Analisis Dinamika Harga Saham Yang Dipengaruhi Oleh Analisis Sentimen Di Media Sosial Menggunakan Algoritma Support Vector Machine

Tando, Galileo Antonio (2022) Analisis Dinamika Harga Saham Yang Dipengaruhi Oleh Analisis Sentimen Di Media Sosial Menggunakan Algoritma Support Vector Machine. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pasar saham merupakan salah satu instrumen investasi yang diminati oleh masyarakat karena potensi keuntungan yang tinggi, namun memiliki risiko yang cukup besar. Pergerakan harga saham seringkali dipengaruhi oleh berbagai faktor, salah satunya adalah sentimen publik di media sosial. Penelitian ini bertujuan untuk menganalisis dinamika harga saham dengan mempertimbangkan analisis sentimen dari media sosial menggunakan algoritma Support Vector Machine (SVM). Data sentimen diambil dari platform media sosial, kemudian diproses untuk menentukan polaritas sentimen (positif, negatif, atau netral). Algoritma SVM digunakan untuk memodelkan hubungan antara sentimen media sosial dan pergerakan harga saham. Hasil penelitian menunjukkan bahwa terdapat korelasi antara sentimen media sosial dengan dinamika harga saham, dan penggunaan algoritma SVM memberikan hasil prediksi yang cukup akurat dalam menggambarkan pola pergerakan harga saham berdasarkan sentimen yang ada.
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The stock market is one of the investment instruments that is in demand by the public due to its high profit potential, but it has significant risks. Stock price movements are often influenced by various factors, one of which is public sentiment on social media. This study aims to analyze stock price dynamics by considering sentiment analysis from social media using the Support Vector Machine (SVM) algorithm. Sentiment data is taken from social media platforms and then processed to determine the sentiment polarity (positive, negative, or neutral). The SVM algorithm is used to model the relationship between social media sentiment and stock price movements. The results show that there is a correlation between social media sentiment and stock price dynamics, and the use of the SVM algorithm provides quite accurate prediction results in describing stock price movement patterns based on existing sentiment.

Item Type:	Thesis (Other)
Additional Information:	RSMa 519.53 Tan a-1 2022
Uncontrolled Keywords:	Analisis sentimen. Support Vector Machine. Sentiment analysis. Support Vector Machine.
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	08 Jun 2026 04:46
Last Modified:	08 Jun 2026 04:46
URI:	http://repository.its.ac.id/id/eprint/133627

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