Optimalisasi Pemrosesan Text Dengan NLP Pada Klasifikasi Sentimen Berbasis SVM (Studi Kasus Prediksi Harga Saham)
Keywords:
harga saham, NLP, analisa sentimentAbstract
One of the common business opportunities today is the business of buying and selling shares. Stock price movements are an important thing that is quite influential in this business strategy. But unfortunately, in this business there are still problems, namely it is still relatively difficult in making an accurate model of stock price movement. Some factors that influence the movement of stock prices are the history of price and market sentiment towards stock issuers. Comment data on stock issuers on social media can be used as material used in extracting market sentiment. The main objective of this research is to build a model of predicting stock price movements, using sentiment analysis methods. The data used in the sentiment analysis process is a related topic and discussion about 10 issuers in Indonesia that are incorporated in LQ45 shares. In addition, this study also measures the accuracy and precision of the proposed model. Comparing the average accuracy and precision values of each model used is 0.70% and 0.60%, this value is better than models that do not use NLP as an algorithm for word processing
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