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Ansari Saleh Ahmar
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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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Transformational Leadership and Work‒Life Balance Effects on Job Satisfaction: Organizational Commitment as a Mediator Ridhani, Aulia; Rahmawati, Rini
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.qems3930

Abstract

Employee job satisfaction is a critical determinant of organizational performance, with transformational leadership and work‒life balance emerging as significant factors. However, the literature reveals inconsistent relationships between these variables across different organizational contexts, indicating the need for further investigation into potential mediating variables. This study investigated the impact of transformational leadership and work‒life balance on job satisfaction, with organizational commitment serving as an intervening variable at PTs. PLN (Persero) Marabahan Customer Service Unit. Using a quantitative methodology, data were collected via questionnaires from 58 technical employees selected through purposive sampling. Variables were assessed via Likert scales, and analysis was conducted via structural equation modeling-partial least squares (SEM-PLS) facilitated by Smart PLS-4 software. The findings revealed that both transformational leadership style and work‒life balance positively and significantly influenced job satisfaction among technical personnel. Furthermore, organizational commitment was demonstrated to function effectively as a mediating variable in the relationship between the independent variables (transformational leadership and work-life balance) and the dependent variable (job satisfaction) and to directly enhance employee satisfaction levels. These findings suggest that an inspiring leadership style and a well-balanced work-life environment not only directly improve job satisfaction but also do so through increased organizational commitment, ultimately contributing to employee well-being and productivity.
Regression Analysis of Panel Data on Gross Enrolment Rate (GER) At Junior High School and Equivalent Education Levels in South Sulawesi Province in 2018-2022 Elisa, Nur; Aidid, Muhammad Kasim; Meliyana, Sitti Masyitah
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.qems3932

Abstract

Panel data regression is a combination of time series and cross section data. This research aims to determine the factors that influence the gross participation rate in South Sulawesi Province using panel data regression analysis. The data used is data from 24 districts/cities in South Sulawesi province from 2018 to 2022 which was obtained through the website of the South Sulawesi Provincial Central Statistics Agency. There are three models in panel data regression analysis, namely the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). Based on the model selection carried out by carrying out the Chow Test, Hausman Test, and Lagrange Multiplier Test, the best model was obtained, namely the Random Effect Model. The equation of this model is Yit = 82,818 + 0,1485X1it − 0,0784X2it + 0,0053X3it + 0,0011X4it. Based on the results of panel data regression analysis, it was found that the variables that had a significant effect on the Gross Enrollment Rate in South Sulawesi province were the student to teacher ratio (X2), and population density (X4).
Green Entrepreneurship in MSMEs: Marketing Challenges and Opportunities in the Context of Sustainability Mukti Diapepin; Naufal Raid; Seven Putra; Yurismen Effendi; Yenni Jufri
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.qems3934

Abstract

This study aims to analyze the influence of Green Marketing Strategies (GMS), Environmental Awareness (EA), and Government and Institutional Support (GIS) on Green Entrepreneurship Readiness (GER) among MSME actors in Nagari Sungai Batang, Agam Regency, West Sumatra. The research adopts a quantitative approach using Structural Equation Modeling – Partial Least Squares (SEM-PLS) analysis method. Data were collected through questionnaires from 60 MSME actors divided into three sectors: culinary, handicrafts, and agrotourism. Additionally, the Multi-Group Analysis (PLS-MGA) technique was employed to identify differences in influence across sectors. The results show that the three exogenous variables GMS, EA, and GIS simultaneously have a significant effect on GER, with an R² value of 0.62. Environmental Awareness emerges as the most influential variable. The PLS-MGA analysis revealed significant differences based on business sectors. The culinary and craft sectors show strong influences from GMS and EA, while the agrotourism sector is more affected by GIS. These findings highlight the importance of sector-specific and contextual policy approaches in empowering MSMEs through green entrepreneurship. This research contributes to the development of green entrepreneurship literature and provides an empirical basis for government and supporting institutions to design more adaptive programs in face of the challenges and opportunities of green marketing. Collaborative efforts among business actors, educational institutions, and local stakeholders are necessary to strengthen MSME readiness in facing an increasingly sustainability-oriented economic transition.
A Seasonal ARIMA (SARIMA) Model for Forecasting Domestic Passenger Traffic at Sultan Hasanuddin Airport Meliyana, Sitti Masyitah; Hafid, Hardianti; Mar'ah, Zakiyah; Muthahharah, Isma
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.qems3935

Abstract

The growth of the domestic aviation industry in Indonesia has led to a significant increase in passenger numbers, particularly at major airports such as Sultan Hasanuddin Airport. Accurate forecasting of passenger traffic is essential for effective planning and resource allocation. This study aims to develop a suitable time series model to forecast the number of domestic air passengers departing from Sultan Hasanuddin Airport. Using monthly passenger data from January 2019 to April 2024 obtained from the Indonesian Badan Pusat Statistik (BPS), the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied. The modelling process followed the Box-Jenkins methodology, involving data exploration, stationarity testing, model identification, parameter estimation, diagnostic checking, and model validation. Among several candidate models, the ARIMA (0,1,1)(0,0,1)12 model was identified as the most appropriate, producing normally distributed, independent residuals and yielding a Mean Absolute Percentage Error (MAPE) of 4.5%. The results demonstrate that the SARIMA model provides a reliable tool for forecasting short-term domestic passenger flows at the airport.
Forecasting Indonesia’s Wholesale Price Index (WPI) Using the Holt's Exponential Smoothing Method Muthahharah, Isma; Meliyana, Sitti Masyitah; Mar’ah, Zakiyah
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.qems3937

Abstract

The Index of Wholesale Price (WPI) is a key benchmark in analyzing price movements at the wholesale level as it can affect the economic stability of a country. This research purpose to forecast the movement of WPI in Indonesia using Holt's Exponential Smoothing technique, which is effective in analyzing time series data that show trend patterns. This research utilizes secondary data obtained from the BPS for the period 2020-2024. The analysis is carried out by determining the optimal value of α and β parameters using trial and error techniques. Furthermore, the forecasting process is carried out using the best parameters that have been obtained. Based on the analysis results, the combination of parameters α = 0.9 and β = 0.8 provides a Mean Absolute Percentage Error (MAPE) value of 0.22%, which indicates a very good level of forecasting accuracy. WPI forecasting for the year 2025 shows a consistent upward pattern, reflecting a consistent increase in WPI previous historical trends. The results of this study can be a reference in making price and wholesale trade policies by the government and related parties in the economic sector.
Implementation K-Medoids Algorithm for Clustering Indonesian Provinces by Poverty and Economic Indicators Hafid, Hardianti; Meliyana, Sitti Masyitah; Muthahharah, Isma; Mar’ah, Zakiyah
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.qems3940

Abstract

Regional development disparities in Indonesia remain one of the main challenges in formulating national development policies. This study aims to classify the 38 provinces in Indonesia based on four key indicators: the percentage of the population living in poverty, Gross Regional Domestic Product (GRDP) per capita, the open unemployment rate, and the Human Development Index (HDI), using the K-Medoids algorithm. This method was chosen due to its robustness to outliers and its ability to produce representative clusters. The data used are secondary data obtained from the Central Bureau of Statistics (BPS). The analysis process began with data standardization, determination of the optimal number of clusters using the Elbow and Silhouette methods, followed by clustering implementation and result interpretation. The analysis results identified four main clusters with distinct socioeconomic characteristics. Cluster 1 reflects provinces with moderate conditions, Cluster 2 represents more developed provinces, Cluster 3 highlights regions facing significant development challenges, and Cluster 4 consists of provinces with the most underdeveloped socioeconomic conditions. These findings indicate that the K-Medoids algorithm is effective in identifying inter-provincial disparity patterns and can serve as a foundation for formulating more targeted and inclusive development policies.
The Influence of Financial Capital and Financial Management on the Performance of MSMEs at the Mentaya Shooping Center in Sampit Glorianismus, Filoshopia Yasni; Sambung, Roby; Ani Mahrita; Pratiwi Hamzah
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.qems3946

Abstract

This study aims to analyze the influence of financial capital and financial management on the performance of Micro, Small, and Medium Enterprises (MSMEs) at the Mentaya Shopping Center in Sampit, Central Kalimantan. Using a quantitative approach with a survey method, data were collected from 82 MSME respondents and analyzed through Structural Equation Modeling using SmartPLS 4.0. The research reveals that both financial capital and financial management have a positive and significant effect on MSME performance, both individually and simultaneously. The coefficient of determination (R²) value of 0.612 indicates that 61.2% of the variation in MSME performance is explained by the two independent variables. The findings show that most MSMEs rely on internal capital and face challenges accessing external financing. At the same time, financial management practices—especially in recording, reporting, and controlling—are still not fully optimized. The research supports the Resource-Based View (RBV) and Financial Capability Theory, which emphasize that a combination of financial resources and managerial competence is critical to enhancing business performance. Strategic implications highlight the importance of integrated interventions from stakeholders to improve access to capital and financial literacy among MSME actors. Programs combining digital finance access with structured financial training can significantly enhance MSME competitiveness, especially in traditional market settings. The study contributes both theoretically and practically to the development of inclusive economic models for MSME sustainability in regional markets.
Supporting Factors of Digital Marketing and Customer Relationship Management and Their Role in Developing the Champion UMKM Model in West Java: Literature Review Wulandari, Rosanna; Nugroho, Arissetyanto; Derriawan, Derriawan
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.qems3951

Abstract

This study aims to identify the supporting factors in implementing Digital Marketing(DM) and Customer Relationship Management(CRM) and to examine their role in developing the Champion MSME model in West Java. Amidst tight digital competition, many MSMEs have not fully leveraged the use of digital technology, particularly in building strong customer relationships and expanding their market share. The method employed is a Systematic Literature Review(SLR) using the PRISMA 2020 guidelines, which involves articles published between 2015 and 2025 and indexed in Scopus, Web of Science, Copernicus, Sinta, and Garuda. The results of the study show that the success of digital marketing (DM) and CRM depends on the level of digital literacy, technological infrastructure support, personal interaction, and efficient customer data management. Both strategies play a role in increasing Customer Satisfaction(CS), Customer Engagement(CE), and Customer Loyalty(CL), which then contribute positively to MSME performance. In addition, the Soft System Methodology (SSM) approach is used to design a contextual Champion MSME development model that involves the participation of stakeholders. These findings are expected to be the basis for an effective strategy for developing sustainable MSME digitalization.
Dynamic Determinants of Share Price in Emerging Markets: Evidence from System GMM Estimation in Nigeria Edokpa, Solomon Ighodalo; Akpadaka, Ovbe Simon
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.qems3959

Abstract

This study investigates the dynamic determinants of share price among listed firms in Nigeria’s Consumer Goods and Agriculture sectors using a decade-long panel dataset covering the period from 2012 to 2023. Anchored on the theoretical perspectives of the Efficient Market Hypothesis, Signalling Theory, and Agency Theory, the study evaluates how firm-specific indicators such as earnings per share (EPS), return on equity (ROE), current ratio, debt-to-equity ratio, and total asset turnover, as well as macroeconomic variables like exchange rate and GDP per capita, influence share price in an environment characterised by institutional inefficiencies and information asymmetry. The empirical analysis begins with a static panel regression using the Fixed Effects model to establish a baseline understanding. To improve robustness and account for econometric challenges such as endogeneity, serial correlation, and unobserved heterogeneity, the study adopts the two-step System Generalised Method of Moments (System GMM) as the main estimation technique. The dynamic model reveals strong persistence in share price, as lagged share price is significantly associated with current values. While EPS shows a positive and significant effect in the static model, the dynamic GMM results indicate a negative and significant relationship, suggesting that reported earnings may reflect investor scepticism or earnings manipulation, particularly in contexts with weak governance oversight. Other variables, including ROE, leverage, and macroeconomic indicators, remain statistically insignificant in the dynamic specification. Year effects are incorporated to control for time-specific macro shocks. This study contributes to frontier market finance literature by offering sector-specific insights and demonstrating the added value of dynamic modelling. It also cautions investors and policymakers against excessive reliance on earnings-based metrics without adequate consideration of the institutional environment.
Reconstructing Entrepreneurship Learning Through a Managerial Approach Based on Local Ethnoscience Azzajjad, Muhammad Fath; Ahmar, Dewi Satria; Ningsih, Purnama; Nurfianti
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.qems3960

Abstract

This study looks at how students' abilities in contextual company development are affected when entrepreneurship education is reconstructed using a management style grounded on local ethnoscience. 18 students from the 2019 cohort who took the Entrepreneurship course in the Chemistry Education programme at Universitas Sembilanbelas November Kolaka provided survey data for the study. Through direct observation and group business planning, students were introduced to fundamental entrepreneurial principles and assisted in interacting with local ethnoscientific resources, including sago, cassava, green vegetables (spinach), clove, honey, shrimp, and milkfish. Standardised questionnaire encompassing eight important markers of ethnoscientific understanding in entrepreneurship was used to gather data. To understand the findings, descriptive and mapping data analysis were used. The findings show that students are highly engaged and competent in locating, evaluating, and innovatively using local resources for entrepreneurship. The most motivating resources were honey, cassava, and shrimp, and students showed great aptitude in contextual business design, product creation, and team-based entrepreneurial analysis. The main results support the idea that including local ethnoscience into entrepreneurship education increases both practical entrepreneurial abilities and cultural and ecological sensitivity. This concept is a potential educational framework for creating entrepreneurs who are innovative, locally rooted, and prepared for the future.

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