IMPLEMENTASI CASE BASE REASONING MENGGUNAKAN METODE COSINE SIMILARITY UNTUK MENDIAGNOSA PENYAKIT PADA SAPI - Ssainah P Faransyah; Sebastianus Adi Santoso Mola; Yelly Y Nabuasa (J-Icon : Jurnal Komputer dan Informatika, 2018)
Case Based Reasoning (CBR) is a case-breaking technique based on experience in cases that have previously occurred with the highest similarity value. In this study, the authors apply CBR to diagnose cow disease. Sources of system knowledge are obtained by collecting cases from medical records on 2014, 2016, and 2017. The system uses the Rough Set method for indexing and the calculation of similarity values ​​using the Cosine Similarity method with threshold 70%. This system is able to diagnose 15 diseases based on 29 existing symptoms. The output of the system in the form of the illness experienced, the solution and the presentation of similarities with the previous case to show the truth level of possible diagnose. Based on the test of 30 cases on casebase obtained system accuracy at second part is 27% and at third part the system gets the best result using 3 fold by 33,33%. The system produces low accuracy due to the small number of cases and the scattered data in the case.