Sihombing, Johnson
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Klasifikasi Data Antroprometri Individu Menggunakan Algoritma Naïve Bayes Classifier Sihombing, Johnson
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 2 No 1 (2021): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (456.584 KB) | DOI: 10.37148/bios.v2i1.15


With the development of advances in computer technology today, most companies and organizations need a decision support system based on information systems, where the information is generally stored in the form of documents / text that is not structured. In this regard, a system for text management that is integrated with the decision support system is needed. One of them is the use of text data classification for anthropometric case studies of several samples. Anthropometry is a measurement of a person's body dimensions. The object of research is gender, first name, and height of a person. The research aims to determine the ratio of the number and height probability level of the number of men and women based on the input into an application using the Naïve Bayes Classifier method. The implementation design uses the Python programming language. The results showed that the height classification data frequency of women was more than the height classification data for men. And the number of height probability of a woman's body is greater than the number of height probability of a man's body.