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All Journal Journal of Computing Theories and Applications Heca Journal of Applied Sciences Leuser Journal of Environmental Studies Ekonomikalia Journal of Economics Journal of Educational Management and Learning Infolitika Journal of Data Science Indatu Journal of Management and Accounting The International Journal of Financial Systems Grimsa Journal of Business and Economics Studies Journal of Future Artificial Intelligence and Technologies
Idroes, Ghalieb Mutig
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Social Sciences Other

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Digital Transformations in Vocational High School: A Case Study of Management Information System Implementation in Banda Aceh, Indonesia Idroes, Rinaldi; Subianto, Muhammad; Zahriah, Zahriah; Afidh, Razief Perucha Fauzie; Irvanizam, Irvanizam; Noviandy, Teuku Rizky; Sugara, Dimas Rendy; Mursyida, Waliam; Zhilalmuhana, Teuku; Idroes, Ghalieb Mutig; Maulana, Aga; Nurleila, Nurleila; Sufriani, Sufriani
Journal of Educational Management and Learning Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i2.128

Abstract

This study examines the digital transformation in vocational education through the implementation of a Management Information System (MIS) in Banda Aceh, Indonesia. Focused on enhancing educational administration and decision-making, the study provides insightful analysis on the integration of MIS in State Vocational High School (SMK), specifically SMKN 1 and SMKN 3 in Banda Aceh. A purposive sampling method was employed for usability testing. The questionnaire-based usability test revealed high reliability and positive user responses across multiple indicators. Data analysis affirmed the system's high user satisfaction, effectiveness, and ease of use. Despite limitations, the study highlights the significant potential of well-designed MIS in improving operational efficiency and user satisfaction in educational settings. Future research directions include expanding the sample size, conducting longitudinal studies, incorporating qualitative methods, and exploring the impact on educational outcomes, to enhance the generalizability and depth of understanding regarding the role of MIS in education.
A Model-Agnostic Interpretability Approach to Predicting Customer Churn in the Telecommunications Industry Noviandy, Teuku Rizky; Idroes, Ghalieb Mutig; Hardi, Irsan; Afjal, Mohd; Ray, Samrat
Infolitika Journal of Data Science Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v2i1.199

Abstract

Customer churn is critical for businesses across various industries, especially in the telecommunications sector, where high churn rates can significantly impact revenue and growth. Understanding the factors leading to customer churn is essential for developing effective retention strategies. Despite the predictive power of machine learning models, there is a growing demand for model interpretability to ensure trust and transparency in decision-making processes. This study addresses this gap by applying advanced machine learning models, specifically Naïve Bayes, Random Forest, AdaBoost, XGBoost, and LightGBM, to predict customer churn in a telecommunications dataset. We enhanced model interpretability using SHapley Additive exPlanations (SHAP), which provides insights into feature contributions to predictions. Here, we show that LightGBM achieved the highest performance among the models, with an accuracy of 80.70%, precision of 84.35%, recall of 90.54%, and an F1-score of 87.34%. SHAP analysis revealed that features such as tenure, contract type, and monthly charges are significant predictors of customer churn. These results indicate that combining predictive analytics with interpretability methods can provide telecom companies with actionable insights to tailor retention strategies effectively. The study highlights the importance of understanding customer behavior through transparent and accurate models, paving the way for improved customer satisfaction and loyalty. Future research should focus on validating these findings with real-world data, exploring more sophisticated models, and incorporating temporal dynamics to enhance churn prediction models' predictive power and applicability.
Credit Card Fraud Detection for Contemporary Financial Management Using XGBoost-Driven Machine Learning and Data Augmentation Techniques Noviandy, Teuku Rizky; Idroes, Ghalieb Mutig; Maulana, Aga; Hardi, Irsan; Ringga, Edi Saputra; Idroes, Rinaldi
Indatu Journal of Management and Accounting Vol. 1 No. 1 (2023): September 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v1i1.78

Abstract

The rise of digital transactions and electronic payment systems in modern financial management has brought convenience but also the challenge of credit card fraud. Traditional fraud detection methods are struggling to cope with the complexities of contemporary fraud strategies. This study explores the potential of machine learning, specifically the XGBoost (eXtreme Gradient Boosting) algorithm, combined with data augmentation techniques, to enhance credit card fraud detection. The research demonstrates the effectiveness of these techniques in addressing imbalanced datasets and improving fraud detection accuracy. The study showcases a balanced approach to precision and recall in fraud detection by leveraging historical transaction data and employing techniques like Synthetic Minority Over-sampling Technique-Edited Nearest Neighbors (SMOTE-ENN). The implications of these findings for contemporary financial management are profound, offering the potential to bolster financial integrity, allocate resources effectively, and strengthen customer trust in the face of evolving fraud tactics.
Assessing the Linkage Between Sustainability Reporting and Indonesia’s Firm Value: The Role of Firm Size and Leverage Hardi, Irsan; Idroes, Ghalieb Mutig; Hardia, Natasha Athira Keisha; Fajri, Irfan; Furqan, Nurul; Noviandy, Teuku Rizky; Utami, Resty Tamara
Indatu Journal of Management and Accounting Vol. 1 No. 1 (2023): September 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v1i1.79

Abstract

Sustainability reporting is widely regarded as an essential factor in enhancing a firm's value. In light of its importance, this study examines the impact of three sustainability reporting indicators - sustainability reporting disclosure, sustainability reporting index, and sustainability reporting score - on firm value, as well as determining the role of firm size and leverage. Utilizing a sample of 200 companies listed on the Indonesia Stock Exchange (IDX) during the research period from 2013 to 2021, the results of panel data regression reveal that two of the three indicators have a significant impact on firm value. Specifically, the sustainability reporting index exerts a positive impact, while the sustainability reporting score has a negative effect on firm value. Furthermore, path analysis estimations reveal that sustainability reporting mediates the positive relationship between firm size and firm value. This study's empirical findings underscore that sustainability reporting plays a pivotal role in shaping a firm's value, and these insights can be valuable for businesses and investors seeking to understand the financial implications associated with sustainability reporting.
Dynamic Impact of Inflation and Exchange Rate in Indonesia's Top 10 Market Capitalization Companies: Implications for Stock Prices Hardi, Irsan; Idroes, Ghalieb Mutig; Utami, Resty Tamara; Dahlia, Putri; Mirza, Muhammad Alfin Falha; Humam, Rais Aulia; Chairunnisa, Rizka; Hardia, Natasha Athira Keisha; Mahdani, Rimal
Indatu Journal of Management and Accounting Vol. 1 No. 2 (2023): December 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v1i2.110

Abstract

Macroeconomic factors are widely believed to have a crucial role in affecting a company's financial health and, ultimately, its stock price. The study addresses this important issue by investigating the long-term impact of inflation and exchange rates on firm stock prices. This study adopts both panel and cross-firm modeling, along with a dynamic approach, which no prior study has ever conducted in Indonesia’s top 10 market capitalization companies. It utilizes monthly data spanning from September 2008 to August 2023. To generate insights into long-term effects, the study applies the Dynamic Ordinary Least Squares (DOLS) method, with a robustness check using the Fully-Modified Ordinary Least Squares (FMOLS) method. The econometric estimations yield results that are consistent with the hypotheses, indicating that the rise in inflation levels has a negative effect, while the strengthening of the domestic currency in exchange rates positively influences firm stock prices in the long term. This implies that investors should carefully assess and navigate inflationary environments, consider diversifying their portfolios across industries and international markets, and maintain a long-term perspective when making investment decisions in the unique context of Indonesia's market landscape.
Business Confidence in Indonesia: Which Macroeconomic Factors Have Long-Term Impact? Hardi, Irsan; Ali, Najabat; Duwal, Niroj; Devi, N. Chitra; Mardayanti, Ulfa; Idroes, Ghalieb Mutig
Indatu Journal of Management and Accounting Vol. 2 No. 1 (2024): June 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v2i1.203

Abstract

Business confidence refers to the level of optimism or pessimism that business owners have about the prospects of their companies and the overall economy. Thus, the focus of this study is to examine the long-term impact of various macroeconomic factors—economic growth, government expenditure, interest rates, inflation, exchange rates, and the composite stock price index—on the business confidence index in Indonesia by utilizing monthly data from January 2009 to December 2022. We employ Dynamic Ordinary Least Squares (DOLS) and Fully-Modified Ordinary Least Squares (FMOLS) as the main methods, with Canonical Cointegrating Regressions (CCR) as a robustness check method. The study also utilizes pairwise Granger causality tests for a comprehensive analysis. The findings indicate that all macroeconomic factors significantly impact the business confidence index in the long term across all methodologies. Specifically, economic growth, inflation, and the composite stock price index exert a positive impact, while government expenditure, interest rates, and exchange rates indicate a negative impact on the business confidence index. This evidence emphasizes the importance for businesses to diligently monitor macroeconomic trends and understand the patterns in these indicators so that companies can better anticipate changes in business sentiment. Taking a long-term perspective when making strategic decisions and investments is also advisable, recognizing that the influence of macroeconomic factors on business confidence may be more pronounced over time.
Classifying Beta-Secretase 1 Inhibitor Activity for Alzheimer’s Drug Discovery with LightGBM Noviandy, Teuku Rizky; Nisa, Khairun; Idroes, Ghalieb Mutig; Hardi, Irsan; Sasmita, Novi Reandy
Journal of Computing Theories and Applications Vol. 1 No. 4 (2024): JCTA 1(4) 2024
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.10129

Abstract

This study explores the utilization of LightGBM, a gradient-boosting framework, to classify the inhibitory activity of beta-secretase 1 inhibitors, addressing the challenges of Alzheimer's disease drug discovery. The study aims to enhance classification performance by focusing on overcoming the limitations of traditional statistical models and conventional machine-learning techniques in handling complex molecular datasets. By sourcing a dataset of 7298 compounds from the ChEMBL database and calculating molecular descriptors for each compound as features, we employed LightGBM in conjunction with a set of carefully selected molecular descriptors to achieve a nuanced analysis of compound activities. The model's efficiency was benchmarked against traditional machine-learning algorithms, revealing LightGBM's superior accuracy (84.93%), precision (87.14%), sensitivity (89.93%), specificity (77.63%), and F1-score (88.17%) in classifying beta-secretase 1 inhibitor activity. The study underscores the critical role of molecular descriptors in understanding drug efficacy, highlighting LightGBM's potential in streamlining the virtual screening process. Conclusively, the findings advocate for LightGBM's adoption in computational drug discovery, offering a promising avenue for advancing Alzheimer's disease therapeutic development by facilitating the identification of potential drug candidates with enhanced precision and reliability.
Consumer Confidence and Economic Indicators: A Macro Perspective Hardi, Irsan; Ray, Samrat; Duwal, Niroj; Idroes, Ghalieb Mutig; Mardayanti, Ulfa
Indatu Journal of Management and Accounting Vol. 2 No. 2 (2024): December 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v2i2.241

Abstract

This study examines the impact of the determinants of consumer confidence in Indonesia, one of the largest consumer markets in the world. Various macroeconomic factors are assessed, including economic growth, government expenditure, the consumer price index, interest rates, unemployment, and stock price index, using monthly data from January 2009 to December 2022. The study employs the Autoregressive Distributed Lag (ARDL) model as the primary method, with robustness checks using Fully Modified Ordinary Least Squares (FMOLS) and Canonical Cointegrating Regressions (CCR). The results indicate that all selected factors significantly influence consumer confidence, particularly from a long-term perspective. Economic growth and unemployment have a positive impact, while government expenditure, the consumer price index, interest rates, and stock prices exert a negative effect. These findings suggest that businesses should align their strategies with economic trends to capitalize on periods of strong consumer sentiment and mitigate risks during downturns. Simultaneously, policymakers should prioritize effectively managing key macroeconomic factors to sustain and enhance overall consumer confidence.
Starting a Business: A Focus on Construction Permits, Electricity Access, and Property Registration Hardi, Irsan; Nghiem, Xuan-Hoa; Suwal, Sunil; Ringga, Edi Saputra; Marsellindo, Rio; Idroes, Ghalieb Mutig
Indatu Journal of Management and Accounting Vol. 2 No. 2 (2024): December 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v2i2.245

Abstract

Efficient processes for construction permits, electricity access, and property registration are critical to fostering entrepreneurship and economic growth. Delays, high costs, and bureaucratic inefficiencies in these areas pose significant barriers to business start-ups. This study examines the impact of these factors on starting a business, highlighting their role in shaping formal economic activity and business dynamics. By applying methods such as the Generalized Linear Model (GLM), Robust Least Squares (RLS), and Quantile Regressions (QR) to data from 213 countries and cities featured in the World Bank’s Doing Business 2019 (DB19) and Doing Business 2020 (DB20) reports, this paper demonstrates that all three factors significantly and positively impact starting a business. Notably, a comparison of results between DB19 and DB20 reveals that the magnitude of these influences decreased in DB20, with some effects becoming less significant or even insignificant compared to DB19. This phenomenon is most apparent in countries with middle-to-high starting a business scores. The findings suggest that shocks like the COVID-19 pandemic may have reduced the relevance of these factors in DB20, as the increased risks associated with starting a business during the pandemic likely overshadowed these considerations. Overall, the results indicate that streamlining construction permits, improving electricity access, and simplifying property registration processes could significantly enhance entrepreneurial activity, drive economic growth, and foster a more dynamic business environment.
The Impact of Credit Access on Economic Growth in SEA Countries Idroes, Ghalieb Mutig; Maulidar, Putri; Marsellindo, Rio; Afjal, Mohd; Hardi, Irsan
Indatu Journal of Management and Accounting Vol. 2 No. 2 (2024): December 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijma.v2i2.256

Abstract

Access to credit serves as a vital catalyst for economic growth, allowing individuals, enterprises, and governments to fund investments, maintain consumption stability, and encourage productive endeavors. Economic growth is fundamental to sustainable development, enhancing living standards, and promoting innovation. This study investigates the impact of credit access on economic growth in Southeast Asia (SEA) countries using monthly data from 2014 to 2020. By applying the Fully Modified Ordinary Least Squares (FMOLS) method, along with robustness checks using the Dynamic Ordinary Least Squares (DOLS) technique, this study includes essential control variables such as capital, labor, and technology. The results reveal that credit access has a positive impact on economic growth, while capital and technology also contribute positively to economic growth. Conversely, labor shows a negative impact on economic growth within the region. These results are consistent across both the FMOLS and DOLS analyses. Based on these findings, Southeast Asian policymakers ought to facilitate credit accessibility by making loan applications more straightforward, minimizing bureaucratic obstacles, and providing lower interest rates, especially for small enterprises and marginalized communities. Moreover, encouraging financial institutions to lend more liberally and utilizing digital platforms can expand access. Additionally, investing in technology, improving capital formation, and tackling labor market challenges will more effectively align with the region's growth path.
Co-Authors Afjal, Mohd Agustina, Maulidar Ali, Najabat Amalina, Faizah Apriliansyah, Feby Attari, Muhammad Umer Quddoos Ayu Puspitasari, Ayu Bani, Nor Yasmin binti Mhd Bruyn, Chané de Chairunnisa, Rizka Çoban, Mustafa Necati Dahlia, Putri Devi, N. Chitra Duwal, Niroj Eddy Gunawan, Eddy Eko Suhartono Emran, Talha Bin Fadila, Sintia Fajri, Irfan Fazli, Qalbin Salim Fijay, Ade Habya Fikri, Mumtaz Kemal Fitriyani Fitriyani Furqan, Nurul Ghazi Mauer Idroes Hadiyani, Rahmilia Hafizah, Iffah Hamaguchi, Yoshihiro Hapzi Ali Hardia, Natasha Athira Keisha Hidayatullah, Ferdy HUMAM, RAIS AULIA Idroes, Ghifari Maulana Idroes, Rinadi Iin Shabrina Hilal Irsan Hardi Irvanizam, Irvanizam Kadri, Mirzatul Khairan Khairan Khairul, Mhd Khairun Nisa Kusumo, Fitranto Lala, Andi Majid, M. Shabri Abd Majumder, Shapan Chandra Mardayanti, Ulfa Marsellindo, Rio Maulana, Aga Maulana, Ar Razy Ridha Maulidar, Putri Mirza, Muhammad Alfin Falha Muhammad Subianto Mursyida, Waliam Nghiem, Xuan-Hoa Nurleila, Nurleila Pernici, Andreea Phonna, Rahmatil Adha Prasetio, Rasi Ray, Samrat Razief Perucha Fauzie Afidh Rimal Mahdani Rinaldi Idroes Ringga, Edi Saputra RR. Ella Evrita Hestiandari Salimullah, Abul Hasnat Muhammed Saputra, Fachri Eka Saputra, Jumadil Sasmita, Novi Reandy Sikdar, Asaduzzaman Sofyan Syahnur Sofyan, Rahmi Souvia Rahimah Stancu, Stelian sufriani, sufriani Sugara, Dimas Rendy Sugeng Santoso Suhendrayatna Suhendrayatna Suriani Suriani Suwal, Sunil Syahyana, Ahmad T. Zulham Teuku Rizky Noviandy Thahira, Zia Utami, Resty Tamara Wiranatakusuma, Dimas Bagus Zahriah, Zahriah Zhilalmuhana, Teuku Zikra, Naswatun