis techniques and classification methods in data mining. The classification process uses 200 records of cervical cancer patients with 12 symptoms as a reference. The Decision Tree method used has an accuracy value of 85.50%, recall 85.40%, and precision 86.74%. The expert system was developed using the flutter framework. The results of the study are in the form of an expert system mobile application that has been black box tested which is declared valid. This system can help the public know the diagnosis results from the symptoms experienced and the stage level accurately to apply the appropriate treatment.


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Author Biographies

Maryam Maryam, Universitas Muhammadiyah Surakarta

Fakultas Komunikasi dan Informatika; Universitas Muhammadiyah Surakarta

Huan Wendy Ariono, Fakultas Komunikasi dan Informatika; Universitas Muhammadiyah Surakarta

Fakultas Komunikasi dan Informatika; Universitas Muhammadiyah Surakarta


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How to Cite

Maryam, M., & Ariono, H. W. . (2022). Sistem Pakar Pengklasifikasi Stadium Kanker Serviks Berbasis Mobile Menggunakan Metode Decision Tree. Jurnal Kajian Ilmiah, 22(3), 267–278.