Perbandingan analisis algoritma naïve bayes dan certainty factor untuk memprediksi tingkat agreeableness big 5 berbasis android

Al Duri, Maulana Fauzi (2018) Perbandingan analisis algoritma naïve bayes dan certainty factor untuk memprediksi tingkat agreeableness big 5 berbasis android. Diploma thesis, Uin Sunan Gunung Djati Bandung.

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Abstract

INDONESIA The Big Five merupakan salah satu klasifikasi trait pengukuran kepribadian seseorang. Model kepribadian dikembangkan dengan mengelompokkan kata-kata. Hasil pengelompokkan itu terbentuklah 5 faktor yang dijadikan penciri masing-masing kelompok, yang kemudian dikenal menjadi 5 traits kepribadian “The Big Five”. Lima traits kepribadian dalam Big Five) meliputi openness (O), conscientiousness (C), extraversion (E), agreeableness (A), dan neuroticism (N). Dalam penelitian ini akan mencoba Mengimplementasikan algoritma Certainty Factor dan Naïve Bayes ke dalam sebuah sistem yang dapat memprediksi salah satu klasifikasi dalam Big Five yaitu tingkat agreeableness. Metode yang digunakan dalam mendeteksi tingkat agreeableness ini yaitu menggunakan algoritma Certainty Factor dan Naïve Bayes. Hasil yang didapat dalam perbandingan tingkat akurasi dalam prediksi kepribadian, algoritma Certainty Factor mendapatkan hasil sebesar 80% dan Naïve Bayes mendapatkan hasil 90%. Dari hasil tersebut dapat disimpulkan bahwa algoritma Naïve Bayes lebih baik dalam memprediksi kepribadian. ENGLISH The Big Five is one of the trait classifications for measuring one's personality. The personality model is developed by grouping words. The results of the grouping formed 5 factors that made the identifiers of each group, which became known as 5 traits of the personality "The Big Five". Five personality traits in Big Five) include openness (O), conscientiousness (C), extraversion (E), agreeableness (A), and neuroticism (N). This study will try to implement the Certainty Factor and Naïve Bayes algorithm into a system that can predict one of the classifications in the Big Five, namely the level of agreeableness. The method used in detecting this level of agreeableness is using the Certainty Factor and Naïve Bayes algorithms. The results obtained in a comparison of the level of accuracy in personality prediction, the Certainty Factor algorithm get results of 80% and Naïve Bayes get 90%. From these results it can be concluded that the Naïve Bayes algorithm is better at predicting personality.

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