Analisis Sentimen E-Learning X Terhadap Antarmuka Pengguna Menggunakan Kombinasi Multinomial Naive Bayes dan Pendekatan Design Thinking

Penulis

  • Baenil Huda Universitas Kristen Satya Wacana, Salatiga dan Universitas Buana Perjuangan Karawang, Karawang
  • Irwan Sembiring Universitas Kristen Satya Wacana, Salatiga
  • Iwan Setiawan Universitas Kristen Satya Wacana, Salatiga
  • Danny Manongga Universitas Kristen Satya Wacana, Salatiga
  • Hindriyanto Dwi Purnomo Universitas Kristen Satya Wacana, Salatiga
  • Hendry Hendry Universitas Kristen Satya Wacana, Salatiga
  • Ahmad Fauzi Universitas Buana Perjuangan Karawang, Karawang
  • April Lia Hananto Universitas Buana Perjuangan Karawang, Karawang
  • Tukino Tukino Universitas Buana Perjuangan Karawang, Karawang

DOI:

https://doi.org/10.25126/jtiik.1147686

Abstrak

Penelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap antarmuka e-learning X menggunakan kombinasi Multinomial Naive Bayes dan pendekatan Design Thinking. Permasalahan yang dihadapi adalah banyaknya feedback negatif terkait antarmuka pengguna yang dianggap kurang intuitif. Data sentimen dari ulasan pengguna diklasifikasikan menggunakan algoritma Multinomial Naive Bayes, sementara Design Thinking digunakan untuk merancang solusi antarmuka yang lebih user-friendly. Hasilnya menunjukkan bahwa metode ini efektif meningkatkan sentimen positif pengguna, dengan perbaikan signifikan dalam pengalaman dan kepuasan pengguna terhadap antarmuka e-learning X, Serta rekomendasi untuk pengembangan aplikasi e-learning.

 

Abstract

 

This research aims to analyze user sentiment towards the e-learning interface X using a combination of Multinomial Naive Bayes and Design Thinking approaches. The problem faced was the large number of negative feedback regarding the user interface which was considered less intuitive. Sentiment data from user reviews is classified using the Multinomial Naive Bayes algorithm, while Design Thinking is used to design more user-friendly interface solutions. The results show that this method is effective in increasing positive user sentiment, with significant improvements in user experience and satisfaction with the X e-learning interface As well as recommendations for developing e-learning applications.

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Biografi Penulis

  • Baenil Huda, Universitas Kristen Satya Wacana, Salatiga dan Universitas Buana Perjuangan Karawang, Karawang
    Sistem Informasi

Referensi

ALYOUSSEF, I. Y. 2023. Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3), e13751. https://doi.org/10.1016/j.heliyon.2023.e13751

BAYES, N., MACHINE, S. V., & SHORT-, L. 2023. JURNAL RESTI Sentiment Analysis of Public Acceptance of Covid-19 Vaccines Types in. 5(158), 2–6.

BROWN, K. E., FLORES, M. J., MACKECHNIE, M. C., RODARTE, P., O’MARR, J., SHEARER, D. W., & TOOGOOD, P. 2023. Novel e-learning platform for orthopaedic training in LMICs: A descriptive review of the IGOT portal. Surgery Open Science, 13, 24–26. https://doi.org/10.1016/j.sopen.2023.04.003

BUDIAWAN ZULFIKAR, W., RIALDY ATMADJA, A., & PRATAMA, S. F. 2023. Sentiment Analysis on Social Media Against Public Policy Using Multinomial Naive Bayes. Scientific Journal of Informatics, 10(1), 25–34. https://doi.org/10.15294/sji.v10i1.39952

EZALDEEN, H., BISOY, S. K., MISRA, R., & ALATRASH, R. 2023. Semantics aware intelligent framework for content-based e-learning recommendation. Natural Language Processing Journal, 3(November 2022), 100008. https://doi.org/10.1016/j.nlp.2023.100008

FERLIAMO, A. F., HANGGARA, B. T., MURSITYO, Y. T., BRAWIJAYA, U., & KORESPONDENSI, P. 2023. USER INTERFACE AND USER EXPERIENCE DESIGN ON NOTARY OPERATIONAL APPLICATION PROTOTYPE USING ETHNOGRAPHIC FIELD STUDIES AND USER CENTERED DESIGN METHOD. 10(2). https://doi.org/10.25126/jtiik.2023106637

FRANSISKA, S., & IRHAM GUFRONI, A. 2020. Sentiment Analysis Provider by.U on Google Play Store Reviews with TF-IDF and Support Vector Machine (SVM) Method. Scientific Journal of Informatics, 7(2), 2407–7658. http://journal.unnes.ac.id/nju/index.php/sji

HIDAYANTO, A. N., M, K. Y. P., & RANDY, R. 2023. JURNAL RESTI Quality on Playstore Data : A Case of Indodax. 5(158), 1–6.

IRYANTI, E., ZULFIQAR, L. O. M., KUSUMAWARDANI, S. S., & HIDAYAH, I. 2022. Pengukuran Kepuasan Pengguna E-Learning Menggunakan Metode Evaluasi Heuristik dan System Usability Scale. Jurnal Teknologi Informasi Dan Ilmu Komputer, 9(3), 469. https://doi.org/10.25126/jtiik.2022924631

KARLSEN, K., ARONSEN, C., BJØRNNES, T. D., HARBERG, T. B., HALLAND, A. N., HOLAND, T., JAKOBSEN, L., KORNBAKK, L., KVALSHAUG, B. I., LIAN, H., NYGÅRD, C., SOLSVIK, A. K., TRØMBORG, E., & EMAUS, N. 2023. Integration of e-learning approaches in a post-pandemic learning environment – Norwegian nursing students’ recommendations from an action research study. Heliyon, 9(2). https://doi.org/10.1016/j.heliyon.2023.e13331

LIN, H. M., WU, J. Y., LIANG, J. C., LEE, Y. H., HUANG, P. C., KWOK, O. M., & TSAI, C. C. 2023. A review of using multilevel modeling in e-learning research. Computers and Education, 198(February), 104762. https://doi.org/10.1016/j.compedu.2023.104762

NASUTION, W. S. L., & NUSA, P. 2021. UI/UX Design Web-Based Learning Application Using Design Thinking Method. ARRUS Journal of Engineering and Technology, 1(1), 18–27. https://doi.org/10.35877/jetech532

O’CONNOR, S., WANG, Y., COOKE, S., ALI, A., KENNEDY, S., LEE, J. J., & BOOTH, R. G. 2023. Designing and delivering digital learning (e-Learning) interventions in nursing and midwifery education: A systematic review of theories. Nurse Education in Practice, 69(September 2022), 103635. https://doi.org/10.1016/j.nepr.2023.103635

SAYAF, A. M. 2023. Adoption of E-learning systems: An integration of ISSM and constructivism theories in higher education. Heliyon, 9(2), e13014. https://doi.org/10.1016/j.heliyon.2023.e13014.

Sistem, R. 2021. Seleksi Fitur menggunakan Algoritma Particle Swarm Optimization pada. 1(10), 469–475.

Sistem, R., Informasi, S., Informasi, F. T., Kristen, U., & Wacana, S. 2021. Jurnal resti. 1(10), 474–482.

Sistem, R., Kepuasan, K., Passenger, A., Teknik, F., & Bangsa, U. P. 2021. JURNAL RESTI Perbandingan Optimasi Feature Selection pada Naïve Bayes untuk. 1(10), 527–533.

Sistem, R., ZAMACHSARI, F., SARAGIH, G. V., & GATA, W. 2021. Analisis Sentimen Pemindahan Ibu Kota Negara dengan Feature Selection. 1(10), 504–512.

SUKARSA, I. M., PIARSA, I. N., & LINGGAR SUKARTA, E. B. 2021. Goal Directed Design Method Application on UI/UX of Dua Mata Mobile Apps. Scientific Journal of Informatics, 8(2), 183–193. https://doi.org/10.15294/sji.v8i2.30216

UMAR, N., NUR, M. A., & INFORMATIKA, T. 2022. JURNAL RESTI Application of Naïve Bayes Algorithm Variations On Indonesian General Analysis Dataset for Sentiment Analysis. 5(158), 585–590.

ZAHRA, M. N., & KRAUGUSTEELIANA, K. 2023. ANALISIS KUALITAS PERFORMA APLIKASI DIGITAL BANKING X MENGGUNAKAN FRAMEWORK ISO 25010 EVALUATION OF QUALITY OF PERFORMANCE DIGITAL BANKING X APPLICATION USING FRAMEWORK ISO 25010. 10(3). https://doi.org/10.25126/jtiik.2023106326

Diterbitkan

26-08-2024

Terbitan

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Ilmu Komputer

Cara Mengutip

Analisis Sentimen E-Learning X Terhadap Antarmuka Pengguna Menggunakan Kombinasi Multinomial Naive Bayes dan Pendekatan Design Thinking. (2024). Jurnal Teknologi Informasi Dan Ilmu Komputer, 11(4), 895-902. https://doi.org/10.25126/jtiik.1147686