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Studi Implementasi Adaptive Neuro Fuzzy Inference System Untuk Menentukan Normalitas Kehamilan

*Lili Rusdiana  -  STMIK Palangkaraya, Kalimantan Tengah, Indonesia
Eko Sediyono  -  Magister Sistem Informasi Universitas Kristen Satya Wacana, Indonesia
Bayu Surarso  -  Jurusan Matematika, Fakultas Sains dan Matematika Universitas Diponegoro, Indonesia

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Early detection of normality pregnancy is one of the ways to prevent more serious disorders in pregnancy. This thesis study the implementation of Adaptive Neuro Fuzzy Inference System (ANFIS) to determine the normality of pregnancy. The period of pregnancy and complaints during pregnancy are used as inputs and the normality of pregnancy as output. Data were analyzed using ANFIS method and using Sugeno FIS rules. The program simulation results show that the performance of ANFIS can be implemented to determine the normality of pregnancy. The learning results on different training with the highest level of accuracy of 77,5% can recognize the symptoms and 97.5% could identify the diagnosis to determine the normality of pregnancy. The system can provide the necessary information about the normality of pregnancy. The results show that ANFIS can be used to determine the normality of pregnancy.



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Keywords: ANFIS; Normality of Pregnancy

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