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All Journal STRING (Satuan Tulisan Riset dan Inovasi Teknologi)
Nabila Cahyani
Universitas Nasional
Computer Science & IT Mathematics

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Analisis Sentimen Kepuasan Investasi Pada Masa Pandemi dengan Metode Support Vector Machine dan K-Nearest Neighbors Nabila Cahyani; Fauziah Fauziah
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 7, No 2 (2022)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/string.v7i2.13937

Abstract

Investment is an activity to invest assets in certain people or institutions in order to get profits for a certain period of time. Investment can not only be made for the short term, but also be used as saving for the future use. Investment has now become a trend since the pandemic started. Many people jump into this activity with the hope of getting very promising profits. Both teenagers and adults have tried to plunge into the investment activity. However, some people still don't understand how to invest properly, so that they must take is quite high risks that create a negative impact on the profits. During the current pandemic, it is worsened by the inflation on the value of the Composite Stock Price Index that can fluctuate along with various things. This study aims to review how the public responds in making investments during the current pandemic. The research uses the Support Vector Machine and K-Nearest Neighbors methods. Seeing the use of the Support Vector Machine and K-Nearest Neighbors methods, it can be concluded that SVM is better than KNN, with the SVM accuracy value of 96.84% and that of KNN of 95.74% with a accuracy difference of 1.10% between the two methods.
Co-Authors Fauziah Fauziah