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Sentimen Analisis Pengguna Media Sosial Berdasarkan Metode Ekstraksi Fitur dan Klasifikasi Putra, Fathiyarizq Mahendra; Hardjita, Pahlevi Wahyu; Tyas, Dyah Aruming
Jurnal Ilmu Komputer Vol 16 No 2 (2023): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIK.2023.v16.i02.p02

Abstract

Analisis sentimen adalah gabungan dari berbagai bidang penelitian seperti NLP (natural language processing), data mining, dan text mining dengan tujuan untuk menemukan pendapat orang yang diungkapkan dalam bentuk teks. Terdapat beberapa tugas dalam analisis sentimen seperti ekstraksi sentimen, klasifikasi sentimen, peringkasan, Terdapat beberapa tantangan dalam melakukan analisis sentimen antara lain sinonim dan polisemi, sarkasme, kalimat majemuk, data tidak terstruktur, Tujuan penulisan ini adalah mereview penelitian lain mengenai Sentimen Analisis berdasarkan dataset, seleksi fitur, dan algoritma klasifikasi dan juga penggunaan multilabel pada sentimen analisis, serta evaluasi hasil akurasi, untuk mendapatkan pendekatan terbaik terhadap pemilihan metode yang digunakan dalam melakukan pemrosesan penambangan
Sentiment Analysis of Tweets on Prakerja Card using Convolutional Neural Network and Naive Bayes Hardjita, Pahlevi Wahyu; Nurochman; Hidayat, Rahmat
IJID (International Journal on Informatics for Development) Vol. 10 No. 2 (2021): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2021.3007

Abstract

The Indonesian government launched the Prakerja (pre-employment) card in the midst of the COVID-19 pandemic, andthe local citizens have voiced their opinions about this controversial program through social media such as Twitter. People’scomments on it can be useful information, and this research tries to analyze the sentiment regarding the Prakerja Card programusing the Convolutional Neural Network and Naive Bayes methods. The main task in this sentiment analysis is analyzing the dataand then classifying them into one of the following classes: positive, negative or neutral. Naive Bayes is an algorithm that is often usedin sentiment analysis research, and the results have been very good. Convolutional neural network (CNN) is a deep learning algorithmthat uses one or more layers commonly used for pattern recognition and image recognition. Having applied these methods, thisresearch found that the CNN model with the GlobalMaxPooling layer is the best model of the other two CNN models. Sentimentanalysis has the best accuracy of 78.5% on the CNN method, and NBC of 76.2% accuracy. The best accuracy result in K-fold withfive classes is 85.4% on the CNN model with a learning rate optimization of 0.00158. While the average accuracy on NBC only reached75.3%