Garuda - Garba Rujukan Digital

METODE REGRESI PANEL SPASIAL PADA PEMODELAN TINGKAT KEMISKINAN DI KABUPATEN / KOTA PROVINSI JAWA TIMUR Metyopandi, Vierkury; Fitriani, Rahma; Sumarminingsih, Eni
Jurnal Mahasiswa Statistik Vol 2, No 5 (2014)
Publisher : Jurnal Mahasiswa Statistik

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Strengthening Community Businesses Through Creative Digital Promotion and Education Dewantara, Alif; Pratama, Ahmad Herlyasa Sosro; Pratama, Andik; Metyopandi, Vierkury
TGO Journal of Community Development Vol. 2 No. 1 (2024): January - June
Publisher : Trescode Green Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56070/jcd.2024.003

In 2020 - 2022, digital marketing practices will become increasingly prominent in response to the global COVID-19 pandemic, which has driven the transformation of society towards broader use of the digital realm. Apart from being a marketing tool, digital applications also play an essential role as a source of inspiration for individuals interested in starting an independent business. Within the framework of community service activities, the service team from Merdeka University Malang, together with students, carried out community service activities through the creative promotion of MSMEs and video tutorials that were beneficial to the community. This service activity involves the active participation of twenty students who are members of two different teams, namely the team responsible for its implementation.

Influence of Machine Learning Algorithm, Demand Prediction, and Automation System in Responsive Inventory Management in Retail Industry in Central Java Loso Judijanto; Vierkury Metyopandi; Sumarni Sumarni
West Science Social and Humanities Studies Vol. 2 No. 12 (2024): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v2i12.1491

This study investigates the impact of machine learning algorithms, demand prediction, and automation systems on responsive inventory management in the retail industry of Central Java. Using a quantitative approach, data were collected from 160 respondents through a structured questionnaire employing a Likert scale (1–5) and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The findings reveal that automation systems and demand prediction significantly and positively influence responsive inventory management, while machine learning algorithms exhibit a significant but negative relationship. Automation systems streamline processes and improve efficiency, and demand prediction enhances inventory alignment with market needs. However, challenges such as limited technical expertise and integration issues hinder the effective use of machine learning. These results underscore the importance of strategic technology adoption and provide practical insights for improving inventory management practices in the retail sector of developing regions.

Perusahaan Healthcare dalam Bahaya: Pendekatan Analisis Risiko Keuangan Perusahaan Vierkury Metyopandi; Ery Sulistyorini; Rafiq Firdaus Al-Asjim; Ulfa Miftachul Afifah
Syntax Idea 2116-2129
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/syntax-idea.v5i11.2719

Conditions after the pandemic subsides are another new challenge for healthcare sector companies in Indonesia. This research aims to investigate the influence of financial performance on company share prices in the healthcare sector. The company's financial performance, for all aspects of financial ratios, is often considered an important indicator for investors in making their investment decisions. Therefore, this research seeks to identify the influence between the financial performance of healthcare companies and their share price movements. This research method involves analyzing historical financial data of healthcare companies for the period 2019 to 2022, as well as their share price movements during the same period. The analytical tool used uses multiple linear regression analysis with the help of Eviews 10. The results of data analysis will be used to measure the extent to which financial performance influences stock prices. It is hoped that the results of this research will provide deeper insight for investors and stakeholders in understanding the factors that influence company share prices in the healthcare sector. This research concludes that return on equity and earnings per share have a significant influence on the share prices of health sector companies. These findings show that healthcare companies with high ROE and controlled debt ratios tend to have better stock performance. Apart from that, consistent EPS is also an important indicator in assessing a company's financial performance, which has a positive impact on investor confidence and share prices. This conclusion provides a holistic view of the close relationship between the financial aspects of healthcare companies and the stock market response to them. It is highly recommended for further research to use all financial ratio parameters to obtain comprehensive information regarding financial performance and stock prices.

THE EFFECTS OF FOREIGN DIRECT INVESTMENT AND PROFITABILITY ON THE STOCK RETURNS Metyopandi, Vierkury; Salim, Ubud; Aisjah, Siti
Jurnal Aplikasi Manajemen Vol. 21 No. 2 (2023)
Publisher : Universitas Brawijaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jam.2023.021.02.11

This research aimed to identify how to examine and analyze the effects of foreign direct investment and profitability on the stock returns in manufacturing companies registered on IDX during 2016-2018. The total population was 91 companies registered and filtered into 32 registered companies according to the sample criteria and analyzed through Eviews 10 software. The research result referred that the foreign direct investment received by multinational companies could not yet affect stock return directly. Also, foreign direct investment was not able to influence the return on asset (ROA), but it was able to affect the return on equity (ROE). Further, ROA was not able to affect the increase of stock returns, while ROE was able to affect the rise of stock returns. Another research finding showed that ROE was the only one that could be a mediation variable in the relationship between foreign direct investment affecting stock returns. At the same time, ROA could not be a mediation variable. For the next studies, the researchers suggested exploring the other financial performance variables suited to foreign direct investment to affect the stock returns. In practice implication from this research, the investors must see how strong the capital owned by a company that accepts foreign direct investment and the relation, how the capital they receive can improve or maintain the company's financial performance within a certain period of time.

Influence of Machine Learning Algorithm, Demand Prediction, and Automation System in Responsive Inventory Management in Retail Industry in Central Java Judijanto, Loso; Metyopandi, Vierkury; Sumarni , Sumarni
West Science Social and Humanities Studies Vol. 2 No. 12 (2024): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v2i12.1491

This study investigates the impact of machine learning algorithms, demand prediction, and automation systems on responsive inventory management in the retail industry of Central Java. Using a quantitative approach, data were collected from 160 respondents through a structured questionnaire employing a Likert scale (1–5) and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The findings reveal that automation systems and demand prediction significantly and positively influence responsive inventory management, while machine learning algorithms exhibit a significant but negative relationship. Automation systems streamline processes and improve efficiency, and demand prediction enhances inventory alignment with market needs. However, challenges such as limited technical expertise and integration issues hinder the effective use of machine learning. These results underscore the importance of strategic technology adoption and provide practical insights for improving inventory management practices in the retail sector of developing regions.

Pengaruh Tata Kelola dan Risiko Perbankan Terhadap Kinerja Keuangan Bank di Indonesia Kawakibi, Ardhan Ardiansyah; Metyopandi, Vierkury
Jurnal Ekonomi Dan Statistik Indonesia Vol. 5 No. 3 (2025): Berdikari: Jurnal Ekonomi dan Statistik Indonesia (JESI)
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jesi.05.03.11

Penelitian ini bertujuan untuk menguji pengaruh tata kelola perusahaan terhadap kinerja keuangan perbankan yang terdaftar di Bursa Efek Indonesia (BEI) periode 2019–2024, baik secara langsung maupun melalui risiko kredit dan risiko operasional sebagai variabel mediasi. Tata kelola perusahaan diukur menggunakan corporate governance index, risiko kredit diproksikan dengan Non Performing Loan (NPL), risiko operasional dengan rasio Beban Operasional terhadap Pendapatan Operasional (BOPO), serta kinerja keuangan diukur menggunakan Tobin’s Q. Penelitian ini menggunakan pendekatan kuantitatif dengan metode sampel purposive sampling dan didapatkan 27 bank sebagai sampel. Analisis data dilakukan menggunakan Partial Least Square (PLS), sedangkan pengujian mediasi menggunakan Sobel Test. Hasil penelitian menunjukkan bahwa penerapan tata kelola perusahaan yang baik mampu menurunkan risiko kredit dan risiko operasional serta meningkatkan kinerja keuangan perbankan. Selain itu, risiko kredit dan risiko operasional terbukti memediasi secara positif hubungan antara tata kelola perusahaan dan kinerja keuangan. Temuan ini menegaskan bahwa tata kelola perusahaan yang efektif berperan dalam meminimalkan konflik kepentingan dan asimetri informasi sehingga berdampak pada peningkatan kinerja keuangan bank.

The Influence Of Borrower Characteristics, Income, And Business Type On The Level Of Smoothness In Return Of People's Business Credit (KUR) (Case Study at Bank BTN KCP Jombang in 2024) Fuzaki, Alfani Amar; Metyopandi, Vierkury; Efionita, Yolanda; Amin, Rofikul
Business Management Research Vol. 5 No. 1 (2026): January 2026
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/bismar.v5i1.16589

Micro, Small, and Medium Enterprises (MSMEs) serve as the vital backbone of the Indonesian economy, yet they frequently encounter structural hurdles in capital access and business management. To bridge this gap, the People's Business Credit (KUR) provides essential financing for feasible but non-bankable businesses. This research evaluates the critical factors determining the success of the KUR program, specifically focusing on the influence of borrower characteristics, income levels, and business types on repayment smoothness. Situated as a case study at Bank BTN KCP Jombang in 2024, the study addresses persistent challenges in loan installments despite existing government guarantees. Utilizing a quantitative approach, primary data were gathered from 30 KUR debtors selected through purposive sampling and analyzed via multiple linear regression. Empirical results reveal that all three variables significantly impact credit repayment. Notably, borrower characteristics exhibit a significant yet negative influence (sig = 0.021), suggesting that certain personal traits or high social responsibilities may inadvertently burden financial discipline. Conversely, income (sig = 0.000) and business type (sig = 0.000) demonstrate strong positive correlations with repayment performance. The model achieved an Adjusted R-Square of 0.961, indicating that 96.1% of the variance in repayment is explained by these factors. These findings highlight that while individual character is essential, the economic viability of the business sector and stable revenue streams are the primary drivers of credit quality.

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