Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : TEKNOLOGIA

KLASIFIKASI GIGITAN ULAR MENGGUNAKAN LOCAL BINARY PATTERN DAN NAÏVE BAYES Fathur Rohman; Adiwijaya Adiwijaya; Dody Qori Utama
JURNAL TEKNOLOGIA Vol 2 No 1 (2019): Jurnal Teknologia
Publisher : Aliansi Perguruan Tinggi Badan Usaha Milik Negara (APERTI BUMN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (5494.817 KB)

Abstract

Cases of poisonous snake bites around the world are estimated to occur around 421,000 cases and 20,000 of them die every year. Identifying snake bite marks on victims will greatly help the medical team in handling victims of snake bites and will avoid fatal errors such as the death of the victim. This research will try to create a system that can classify snake bites images. The system has been built using the extraction method Local Binary Pattern (LBP) and Naive Bayes. Parameter r is a radius, while paramter P is the number of neighbor . The best result of this system has accuracy 83.33%, precision 1.00, recall 0.75, and F1 Score 0.86,parameter that used are r = 1 with P = 8 and r = 3 with P = 16. The dataset used has 20 data, the data divided into 14 training data and 6 testing data.