Sistem Pakar Diagnosis Penyakit Leukimia dengan Metode Fuzzy Tsukamoto - Stefan Levianto; Arief Andy Soebroto (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2021)
Leukemia or what we usually call blood cancer is cancer that attacks white blood cells. The healing method which is still being debated in the medical world and the difficulty in preventing this disease, makes this disease a deadly cancer. Lack of experts and information about leukemia often results in delays in diagnosing leukemia. The high cost of medical treatment by doctors has made many people try alternative treatments, which are relatively more affordable. However, even alternative medicine does not ensure a cure for the patient, which in turn requires the patient to be taken to the hospital again and in most cases the cancer has reached an advanced stage. Based on these problems the authors conclude and raise a problem into an expert system study to diagnose leukemia which is expected to help sufferers and doctors in need. The expert system for diagnosing leukemia which is made using the Fuzzy Tsukamoto method based on 100 patient training data with 10 attributes, has been tested with expert diagnosis having a success rate of 90%. The difference in the results of system diagnosis with experts from 30 test data is 3 data so that there are 27 correct data from 30 test data.