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All Journal Jurnal Manajemen Teknologi Journal of Business and Management The Indonesian Journal of Business Administration Gadjah Mada International Journal of Business Jurnal Minds: Manajemen Ide dan Inspirasi Jurnal Manajemen Atma Jaya Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Manajemen
Deddy P Koesrindartoto
School of Business and Management, Institut Teknologi Bandung, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Pemanfaatan Analisis Sentimen Youtube untuk Prediksi Harga Saham: Studi pada Investor Retail Indonesia Christophorus Bintang Saputra; Koesrindartoto, Deddy Priatmodjo
Jurnal Manajemen Vol. 21 No. 1 (2024): Jurnal Manajemen
Publisher : Fakultas Ekonomi dan Bisnis Universitas Katolik Indonesia Atma Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/jm.v21i1.5184

Abstract

The upswing in engagement from retail investors in the Indonesian stock market aligns with a significant rise in the use of various social media platforms as conduits for stock-related information. In particular, number of content creators shared information about stock in Youtube grows, the information including the effect of corporation actions at stock market. This study sought to leverage sentiment data extracted from particular videos to predict the stock closing prices, especially at the corporate action event using Long Short-Term Memory (LSTM) and Bidirectional LSTM (Bi-LSTM) models. In this study also included several classification algorithm result to explore the accuracy in the prediction models. The result indicate that while sentiment from Youtube serves a viable variable for prediction, the Bi-LSTM model shows better performance compared to the based model in forecasting stock prices surrounding corporate action dates. Furthermore, the combination with classification algorithms shows an improvement in refining predictions, where demonstrate a potential accuracy score when incorporated into the predictive model. This research contributes insights the potential value using sentiment from Youtube platform and machine learning models to predict the time series data, especially in stock market. The findings hold significance for Indonesian retail investors seeking an alternative decision-making tools within the dynamic stock market landscape.
Creating Shared Value: Alternative Business Model Innovation for Financial Products and Services Sector Chaniago, Fajar Ismi; Koesrindartoto, Deddy Priatmodjo
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v10i1.17303

Abstract

This final project focuses on the phenomenon of business lending as a provider and SMEs as customers/ beneficaries. Businesses are too profit-oriented and often overlook shared value in contributing to the profitability of business activities. The final project objectives are to answer the question of how to implement and measure the Creating Shared Value (CSV) programs and to propose a business model canvas to solve the phenomenon of business lending and SMEs for growing together and also give positive impact. With a qualitative approach, the researcher incorporates information from literature analysis on related topics, in-depth interviews with four interviewees, and reports from related companies. Data analysis guided by the triangulation process as a logic of inquiry has been conceptualised by the researcher within this final project, which differs in its goals, purposes, and literature review through the case study research process. Some providers have not yet implemented CSV, and some providers have implemented CSV but not with measurements that relate to business objectives. Besides that, the proposed business model canvas will help providers to implement the CSV concept.
Financial Robo-Advisor: Learning from Academic Literature Hasanah, Eneng Nur; Wiryono, Sudarso Kaderi; Koesrindartoto, Deddy P.
Jurnal Minds: Manajemen Ide dan Inspirasi Vol 10 No 1 (2023): June
Publisher : Management Department, Universitas Islam Negeri Alauddin Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/minds.v10i1.33428

Abstract

Financial Robo-Advisor is the technology that integrates machine learning and self-identification to determine investment decisions. This study explores the financial robo-advisor based on bibliometric analysis and a systematic literature review. The method used three steps: determining the keyword, bibliometric analysis of literature metadata using VOSviewer, then collecting and analysing the articles. The bibliometric analysis results show five cluster keywords defined with different colors. In the network visualization, the robo-advisor connects to other keywords: investment, fintech, and artificial intelligence. Furthermore, the systematic literature review shows that the articles are divided into seven research objectives: (1) Law, Regulation, and Policy; (2) Investment Literate and Education; (3) Offered Services; (4) Present Risk-Portfolio Matching Technology; (5) Optimal Portfolio Methods; (6) Human-Robo Interaction; (7) Theoretical Design and Gap. Furthermore, this study can be used by academicians and practitioners to find out about robo-advisors based on an academic perspective.
Co-Authors Abdurrahman Arroisi Adi Prasetio Raharjo Ayat Hidayat Barli Suryanta Brilliant Asmit Chaniago, Fajar Ismi Christophorus Bintang Saputra Eneng Nur Hasanah, Eneng Nur Erman Sumirat Fahmy Helmy Attamimi Fernando Adventius Geovanno, David Ezra Michael Lintang Khairunisa, Lintang Owen, Jeremy Sudarso Kaderi Wiryono