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Journal : Journal of Mathematics and Scientific Computing With Applications

BLACK TEA GRADE CLASSIFICATION USING PROBABILISTIC NEURAL NETWORK (PNN) Sari, Evi Indah; Prasetya, Nurul Huda; Lubis, Riri Syafitri
Journal of Mathematics and Scientific Computing With Applications Vol. 2 No. 1 (2021)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (284.543 KB) | DOI: 10.53806/jmscowa.v2i1.42

Abstract

North Sumatera tea is known as black tea, one which is produced by PT Perkebunan Nusantara IV Unit Bah Butong which produce 16 types of black tea. This research aims to classify black tea grades using Probabilistic Neural Network method and determine the accuracy value of black tea classification using Probabilistic Neural Network method. Data used are data of characteristics of 16 black tea types with the attributes id, types of tea, colour density, particel weight, particel size and particel shape. To get the best accuracy result, training data and testing data are divided using K-Means Clustering. Futhermore, classificy the testing data using Probabilistik the result obtained a grade 1 classification class totaling 7 records with a brownish black appearance and granutes particel, grade 2 totalling 7 record with a beownish appearance and grade 3 totaling 2 records with reddish appearance and not determine its shape and obtain an accuracy value of 80,00%.