Sentiment Analysis on Platform X (Twitter) Towards The 2024 General Election Using The Probabilistic Neural Network Algorithm

Aaron Rumondor(1*), Fitrah Rumaisa(2),

(1) Universitas Widyatama, Indonesia
(2) Universitas Widyatama, Indonesia
(*) Corresponding Author

Abstract


Sentiment analysis is the process of analyzing an opinion or public opinion regarding a phenomenon that has occurred, is currently occurring or will occur. Sentiments that are commonly discussed are the public's assessment of an object positively, negatively or neutrally. Twitter is the most popular media used to express all forms of public emotions and opinions in the form of tweets or text. The issues discussed in it include many events, such as the 2024 general election which will be held in Indonesia. This media is easily accessible to many people to show other people's opinions regarding existing phenomena. This research discusses the topic after the 2024 general election with opinions based on three sentiment classes, namely positive, neutral and negative. The aim of this research is to build a sentiment analysis system by applying the Probabilistic Neural Network algorithm as a classification model. The method used is data collection, cleaning, preprocessing, TF-IDF word weighting, labeling, classification models, and evaluation of results. The data used amounted to 2002 data with a division of 1035 positive tweets, 693 neutral tweets and 274 negative tweets. The program was built using Google Colaboratory and the Python programming language. Testing was carried out with 3 (three) comparisons, namely 90:10, 70:30, and 50:50. By comparing 90% training data and 10% testing data, the greatest model accuracy was obtained with a value of 88.42% and taking into account the evaluation using the confusion matrix and precision parameters of 89%, recall of 88%, and f1-score of 88%. Evaluation was also carried out for website-based applications on new data with an accuracy value of 66%.


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References


Pratama, Rizky. 2022. Hate Speech: Deviations from the ITE Law, Freedom of Opinion and the Values of Dignified Justice. Pelita Harapan University. Tangerang.

Najiyah, Ina. 2021. Sentiment Analysis of Covid-19 using Probabilistic Neural Network and TF-IDF Methods. Accessed 21 February 2024 from https://ejurnal.ars.ac.id/index.php/jti/article/view/488.

Puad, Salim. 2023. Analysis of Public Sentiment on Twitter Regarding the 2024 General Election Using the Naïve Bayes Algorithm. Accessed 21 February 2024 from https://ejournal.itn.ac.id/index.php/jati/article/download/6920/4114/.

Yasin, H., & Ispriyanti, D. 2017. Classification of Baby Birth Weight Data Using Weighted Probabilistic Neural Network (WPNN) (Case Study at Sultan Agung Islamic Hospital Semarang). Statistics Media. Semarang.

Indonesia. Law Number 15 of 2011 concerning General Election Organizers. State Secretariat. Jakarta.

Revoupedia Editorial Team. 2024. What is Sentiment Analysis. Revoupedia.com. Jakarta.

Scientific Journal Center Editorial Team. 2021. Definition, History and Benefits of Twitter for Millennial Young People. Center for Scientific Journals. Medan.

Davis, Wes. 2023. Twitter is being rebranded as X (Twitter changed its name to X). Retrieved February 24, 2024 from https://www.theverge.com/2023/7/23/23804629/twitters-rebrand-to-x-may-actually-be happening-soon.

Suripto. 2022. Pre-Processing and Classification Techniques in Data Science. Binus University. Jakarta

Anzir, Oumfa. 2019. Application of the Probabilistic Neural Network Method for Classifying the Pekanbaru City Family Hope Program. Sultan Syarif Islamic University. Pekanbaru.




DOI: http://dx.doi.org/10.30645/jurasik.v9i2.830

DOI (PDF): http://dx.doi.org/10.30645/jurasik.v9i2.830.g803

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