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Quantitative Economics and Management Studies
Published by PT. Mattawang Mediatama Solution
ISSN : -     EISSN : 27226247     DOI : https://doi.org/10.35877/qems
Core Subject : Economy, Science, Education,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics
Journal of Quantitative Economics and Management Studies (QEMS) is an international peer-reviewed open-access journal dedicated to interchange for the results of high-quality research in all aspects of economics, management, business, finance, marketing, accounting. The journal publishes state-of-art papers in fundamental theory, experiments, and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion, and concise conclusion. As our commitment to the advancement of science and technology, the QEMS follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekomomi dan Ekonometrika
Articles 595 Documents
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Transformation of Noodle Processing Business Productivity through the Role of Business Managers and Innovation in Bondowoso Regency Ach. Humaidi; Nurhidayah; Muhammad Ridwan Basalama
Quantitative Economics and Management Studies Vol. 6 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3963

Abstract

Indonesia’s MSME sector faces growing competition and changing consumer demands. Traditional food processors must improve operational efficiency to stay competitive. However, many still rely on conventional management methods that may not meet today’s market challenges. This study examines the interrelationships between management practices, innovation adoption, and operational performance within food processing MSMEs in East Java. Using Structural Equation Modeling-Partial Least Squares (SEM-PLS), the research analyzed census data from 70 registered enterprises. Primary data were collected through validated questionnaires measuring management capabilities, innovation implementation, and performance outcomes across operational dimensions. The findings reveal significant positive relationships among all variables. Management practices demonstrate substantial direct influence on operational performance (path coefficient = 0.798, p < 0.001) while fostering innovation adoption (path coefficient = 0.504, p < 0.001). Innovation significantly enhances performance outcomes (path coefficient = 0.633, p < 0.001). Crucially, mediation analysis confirms innovation as a significant mediator in the management-performance relationship, explaining how managerial effectiveness translates into operational improvements. The model explains 63.6% of performance variance, with effect size analysis confirming large management effects on performance (f² = 1.372) and moderate effects on innovation (f² = 0.340). Results indicate that effective management creates environments conducive to innovation adoption, subsequently driving operational efficiency. The research establishes innovation as a critical mediating mechanism, suggesting enterprise development programs should integrate management capacity building with innovation facilitation to maximize outcomes.
Assessing the Impact of Web-Based e-Performance Applications on Employee Motivation and Discipline: A Quantitative Study in Batanghari Regency Naibaho, Ronald; Ahmad Asyhadi; Gunardi; Mardiana
Quantitative Economics and Management Studies Vol. 6 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3964

Abstract

This study aims to analyze the effect of using the web-based e-Performance (e-Kinerja) application on the motivation and work discipline of Civil Servants (ASN) in Batanghari Regency. A quantitative approach was employed in this study using an explanatory research design. Data were collected through questionnaires distributed to 187 civil servants across various Regional Government Organizations (OPD), and analyzed using multiple linear regression. The validity and reliability tests showed that all research instruments were valid and reliable. Classical assumption tests also indicated that the data met the requirements of normality, showed no multicollinearity, and were free from heteroscedasticity. The results revealed that the use of the e-Performance application had a positive and significant influence, both simultaneously and partially, on the motivation and work discipline of civil servants. The coefficient of determination (R²) indicated that 36.2% of the variance in motivation and 32.9% of the variance in work discipline could be explained by the use of the e-Performance variable. This application is considered effective in increasing employee expectations regarding performance incentives and strengthening data-based supervision in shaping more orderly and professional work behavior. Furthermore, e-Performance contributes to the transformation of civil servant work culture towards a more transparent, accountable, and results-oriented bureaucracy. These findings offer theoretical implications for the enhancement of technology-based performance management literature, as well as practical implications for local governments in promoting bureaucratic reform through the digitalization of personnel systems.
Green Public Service Innovation: Integrating Environmental Values into Local Government Service Delivery Yasmeardi, F.; Rizke, Dian; Kosassy, Siti Mutia; J., Syamsu; Marwandizal, Marwandizal
Quantitative Economics and Management Studies Vol. 6 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3965

Abstract

This study explores the integration of environmental values into public service innovation commonly referred to as green public service innovation within the context of local government service delivery in Padang, West Sumatra. Amid escalating environmental challenges and the urgency of achieving Sustainable Development Goals (SDGs), local governments are increasingly expected to move beyond efficiency and adopt eco-conscious service models. This research employs a quantitative approach using Structural Equation Modeling–Partial Least Squares (SEM-PLS) to examine five key variables: organizational commitment, organizational culture, community participation, green leadership, and green public service innovation. The findings reveal that organizational commitment, organizational culture, and community participation all have significant direct impacts on green public service innovation. Furthermore, green leadership not only directly influences innovation but also plays a moderating role by strengthening the effect of organizational commitment on innovation outcomes. The results emphasize that green innovation in the public sector requires more than technology adoption it demands aligned leadership, an enabling institutional culture, and active community involvement. In Padang’s case, local wisdom and environmental awareness present opportunities for designing inclusive and contextualized green innovations. Strong leadership that embeds environmental values into strategic planning and operational systems significantly enhances institutional resilience and citizen trust. The research contributes to public administration literature by offering empirical support for the systemic relationships between organizational factors and sustainable service delivery. It also provides actionable insights for local governments seeking to institutionalize environmental values in public services.
Business Valuation Analysis Using the Discounted Cash Flow (DCF) and Price to Earnings Ratio (PER) Methods: Case Study on Telecommunication Subsector Companies Listed on Indonesia Stock Exchange (IDX) Radius, Radius; Sriwati, Sriwati
Quantitative Economics and Management Studies Vol. 6 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3970

Abstract

This study aims to analyze business valuation in telecommunication subsector companies listed on the Indonesia Stock Exchange (IDX) using two valuation methods, namely Discounted Cash Flow (DCF) and Price to Earnings Ratio (PER). The data used in this study were obtained from the company's financial statements and stock market data. The results showed that based on the DCF method, PT Indosat Tbk (ISAT) and PT Smartfren Telecom Tbk (FREN) are overvalued, while PT XL Axiata Tbk (EXCL) and PT Telkom Indonesia (Persero) Tbk (TLKM) are undervalued. Meanwhile, based on the PER method, only ISAT shows an undervalued condition, while other companies are also classified as undervalued compared to the industry average. The differences in results between the two methods shows that the selection of valuation methods affects the interpretation of a company’s stock value.
Implementation of Binary Logistic Regression and Chi-Squared Automatic Interaction Detection (CHAID) to Recipients of the Prosper Family Card Program in Makassar City Rais, Zulkifli; Ruliana; Indrayasaro
Quantitative Economics and Management Studies Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3981

Abstract

The binary logistic regression analysis method is a classification method that forms a relationship between a dichotomous dependent variable and an independent variable, while the chi-squared automatic interaction detection (CHAID) analysis method is a decision tree classification method for studying the relationship between independent variables and variables. bound by using the chi-square test statistic as the main tool. This research aims to determine the magnitude of the resulting accuracy value and what factors influence recipients of the Prosperous Family Card program in Makassar City based on National Socio-Economic Survey data in 2022 using the binary logistic regression method and the chi-squared automatic interaction detection method (CHAID). The results of this research using the binary logistic regression method show that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with an accuracy value of 75.78%, while the chi-squared automatic interaction detection (CHAID) method also shows that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with the resulting accuracy value of 75%. Based on the accuracy values of the two methods, the binary logistic regression method is the appropriate method for classifying recipients of the Prosperous Family Card program in Makassar City
Backpropagation Neural Network Method For The Classification of Districts/Cities Based On Macro Socio-Economic Indicators In The Province Of South Sulawesi Rais, Zulkifli; Sudarmin; Syahputra, Akbar
Quantitative Economics and Management Studies Vol. 6 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3982

Abstract

Classification is a way of grouping objects based on the characteristics possessed by the objects of classified. One of the developing classification methods is the backpropagation neural network. This study aims to look at the descriptive and classification results of the District/City Macro Socioeconomic Indicators in South Sulawesi Province. The data set comprises 24 observations with 9 variables, namely population density, poverty line, Gini ratio, open unemployment rate, life expectancy, average length of schooling, labor force participation rate, life growth rate, and GRDP at current prices. A model with a total of 9 hidden layers and a learning rate of 0.002 is obtained with an accuracy of 70%, precision of 70%, recall of 100%, and F1 score of 87%.
A Comparative Analysis of Asymmetric Transmission across Monetary Policy Regimes on Interest Rate Pass-Through in Indonesia’s Banking Sector Stefano, David; Wibowo, Buddi
Quantitative Economics and Management Studies Vol. 6 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3985

Abstract

This study examines the interest rate pass-through mechanism in Indonesia by analyzing how changes in the central bank policy rate are transmitted to commercial bank lending and deposit rates. The research focuses on two monetary policy regimes implemented by Bank Indonesia, namely the BI 7-Day Reverse Repo Rate and the new BI Rate introduced after December 2023. Using monthly time-series data from August 2016 to January 2025, the study employs the Error Correction Model and Mean Adjusted Lag to evaluate both the short-term and long-term dynamics of interest rate transmission. The Johansen Cointegration Test is also applied to identify the existence of long-run equilibrium relationships between the policy rate and banking interest rates. The results show that the pass-through process is asymmetric, with lending rates responding more quickly to policy rate increases than deposit rates do to policy rate decreases. The analysis also reveals variation in the speed and completeness of pass-through across the different policy regimes. Specifically, the new BI Rate demonstrates a shorter lag in transmission, suggesting improved responsiveness of the interest rate channel under the updated framework. These findings highlight the evolving nature of monetary policy effectiveness in Indonesia’s financial system and provide a better understanding of interest rate dynamics in an emerging market context.
Blue Economy Financing: Sustainable Aquaculture in Indonesia Lestari, Dhoya Safira Tresna; Purwanto, Setiyo
Quantitative Economics and Management Studies Vol. 6 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3991

Abstract

The aquaculture sector is a strategic component in Indonesia's marine development, but its sustainability faces serious challenges such as environmental degradation, limited access to finance, and low adoption of environmentally friendly practices. This study aims to analyze the influence of Blue Economy Financing (BEF) on Sustainable Aquaculture (SA), considering the mediating role of environmental, social and governance (ESG) factors. The study uses an explanatory quantitative approach using the Partial Least Squares–Structural Equation Modelling (PLS-SEM) method, based on sample data of 120 seaweed farmers in the coastal area of South Sulawesi. The results of this study show that BEF strongly supports the sustainability of sustainable aquaculture. However, ESG mediation has no effect on increasing the role of BEP in the development of SA. Although the model has adequate predictive capabilities for sustainability, the influence of BEF on ESG is not strong enough to explain and convince the public, investors and the government for the development of SA. To optimize the role of ESG as a catalyst for sustainability, supporting strategies such as institutional strengthening, technological innovation, and integrated policy interventions are needed. This research confirms that BEF is an important instrument in encouraging sustainability transformation in the aquaculture sector. These findings provide practical implications for the development of a more adaptive blue financing scheme in supporting Indonesia's sustainable marine development agenda.
Motivation as a Bridge between Creativity, Environment, and Capital in Shaping Entrepreneurial Interest among Students Bado, Basri; Isma, Andika; Dewantara, Hajar; Raharimalala, Soussou; Adio, Matthew Olufemi
Quantitative Economics and Management Studies Vol. 6 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3992

Abstract

This study aims to examine the influence of creativity, environment, and capital on entrepreneurial interest, with motivation acting as a mediating variable among students of the Faculty of Economics and Business at a university. The sampling technique used was proportional random sampling, and data were collected through questionnaires distributed directly to respondents. The population consisted of active students in the faculty, with a total sample of 109 respondents. Data analysis was conducted using simple linear regression with the assistance of SPSS version 26. The results show that motivation has a significant direct effect on entrepreneurial interest and serves as the primary mediating factor in this study. Creativity was found to have a positive and significant influence on motivation and indirectly contributed substantially to entrepreneurial interest through motivation. The environment emerged as the strongest factor affecting both motivation and entrepreneurial interest. In contrast, capital had the weakest influence on entrepreneurial interest compared to the other variables. Overall, the research model explains 99.7% of the variability in students’ entrepreneurial interest, emphasizing motivation as the key mediating variable linking creativity, environment, and capital to entrepreneurial aspirations.
Does AI Sentiment Affect Stock Returns? Evidence from Indonesia’s Banking Sector Junanta, Geryan; Rokhim, Rofikoh
Quantitative Economics and Management Studies Vol. 6 No. 3 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3995

Abstract

This study investigates the heterogeneous effects of AI-related investor sentiment on the stock returns of Indonesian banks. Using a correlation-weighted AI Sentiment Index (AI-SVI) derived from Google Trends, panel regressions reveal that only fintech-driven banks show significant responsiveness to AI sentiment, while conventional, independent digital, and conglomerate-backed banks do not. These findings are supported by a supplementary investor perception survey, which confirms that market participants associate visible and strategic AI adoption primarily with fintech institutions. The results suggest that AI sentiment can act as a behavioral signal of valuation in emerging financial markets, but its effectiveness depends on how innovation is perceived and communicated. Policymakers and investors should be cautious in interpreting sentiment-driven movements, especially in sectors with uneven technological maturity.

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