ANALISIS SENTIMEN OPINI PUBLIK MENGENAI HARGA MINYAK BBM DAN MINYAK GORENG PADA TWITTER MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN)

PRATAMA, MUHAMMAD TIANSYAH and Samsuryadi, Samsuryadi and Anggina, Primanita (2023) ANALISIS SENTIMEN OPINI PUBLIK MENGENAI HARGA MINYAK BBM DAN MINYAK GORENG PADA TWITTER MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK (CNN). Undergraduate thesis, Sriwijaya University.

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Abstract

The rapid growth of social media has made it easier for people to express their opinions on online platforms such as blogs, web forums, and social media platforms like Instagram, Facebook, and Twitter. Information and comments spread on Twitter encompass various types, including positive, negative, and neutral remarks. Currently, extensive research has been conducted in the field of Natural Language Processing (NLP), specifically focusing on sentiment analysis. Based on this, a software tool has been developed to predict sentiment analysis using the Convolutional Neural Network (CNN) method. The dataset used in this research consists of tweets related to the topic of rising cooking oil and fuel prices from July 27, 2022, to August 18, 2022, totaling 601 tweets. The data was processed into four variations of datasets, based on data splitting ratios of 70:30 and 60:40, and different pre-processing stages, either through all Pre-Processing processes or only through tokenizing.The research results indicate that the model trained using data with a 70:30 data splitting scheme and undergoing full Pre-Processing has the best performance, with an accuracy value of 0.63055, precision of 0.57934, recall of 0.68477, and F1-Score of 0.55286

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Analisis Sentimen, Convolutional Neural Network (CNN), Pra-Pengolahan, Tweet
Subjects:	T Technology > T Technology (General) > T57-57.97 Applied mathematics. Quantitative methods > T57.5 Data processing Cf. HF5548.125+ Business data processing Operations research. Systems analysis
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Tiansyah Pratama
Date Deposited:	01 Aug 2023 08:46
Last Modified:	01 Aug 2023 08:46
URI:	http://repository.unsri.ac.id/id/eprint/122532

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