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Vol. 5 No. 1 (2024) • Articles
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Analisis Sentimen Opini Mahasiswa Terhadap Aplikasi Portal Mahasiswa UTY Menggunakan Metode Naïve Bayes Classifier

Agus Ardiyanto
Universitas Teknologi Yogyakarta
Enny Itje Sela
Universitas Teknologi Yogyakarta
Published: January 10, 2024 Pages: 525-540
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Abstract

University Technology of Yogyakarta (UTY) has released the UTY Student Portal Application since 2020 which is an improvement in services to support student academic activities. The UTY Student Portal application was developed by Puskom from Yogyakarta Technology University. The UTY Student Portal application is a system designed and built to manage data related to academic information which includes student data, lecturer data, lecture results records, lecture schedules and so on. The presence of this Student Portal Application has given rise to various comments from its users, namely UTY students. Seeing this problem, the researchers conducted research on student opinions regarding the UTY Student Portal Application using the Naïve Bayes Classifier. This research uses the Python programming language. Based on the results of the discussion, it was found that the accuracy level was 93% in the training process and the testing accuracy was around 65.2% with a distribution of training and test data of 70%:30% from 150 opinion text data. This model creation experienced overfitting, because the resulting testing accuracy was much smaller than the training accuracy.

Keywords:
Naive Bayes UTY Student Portal Application Sentiment Analysis
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Author Biographies
Agus Ardiyanto Universitas Teknologi Yogyakarta

Program Studi Informatika, Fakultas Sains & Teknologi, Universitas Teknologi Yogyakarta, Kabupaten Sleman, Provinsi Daerah Istimewa Yogyakarta

Enny Itje Sela Universitas Teknologi Yogyakarta

Program Studi Informatika, Fakultas Sains & Teknologi, Universitas Teknologi Yogyakarta, Kabupaten Sleman, Provinsi Daerah Istimewa Yogyakarta

How to Cite
Ardiyanto, A., & Sela, E. I. (2024). Analisis Sentimen Opini Mahasiswa Terhadap Aplikasi Portal Mahasiswa UTY Menggunakan Metode Naïve Bayes Classifier. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 5(1), 525-540. https://doi.org/10.35870/jimik.v5i1.508
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References
Total: 16 References
  1. Kaka, D. L., Pati, G. K., & Rato, K. W. (2023). Analisis Sentimen Komentar SIAKAD Menggunakan Metode Naive Bayes Classifier. JURNAL KRIDATAMA SAINS DAN TEKNOLOGI, 5(02), 266-277. DOI: https://doi.org/10.53863/kst.v5i02.933.
  2. Deni, D. K., & Ferida, F. Y. (2023). Usability Testing Penggunaan Menu Kartu Hasil Studi Di Website Sistem Informasi Akademik Universitas Teknologi Yogyakarta. Jurnal Teknologi dan Manajemen Industri Terapan, 2(I), 41-52. DOI: https://doi.org/10.55826/tmit.v2iI.57.
  3. Locarso, G. K. (2022). Analisis Sentimen Review Aplikasi Pedulilindungi Pada Google Play Store Menggunakan NBC. JTIK (Jurnal Teknik Informatika Kaputama), 6(2), 353-361.
  4. Mujahid, T. A., & itje Sela, E. (2019). Analisis Perbandingan Rule Pakar dan Decision Tree J48 Dalam Menentukan Jumlah Produksi Kain Tenun Menggunakan Metode Fuzzy Tsukamoto. JURIKOM (Jurnal Riset Komputer), 6(5), 501-505. DOI: http://dx.doi.org/10.30865/jurikom.v6i5.1510.
  5. Sekaran, U. (2011). Research Methods for Business: Metodologi Penelitian Untuk Bisnis, Buku 1.
  1. Deolika, A., Kusrini, K., & Luthfi, E. T. (2019). Analisis pembobotan kata pada klasifikasi text mining. (JurTI) Jurnal Teknologi Informasi, 3(2), 179-184. DOI: https://doi.org/10.36294/jurti.v3i2.1077.
  2. Zalukhu, P. S., Handhayani, T., & Sitorus, M. (2023). Analisis Sentimen terhadap Kenaikan BBM di Indonesia pada Media Sosial Twitter Menggunakan Metode Naïve Bayes. Simtek: jurnal sistem informasi dan teknik komputer, 8(1), 65-69. DOI: https://doi.org/10.51876/simtek.v8i1.177.
  3. Sari, K. (2022). ANALISIS SENTIMEN REVIEW UNTUK POPULARITAS MARKETPLACE INDONESIA MENGGUNAKAN METODE WEBSCRAPING= SENTIMENT REVIEW ANALYSIS FOR INDONESIAN MARKETPLACE POPULARITY USING WEBSCRAPING METHOD (Doctoral dissertation, Universitas Hasanuddin).
  4. Hutagalung, J. S. (2023). ANALISIS SENTIMEN KEUANGAN (DATA FIQA AND FINANCIAL PHRASEBANK) MENGGUNAKAN ALGORITMA LOGISTIC REGRESSION DAN SUPPORT VECTOR MACHINE. Jurnal Indonesia: Manajemen Informatika dan Komunikasi, 4(3), 1654-1669. DOI: https://doi.org/10.35870/jimik.v4i3.404.
  5. Dewi, N. K. (2023). Identifikasi Berita Hoax dengan Menerapkan Algoritma Text Mining. Journal of Informatics, Electrical and Electronics Engineering, 2(3), 65-74. DOI: https://doi.org/10.47065/jieee.v2i3.888.
  6. Luqyana, W. A., Cholissodin, I., & Perdana, R. S. (2018). Analisis Sentimen Cyberbullying Pada Komentar Instagram dengan Metode Klasifikasi Support Vector Machine. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2(11), 4704-4713.
  7. Syarifuddinn, M. (2020). Analisis Sentimen Opini Publik Mengenai Covid-19 Pada Twitter Menggunakan Metode Naïve Bayes Dan Knn. Inti Nusa Mandiri, 15(1), 23-28. DOI: https://doi.org/10.33480/inti.v15i1.1347.
  8. Parasati, W., Bachtiar, F. A., & Setiawan, N. Y. (2020). Analisis Sentimen Berbasis Aspek pada Ulasan Pelanggan Restoran Bakso President Malang dengan Metode Naïve Bayes Classifier. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 4(4), 1090-1099.
  9. Simanjuntak, I. Z. (2022). Analisa Kombinasi Algoritma Stemming Dan Algoritma Soundex Dalam Pencarian Kata Bahasa Indonesia. Informasi dan Teknologi Ilmiah (INTI), 10(1), 24-30.
  10. Rozi, I. F., Hamdana, E. N., & Alfahmi, M. B. I. (2018). Pengembangan Aplikasi Analisis Sentimen Twitter Menggunakan Metode Naïve Bayes Classifier (Studi Kasus SAMSAT Kota Malang). Jurnal Informatika Polinema, 4(2), 149-149. DOI: https://doi.org/10.33795/jip.v4i2.164.
  11. Kurniawan, D., & Yasir, M. (2022). Optimization Sentimen Analysis using CRISP-DM and Naive Bayes Methods Implemented on Social Media. Cyberspace: Jurnal Pendidikan Teknologi Informasi, 6(2), 74-85. DOI: http://dx.doi.org/10.22373/cj.v6i2.12793.
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