Analisis perbandingan akurasi antara metode support vector machine (svm) dan jaringan saraf tiruan (jst) untuk klasifikasi karakter baik buruk seseorang

Evi, Pertiwi Munthe (2018) Analisis perbandingan akurasi antara metode support vector machine (svm) dan jaringan saraf tiruan (jst) untuk klasifikasi karakter baik buruk seseorang. Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

On his twitter microblog can be known one's character. This is due to the large number of social media users, unaware to provide information about his personality by use of tweets or post status by using natural language on twitter.One of the techniques to find out which character from someone based on data classification method using twitter.Method of classification of the most widely researched is a method of SVM and ANN.Of the two methods was conducted to know the accuracy of the comparison method according to the classification of the good character of the bad person.A method of testing is done to determine the accuracy of classification technique done using confusion matrix.The results of this research note if the value of accuracy produced by JST higher value accuracy of 84.88% accuracy and value of the resulting SVM of 79.63%.Based on the value of the resulting accuracy then mind if more appropriate methods of JST to classify characters good bad someone using twitter data. Keywords- Classification, tweet, twitter, Pre-processing, SVM, JST

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