4 research outputs found

    Prediksi Sentimen Investor Pasar Modal Di Jejaring Sosial Menggunakan Text Mining

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    The decline in optimism for capital market investors is one of the financial impacts on the business world that arose from the SARS-COVID19 pandemic. This event was reflected in a decrease in trading volume followed by a sharp drop in the JCI on the Indonesia Stock Exchange starting March 2020. Thus, a slowdown in the economic recovery resulting from the pandemic is reflected in investor sentiment in the capital market. On the one hand, the rapid development of the internet in Indonesia has triggered the investor's activities in the information searching prior buy and sell securities, mostly use online platforms, which contribute to influencing investor preferences and sentiment. This study conducted a qualitative examination of the features/terms of stock investment in the capital market and collected them in a compact dictionary (lexicon). Therefore, lexicon-based investor opinion extraction was extracted from Twitter, followed by the text sentiment analysis, and forming a classification model based on Naive Bayes and Decision Tree. This research output shows that the polarity of capital market investor sentiment is optimistic with the sentiment features that often appear, namely "cuan", "bearish," "serok", "copet", "untung", "cut loss", and "nyangkut." Meanwhile, the Decision Tree classification model provides better performance.Keywords                        :  investor, lexicon, social network, stock exchange, text miningCorrespondence to        : [email protected] Penurunan optimisme investor pasar modal adalah salah satu dampak keuangan pada dunia usaha yang timbul akibat pandemi SARS-COVID19. Hal ini tercermin dari turunnya volume perdagangan yang diikuti penurunan tajam IHSG di Bursa Efek Indonesia mulai Maret 2020. Sehingga kekhawatiran atas perlambatan pemulihan ekonomi sebagai dampak pandemi, tercermin dari sentimen investor di pasar modal. Di satu sisi, perkembangan internet di Indonesia yang pesat, memicu kecenderungan aktivitas investor dalam pencarian informasi sebelum membeli dan menjual surat berharga  secara online, turut berkontribusi dalam mempengaruhi preferensi dan sentimen investor. Penelitian ini menggali ekspektasi investor yang tercermin pada sentimen investasi, dimana pasar modal sebagai salah satu barometer penting perekonomian suatu negara. Kajian ini mengeksplorasi fitur/terms investasi saham yang kerap muncul di pasar modal dan mengumpulkannya dalam kamus leksikon. Kemudian, dilakukan ekstraksi opini investor berbasis leksikon yang digali dari jejaring sosial Twitter, dilanjutkan dengan tahap text mining yaitu menganalisis sentimen, dan membentuk model klasifikasi berbasis Naive Bayes dan Decision Tree. Keluaran penelitian ini  menunjukkan bahwa polaritas sentimen investor pasar modal adalah positif dengan fitur sentimen yang sering muncul yaitu “cuan”, “bearish”, “serok”, “copet”, “untung”, dan “cut loss”. Sedangkan model klasifikasi Decision Tree memberikan performansi akurasi yang kebih baik.Kata Kunci                  : Analisis sentimen; Investor; Leksikon; Text mining; Twitte

    Generalized averaged Gaussian quadrature and applications

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    A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

    MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

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    Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

    7th International Conference on Higher Education Advances (HEAd'21)

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    Information and communication technologies together with new teaching paradigms are reshaping the learning environment.The International Conference on Higher Education Advances (HEAd) aims to become a forum for researchers and practitioners to exchange ideas, experiences,opinions and research results relating to the preparation of students and the organization of educational systems.Doménech I De Soria, J.; Merello Giménez, P.; Poza Plaza, EDL. (2021). 7th International Conference on Higher Education Advances (HEAd'21). Editorial Universitat Politècnica de València. https://doi.org/10.4995/HEAD21.2021.13621EDITORIA
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