Open access Jurnal SINTA 2
Prediksi Tipe Kepribadian MBTI Artis K-Pop Berdasarkan Caption Instagram Menggunakan Word2Vec dan Long-Short Term Memory (LSTM)
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 10 No. 5 (2023) · pp. 993–1002
- ISSN
- 2528-6579, 2355-7699
- Published
- 2023-10-17
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- id
Abstract
Myers-Briggs Type Indicator (MBTI) adalah metode pengujian psikologi yang membedakan kepribadian seseorang. MBTI termasuk pembagian tipe kepribadian yang paling populer di dunia, termasuk di Korea Selatan. Tren MBTI di Korea Selatan juga dimanfaatkan oleh para artis K-Pop untuk berbagi tipe MBTI sehingga bisa mendekatkan hubungan antara penggemar dan idolanya. Salah satu media sosial yang umum digunakan oleh artis K-Pop adalah Instagram. Penelitian ini mencoba membuat model klasikasi tipe kepribadian berdasarkan caption Instagram artis K-Pop menggunakan Word2Vec dan Long-Short Term Memory (LSTM). Terdapat 118.401 data caption yang sudah dibersihkan melalui serangkaian langkah pre-processing dari 458 artis. Distribusi tipe kepribadian menunjukkan bahwa target tidak seimbang sehingga perlu dilakukan penanganan yaitu penggeseran threshold yang dilakukan pasca pemodelan. Evaluasi kombinasi model menghasilkan nilai macro f1 0,65 pada data artis, dengan rincian model Extroversion-Introversion, Sensing-Intuition, Thinking-Feeling memiliki nilai macro f1 yang sama yaitu 0,88, sedangkan model Judging-Perceiving memiliki nilai macro f1 yang sedikit lebih baik yaitu 0,90. Model diimplementasikan dalam aplikasi web Streamlit agar penggemar K-Pop dapat menggunakannya untuk memprediksi tipe MBTI dengan masukan caption Instagram. Aplikasi web dievaluasi menggunakan kuesioner System Usability Scale (SUS) dan mendapatkan skor 84,55 sehingga sudah termasuk kategori acceptable. Abstract Myers-Briggs Type Indicator (MBTI) is a psychological test that distinguishes a person's personality. The MBTI is one of the most popular personality types in the world, including South Korea. The MBTI trend in South Korea is also used by K-Pop artists to share their MBTI types so they could be closer to their fans. One of the social media commonly used by K-Pop artists is Instagram. This study tries to develop a personality type classification model based on Instagram captions of K-Pop artists using Word2Vec and Long-Short Term Memory (LSTM). There are 118,401 caption data that have been cleaned through a series of pre-processing steps from 458 artists. The distribution of personality types shows that the target is not balanced, so it is necessary to handle imbalanced data, namely shifting the threshold after modeling. Evaluation of the combination model yields a macro f1 value of 0.65 in the artist data, with the details of the Extroversion-Introversion, Sensing-Intuition, Thinking-Feeling models having the same macro f1 value of 0.88, while the Judging-Perceiving model has a slightly better macro f1 value of 0.90. The model is deployed in the Streamlit web application so that K-Pop fans can use it to predict the MBTI type by inputting Instagram captions. The web application is evaluated using the System Usability Scale (SUS) questionnaire and gets a score of 84.55 so it is considered acceptable.
Collaboration network of the authors
40 authors · 92 co-authorship links · 32 across different organisations · showing the 40 most connected
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- National Research and Innovation Agency
- Institut Teknologi Sepuluh Nopember
- Indonesian Institute of Sciences
- Universitas Muhammadiyah Malang
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Admaja Dwi Herlambang | University of Brawijaya | 5 |
| Yusi Tyroni Mursityo | University of Brawijaya | 3 |
| Satrio Agung Wicaksono | University of Brawijaya | 3 |
| Ahmad Afif Supianto | University of Brawijaya | 3 |
| Dian Eka Ratnawati | University of Brawijaya | 3 |
| Fahrur Rozi | Institut Teknologi Sepuluh Nopember | 2 |
| Septiyan Andika Isanta | Universitas Muhammadiyah Malang | 2 |
| Aditya Rachmadi | University of Brawijaya | 2 |
| Faizatul Amalia | University of Brawijaya | 2 |
| Welly Purnomo | University of Brawijaya | 2 |
| Nur Laita Rizki Amalia | University of Brawijaya | 1 |
| Vicky Zilvan | Indonesian Institute of Sciences | 1 |
| Asri Rizki Yuliani | Indonesian Institute of Sciences | 1 |
| Ade Ramdan | Indonesian Institute of Sciences | 1 |
| Reza Andria S | Affiliation unknown | 1 |
| Sarwosri Sarwosri | Institut Teknologi Sepuluh Nopember | 1 |
| Diana Purwitasari | Institut Teknologi Sepuluh Nopember | 1 |
| Yufis Azhar | Universitas Muhammadiyah Malang | 1 |
| Cindy Felita Nur Alimah | University of Brawijaya | 1 |
| Fitra Abdurrachman Bachtiar | University of Brawijaya | 1 |
| Iqbal Taufiq Ahmad Nur | University of Brawijaya | 1 |
| Muhammad Rosyid Mubarok | University of Brawijaya | 1 |
| Anisah Ikhsawiyanthi | University of Brawijaya | 1 |
| Pratama Aprilianto | University of Brawijaya | 1 |
| Hanifah Muslimah Az-Zahra | University of Brawijaya | 1 |
| Alfansya Achmad Mulyadi | University of Brawijaya | 1 |
| Meilita Dwi Aryati | University of Brawijaya | 1 |
| Azka Azkiyah | University of Brawijaya | 1 |
| Abdul Harris Wicaksono | University of Brawijaya | 1 |
| Didik Krisnandi | National Research and Innovation Agency | 1 |
| Ana Heryana | National Research and Innovation Agency | 1 |
| Fawwaz Roja Mahardika | University of Brawijaya | 1 |
| Raden Sandra Yuwana | National Research and Innovation Agency | 1 |
| Endang Suryawati | National Research and Innovation Agency | 1 |
| Fatmawati Fatmawati | University of Brawijaya | 1 |
| Tri Afirianto | University of Brawijaya | 1 |
| M. Ro'if | University of Brawijaya | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.