Page 113 - E-Skripsi Analisis Sentimen Terhadap Aplikasi Sapawarga Jabar Super Apps Pada Ulasan Google Play Store

https://doi.org/10.35925/j.multi.2020.3.26

Kristiyanti, D. A., Putri, D. A., Indrayuni, E., Nurhadi, A., & Umam, A. H.
(2023). Twitter Sentiment Analysis Using Support Vector Machine and Deep

Learning Model in E-Learning Implementation During The Covid-19

Outbreak. 020033. https://doi.org/10.1063/5.0128685
Laoh, E., Surjandari, I., & Prabaningtyas, N. I. (2019). Enhancing Hospitality

Sentiment Reviews Analysis Performance Using SVM N-grams Method.
2019 16th International Conference on Service Systems and Service

Management, ICSSSM 2019. https://doi.org/10.1109/ICSSSM.2019.8887662

Luthfi, M. A., Audry, ;, Arifin, S., Hafidz, F., & Renggana, R. (2023). Analisis
Pengembangan Kapasitas Rukun Warga (Rw) Dalam Pemanfaatan Aplikasi

Sapawarga Di Kelurahan Isola Kota Bandung. | Prosiding Nasional FISIP
Universitas Islam Syekh Yusuf |, 1(1), 71–79.

Mahmood, A. T., Kamaruddin, S. S., Naser, R. K., & Nadzir, M. M. (2020). A
Combination of Lexicon and Machine Learning Approaches for Sentiment

Analysis on Facebook. Journal of System and Management Sciences, 10(3).

https://doi.org/10.33168/JSMS.2020.0310
Maree, M., Eleyat, M., Rabayah, S., & Belkhatir, M. (2023). A hybrid Composite

Features Based Sentence Level Sentiment Analyzer. IAES International
Journal of Artificial Intelligence, 12(1).

https://doi.org/10.11591/ijai.v12.i1.pp284-294

Mariana, N., Nugroho, I., Saefurrohman, S., & Utomo, A. P. (2023). The Impact
of System and Information Quality on User Satisfaction and Continuance

Intention: An Analysis of Online Motorcycle Taxi (Ojek-Online)
Applications. Scientific Journal of Informatics, 10(2).

https://doi.org/10.15294/sji.v10i2.43830

Mestika, C. J., Selan, O. M., & Qadafi, I. M. (2023). Menjelajahi Teknik-Teknik
Supervised Learning untuk Pemodelan Prediktif Menggunakan Python.

https://jurnalmahasiswa.com/index.php/biikma
Moreo, A., Romero, M., Castro, J. L., & Zurita, J. M. (2012). Lexicon-based

Comments-oriented News Sentiment Analyzer system. Expert Systems with

99