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#JURNAL SKRIPSI SISTEM INFORMASI NUSA MANDIRI FREE#RABIT's spirit is to disseminate articles published are as free as possible. The author warrants that the article is original, written by stated author(s), has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author and free of any third party rights, and that any necessary written permissions to quote from other sources have been obtained by the author(s). #JURNAL SKRIPSI SISTEM INFORMASI NUSA MANDIRI LICENSE#The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. By submitting the article/manuscript of the article, the author(s) accept this policy. Please find the rights and licenses in RABIT : Jurnal Teknologi dan Sistem Informasi Univrab. Yang, “Understanding the disharmony between weight normalization family and weight decay: ε−shifted L2 regularizer,” arXiv, vol. Anggraeny, “Implementasi Algoritma CNN untuk Klasifikasi Citra Lahan dan Perhitungan Luas,” Inform. Guo, “How Far Does BERT Look At: Distance-based Clustering and Analysis of BERT’s Attention,” pp. Fadlurrahman, “Penerapan SMOTE untuk Mengatasi Imbalance Class dalam Klasifikasi Television Advertisement Performance Rating Menggunakan Artificial Neural Network,” JEPIN (Jurnal Edukasi dan Penelit. #JURNAL SKRIPSI SISTEM INFORMASI NUSA MANDIRI SOFTWARE#133–138, 2020.Īinurrohmah, “Akurasi Algoritma Klasifikasi pada Software Rapidminer dan Weka,” vol. Pahlevi, “Klasifikasi Opportunity Menggunakan Algoritma C4.5, C4.5 dan Naive Bayes Berbasis Particle Swarm Optimization,” Inti Nusa Mandiri, vol. Straka, “75 Languages, 1 Model: Parsing Universal Dependencies Universally,” arXiv, pp. Wu, “Target-dependent sentiment classification with BERT,” IEEE Access, vol. Peters et al., “Deep contextualized word representations,” NAACL HLT 2018 - 2018 Conf. Ruder, “Universal language model fine-tuning for text classification,” ACL 2018 - 56th Annu. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” NAACL HLT 2019 - 2019 Conf. Fiza Asyrofi Ramadhan, “Sentiment analysis for go-jek on google play store,” J. Xiaolin, “Comparison research on text pre-processing methods on twitter sentiment analysis,” IEEE Access, vol. Wening, “Handling Imbalance Data in Classification Model with Nominal Predictors,” Int. Tran Quoc Vinh, “Effective text data preprocessing technique for sentiment analysis in social media data,” Proc. Domenech, “Big Data sources and methods for social and economic analyses,” Technol. ![]() Youn, “Word clustering based on POS feature for efficient twitter sentiment analysis,” Human-centric Comput. Sherratt, “Sentiment Analysis for E-Commerce Product Reviews in Chinese Based on Sentiment Lexicon and Deep Learning,” IEEE Access, vol. Khan, “Rating Generation of Video Games using Sentiment Analysis and Contextual Polarity from Microblog,” Proc. Potenza, “Problematic Online Gaming and The COVID-19 Pandemic,” J. This research process stage is data scrapping through the google play store, and using Bidirectional Encoder Representations from Transformers (BERT) as the machine learning model.ĭ. But, it is hard to get studies that explore about the extraction features and the deep learning models that fit with this case, especially in the business game. An autonomus sentiment analysis classification process is required to reduce human error. ![]() This research focused on sentiment analysis with the purpose to find out whether the respected review that scraps from google play store has a neutral, positive or negative sentiment so it will be helpful for afterward game improvement. Genshin Impact is one of the well-known game that developed by miHoYo. Over the years, online game have become inseparable thing for most of us, especially in the widespread economic disruption caused by the Covid-19. Recently, sentiment analysis by using online reviews and messages has become a popular research issue in Natural Langauage Processing field. By huge improvement of Internet Services on social networking, there are a lot data that were streamly made in every time. ![]()
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