Prediksi Kepribadian Myers-Briggs Type Indicator Menggunakan Long Short Term Memory

Prediksi Kepribadian Myers-Briggs Type Indicator Menggunakan Long Short Term Memory

• By Maulidah, Mawadatul;
• Tesis
• 333

Istilah "kepribadian" dapat didefinisikan sebagai campuran fitur dan kualitas yang membangun karakter khas individu, termasuk pikiran, perasaan, dan perilaku. Seiring dengan perkembangan teknologi yang pesat, komputasi kepribadian telah menjadi bidang penelitian populer yang menyediakan personalisasi kepada pengguna. Saat ini, para peneliti telah menggunakan data media sosial untuk memprediksi kepribadian secara otomatis. Penelitian ini menggunakan dataset publik dari Kaggle yaitu Myers-Briggs Personality Type Dataset. Tujuan dari penelitian ini adalah untuk memprediksi akurasi dan klasifikasi kepribadian MBTI dengan menggunakan atribut dari dataset MBTI yaitu posts dan type. Analisis akurasi prediksi dilakukan dengan menggunakan algoritma Long Short Term Memory (LSTM) dengan bantuan feature Random Oversampling untuk prediksi tipe kepribadian MBTI dan membandingkan kinerja metode yang diusulkan dalam penelitian ini dengan algoritma pembelajaran mesin populer lainnya. Model LSTM menggunakan pengoptimal RMSprop dan learning rate  10³ menghasilkan kinerja yang lebih tinggi dalam akurasi daripada algoritma pembelajaran mesin yang diusulkan, sehingga dapat membantu dalam mengidentifikasi tipe kepribadian.

• Katakunci Kepribadian, Long Short Term Memory, Myers-Briggs Type Indicator, Prediksi.
• URL http://
• Penerbit ,

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