Journal of process management and new technologies

MACHINE LEARNING: TECHNIQUES, APPLICATIONS, AND METRICS FOR ENHANCED VEHICLE PERFORMANCE

Aadil Arshad FERHATH — 2025-10-04

Machine learning allows systems to autonomously learn from data and improve performance without direct programming, providing robust tools for identifying patterns, forecasting outcomes, and optimising complex processes. This paper offers a comprehensive overview of machine learning, beginning with an examination of its core categories: supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, and deep learning. The review considers essential algorithms associated with each machine learning category, providing insights into their functions and real-world applications. The paper also discusses widely used evaluation metrics for regression models, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²), which are essential for assessing predictive performance and guiding model selection. The article examines numerous real-world applications of machine learning across various sectors, including healthcare, banking, transportation, marketing, and cybersecurity, illustrating how these technologies are transforming modern processes and delivering tangible benefits.

AN ANALYSIS OF THE DETERMINANTS AFFECTING THE PERFORMANCE OF MICROFINANCE INSTITUTIONS IN GHANA

Jane ARTHUR-SAM — 2025-10-18

Microfinance Institutions (MFIs) are crucial in providing services to the underprivileged, particularly those with limited incomes and the unorganized sector in a sustainable manner. In the Ghanaian business industry, these firms are primarily seen as vital institutions for progress against poverty and an excessive dependence on national and local governments. Thus, the goal of this study is to identify the factors affecting the performance of Microfinance institutions in Ghana. Multiple regression and descriptive statistics were used to analyze the secondary data gathered from the 133 MFIs in Ghana with SPSS. The study's conclusions showed that efficiency and liquidity have significantly positively impact on the firms' return on equity (ROE). Capital adequacy ratio (CAR) and non-performing loans (NPL) had no statistically significant effect on the Microfinance institutions' performance (ROE). Additionally, the study discovered a significant positive effect of CAR on the performance of the return on assets (ROA) on the MFIs. However, liquidity, efficiency and NPL had no statistical significant impact on the performance (ROA) of the companies. The research contributes to literature on the studies conducted on MFIs in Ghana and practically assists in improving and enhancing their performance. This study also promotes ways on how the government and stakeholders can support MFIs for a long-term sustainability and the economic growth in the country.

Engleski

Stefan MILOJEVIĆ — 2025-10-19

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IMAGE PROCESSING BASED PLANT FERTILIZER SPRAYING ROBOT

Omkar KACHARE — 2025-10-19

The application of smart technologies in agriculture has transformed conventional farming practices, significantly increasing productivity and sustainability. In this research, we propose a novel method of agricultural automation through the development of an Autonomous Plant Spraying Robot. The system integrates Raspberry Pi and ESP32 microcontrollers along with servo motors to provide a flexible and robust solution for various agricultural operations. The Raspberry Pi functions as the central processing unit, offering substantial computational power and connectivity for real-time data processing and decision-making. The ESP32 microcontroller manages wireless communication and sensor integration, enabling remote monitoring and control of agricultural activities. Servo motors are employed for precise and efficient actuation, allowing the robot to carry out tasks such as spraying, irrigation, and harvesting with high accuracy and consistency. Key features of the project include modular design, scalability, and ease of customization. By leveraging open-source hardware and software platforms, the system remains adaptable and easily integrated with existing agricultural machinery and infrastructure. Furthermore, the use of servo motors enables the robot to navigate a variety of terrains and complex environments, broadening its applicability across diverse farming practices and landscapes. Through field testing and performance evaluation, we demonstrate the effectiveness of the robotic system in enhancing operational efficiency, reducing labor costs, and minimizing environmental impact. Future developments will focus on system optimization, integration of advanced sensing technologies, and real-world deployment to maximize its contribution to global food production.

AN INTERVAL-VALUED SPHERICAL FUZZY SWARA-CRADIS APPROACH TO STRATEGIC PROBLEM-SOLVING IN LOCAL MEDIA BUSINESSES

Aleyna SARIGÜL MERT — 2025-11-30

This research aims to identify the key challenges faced by local media businesses, assess their severity, and propose strategic solutions. As social media and technological advancements continue to transform the media landscape, local media organizations are struggling with a wide range of problems. However, most existing strategies have failed to achieve their intended outcomes. The study employs a two-stage data collection process conducted in Artvin province, Turkey. In the first stage, the main challenges and potential strategic solutions were identified based on expert opinions. The problems of local media companies were categorized under the following dimensions: economic issues, technological and digital infrastructure, employment and skilled personnel shortages, structural and institutional challenges, legal and administrative barriers, content production and journalistic quality, distribution and accessibility, and media–political relations and ethical concerns. In the second stage, these problems and strategic solution proposals were evaluated based on experts’ assessments using the Interval-Valued Spherical Fuzzy SWARA-CRADIS methodology. The findings indicate that local media businesses struggle not only with limited economic resources but also with difficult working conditions, insufficient leave, excessive workloads, and the migration of qualified personnel. The proposed strategic solutions focus on strengthening legal and regulatory support, focusing on local community engagement, and enhancing accessibility and content diversity.