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All Journal Journal of Management, Economic, and Accounting Journal of Intelligent Systems and Information Technology Journal Of Management, Economics, And Accounting Research
Annisa Ilmi Faried
Universitas Pembangunan Panca Budi Medan
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Social Sciences

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Economic Valuation of Agricultural Productivity Enhancement through Digital-Based Resource Conservation Annisa Ilmi Faried; Vina Arnita; Nisa Ulzannah
Journal of Management, Economics, and Accounting Research Vol. 1 No. 1 (2025): November 2025
Publisher : CV. Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/jomear.v1i1.30

Abstract

The agricultural sector faces increasing pressure to enhance productivity while maintaining the sustainability of natural resources. Digital technologies offer significant opportunities to optimize resource use and support conservation-oriented farming systems, yet their economic value is often insufficiently quantified. This study examines the economic valuation of agricultural productivity enhancement through digital-based resource conservation. Using a conceptual–analytical approach supported by evidence from recent empirical studies, this paper integrates economic valuation frameworks with digital agriculture practices, including precision farming, data-driven resource management, and decision-support technologies. The analysis highlights how digital interventions generate direct financial benefits through productivity gains and cost efficiency, as well as indirect values related to ecosystem services, option values for future innovation, and social welfare improvements. The findings indicate that digital-based resource conservation contributes not only to higher agricultural output but also to long-term sustainability by reducing environmental degradation and enhancing adaptive capacity to climate change. This study provides a comprehensive valuation perspective that supports policy formulation and strategic investment in digital agriculture systems. The results underscore the importance of incorporating economic valuation into agricultural system planning to ensure balanced outcomes between productivity growth and resource conservation
Utilizing of Big Data and Machine Learning to Predict the Impact of Sharia Monetary Policy on Economic Stability Kiki Hardiansyah Siregar; Dede Ruslan; Annisa Ilmi Faried; Rahmad Sembiring; Maya Andriani; Ika Swantika
Journal of Intelligent Systems and Information Technology Vol. 3 No. 1 (2026): January
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/jisit.v3i1.243

Abstract

This study aims to investigate the use of big data and machine learning techniques to predict the effects of Sharia monetary policy on economic stability. Motivated by the underexplored nature of Sharia-compliant financial forecasting, the research applies various machine learning models including Random Forest, XGBoost, Support Vector Regression (SVR), Linear Regression, and Long Short-Term Memory (LSTM) networks to long-term stock and monetary trend predictions within the Islamic finance context. Utilizing a dataset of Indonesian Sharia stocks and financial indicators, and employing SHAP analysis for model interpretability, the study evaluates model performance based on metrics like MAPE and R². Results reveal that SVR outperforms other algorithms, providing robust and interpretable predictions that capture the influence of key financial indicators such as moving averages and Sharia-compatible BI Rate transmissions. The findings have practical implications for enhancing financial inclusion and promoting risk-efficient, interest-free profit-sharing models, with national Sharia financial assets projected to exceed Rp10.5 quadrillion by 2026. The study fills gaps in academic literature on Islamic monetary forecasting and sets a foundation for future integration of hybrid AI models for real-time policy evaluation, supporting the digital transformation of Sharia banking aligned with maqasid syariah principles
The Effects Of Population Size, Inflation, And Regional Gross Domestic Product (RGDP) On Foreign Investment In North Sumatra Province Lenny Emelia Pane; Rahmad Sembiring; Annisa Ilmi Faried
Journal of Management, Economic, and Accounting Vol. 5 No. 4 (2026): Oktober
Publisher : Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmea.v5i4.1879

Abstract

This study aims to examine whether Foreign Investment as the dependent variable can be influenced by Population Size, Inflation, and Gross Regional Domestic Product (GRDP) as independent variables. This research was conducted using a quantitative approach with secondary data published by the Central Statistics Agency (BPS) of North Sumatra Province, employing time series data from 2010–2025. The study also utilized SPSS software as a tool for data processing and analysis.The results of this study indicate that the independent variable of Population Size has a positive and significant effect on Foreign Investment, while the other independent variable, Inflation, has a positive but insignificant effect, and GRDP has a negative and insignificant effect on Foreign Investment. Simultaneously, these three independent variables have a significant effect on Foreign Investment. It is expected that the findings of this study can serve as a reference for future researchers as well as for the government in supporting decision-making and policy formulation.
Digital Transformation Of Small And Medium Food Businesses From An Inclusive Economic Point Of View: A Qualitative Study On The Use Of Gofood In Medan City Mutiara Rizky; Uswatun Hasanah; Annisa Ilmi Faried; Andria Zulfa
Journal of Management, Economic, and Accounting Vol. 5 No. 4 (2026): Oktober
Publisher : Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmea.v5i4.1915

Abstract

This study looks at how small and medium-sized food businesses are changing with technology, specifically using the GoFood platform on Jalan Dr. Mansyur, Medan City. This study also looks at how technology is adopted, using the Diffusion of Innovation Theory, explains how GoFood works as a Two-Sided Market platform, and shows how both of these things help create an inclusive economy. The method used is qualitative, with a descriptive design based on a case study approach. The main data was gathered by talking in detail with 16 people.These included 10 small businesses in the food industry that work with GoFood, 4 customers, and 2 important people (from the Medan City Cooperatives and SMEs Office and Gojek representatives in Medan).This was done along with watching what happened and keeping records. Data analysis uses the interactive approach by Miles, Huberman, and Saldaña from 2014.This method involves collecting data, reducing it, presenting it, and then making conclusions based on the findings. The results show that digital transformation leads to real improvements in how these small businesses run their operations, use cashless payment methods, and plan their marketing efforts. Business actors start using GoFood slowly, going through five stages of how new ideas spread. GoFood is a platform that connects different groups like merchants, customers, and drivers all in one system, which helps it grow by bringing more people together. From an inclusive economic point of view, this digitalization creates more fair chances for businesses and makes it easier to reach markets without being limited by location. However, the platform's high fees and the lack of digital skills among business owners are still preventing full inclusion in the economy. Working together with the government, platform companies, and small businesses through guidance programs and easier rules is important for building a strong and lasting digital environment.
Co-Authors Andria Zulfa Dede Ruslan Ika Swantika Kiki Hardiansyah Siregar Lenny Emelia Pane Maya Andriani Mutiara Rizky Nisa Ulzannah Rahmad Sembiring Uswatun Hasanah Vina Arnita