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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 Manajemen Atma Jaya Syntax Literate: Jurnal Ilmiah Indonesia Indonesian Journal of Energy Jurnal Manajemen International Journal of Management, Entrepreneurship, Social Science and Humanities (IJMESH)
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 Energy 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.
Factors Shaping Student Debt Attitudes and Behaviours: A Systematic Review and a Pilot Qualitative Study at an Indonesian Multicultural University Rahadi, Ashri; Koesrindartoto, Deddy Priatmodjo; Wisesa, Anggara
International Journal of Management, Entrepreneurship, Social Science and Humanities Vol. 8 No. 1 (2024): July - December Issue
Publisher : Research Synergy Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31098/ijmesh.v8i1.1259

Abstract

The growing concern over student debt highlights its impact on both individual students and the broader economy. Investigating debt attitudes offers insights into an individual’s predisposition to incur debt, influencing debt levels, repayment discipline, and potential behavior modifications through education. This study employed a thematic analysis conducted using systematically selected literature from global databases to understand factors aligned with various debt attitude spectrums. Four global themes were identified: (I) Personal factors, (II) Social factors, and (III) Behavioral Factors as factors correlated with anti- and pro- debt attitudes and behavior. This research presents a global framework for understanding debt attitudes across diverse factors, which is adaptable to specific cultural contexts. Student debt is a complex issue. To fully understand it, we need to examine a broad range of factors, encompassing not only personal and behavioral aspects but also social perspectives. In addition, certain factors may hold greater significance depending on the context. Practical recommendations are offered for educators and policymakers as considerations for addressing debt.
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.
The Impacts of Emission Reduction Targets in Indonesia Electricity Systems: An Energy-Economy-Environment Model Simulation Irsyad, Muhammad Indra al; Halog, Anthony; Nepal, Rabindra; Koesrindartoto, Deddy P.
Indonesian Journal of Energy Vol. 2 No. 2 (2019): Indonesian Journal of Energy
Publisher : Purnomo Yusgiantoro Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33116/ije.v2i2.42

Abstract

Climate change policy often contradicts the least-cost objective of electricity generation in developing countries. The objective of our study is to propose electricity generation mixes that can meet emission reduction targets in Indonesia. We estimate the optimal generation mix, costs, and emissions from three scenarios, namely existing power plant planning, and 11% and 14% emission reductions in Indonesia’s electricity sector. The estimations are based on linear programming, input-output analysis, and life-cycle analysis, integrated into an agent-based modeling (ABM) platform. The simulation results confirm the existing power plant planning, which is dominated by coal-based power plants, as the lowest-cost scenario in the short-term; however, this scenario also produces the highest emissions. Emission reduction scenarios have lower emissions due to a higher share of renewables and, therefore, the Indonesian electricity system is robust from fossil fuel price increases. In the long-term, costs incurred in the emission reduction scenarios will be lower than electricity generation costs under the existing power plant planning. Our findings should be a basis for re-evaluating energy policies, power plant planning, and the research agenda in Indonesia.
Co-Authors Abdurrahman Arroisi Adi Prasetio Raharjo Anggara Wisesa Ayat Hidayat Barli Suryanta Brilliant Asmit Chaniago, Fajar Ismi Christophorus Bintang Saputra Erman Sumirat Fahmy Helmy Attamimi Fernando Adventius Geovanno, David Ezra Michael Halog, Anthony Irsyad, Muhammad Indra al Lintang Khairunisa, Lintang Nepal, Rabindra Owen, Jeremy Rahadi, Ashri