Exchange rate prediction is a crucial aspect of financial analysis, particularly for countries with dual currency systems such as Cambodia. The Khmer Riel (KHR) is widely exchanged with the United States Dollar (USD), making accurate prediction models essential for businesses and policymakers. This study explores ensemble learning and deep learning approaches to predict the USD/KHR daily exchange rate using historical data collected from the Nati
Cambodia's rice sector has undergone significant transformation over the past decades, evolving into a cornerstone of the national economy. Despite improvements in cultivation techniques and land use, the sector remains vulnerable to climate variability, inefficient resource allocation, and limited data-driven planning. To address these challenges, this study presents a comprehensive prediction framework that leverages both traditional Multiple L
Student post-graduate success plays an essential role for higher education institutions (HEIs) to improve their standing and reputation, increasing their enrollment rates. As a result, HEIs are allocating significant effort and resources to cultivate student success after graduation. In this study, student post-graduate success is categorized into four distinct levels including "Failure", "Satisfaction", "Success", and "High Success". To predict
Payment card fraud losses worldwide reached $33.83 billion in 2023 (Nilson Report, 2025). Alarmingly, Deputy Prime Minister and Minister of Interior Sar Sokha (2024) stated that in the first semester of 2024, Cambodians lost nearly $40 million to online and digital fraud. To prevent these significant financial losses, it's crucial to identify the predictive models that can more accurately detect the anomalies in transactions. This study investiga
The rapid evolution of labor markets, particularly in emerging economies like Cambodia, necessitates a dynamic and real-time skill demand analysis. Traditional methods, such as employer surveys, are often static and infrequent, failing to capture the fluidity of an evolving workforce. This research addresses this data gap by presenting a novel computational pipeline that leverages recent advancements in Large Language Models (LLMs) and Natural La
Recognizing handwritten digits is a fundamental aspect of optical character recognition (OCR), with broad applications in areas such as digital archiving, data entry, and assistive technologies. Khmer digits present distinctive challenges due to their intricate shapes and high variability in individual handwriting styles, making the development of accurate recognition systems particularly demanding. Unlike conventional approaches that primarily r
Online writer verification with dynamic handwriting signals is still difficult, and it has been especially under-studied for complex Southeast Asian scripts like Khmer. This work tackles online, text-independent, word-level Khmer writer verification as a pairwise decision problem: given two handwritten word samples, decide whether they were written by the same person. We introduce KVerifyID, a hybrid dual-stream Siamese network that learns from b
In recent years, the application of machine learning in education has gained significant attention for its potential to uncover hidden patterns and improve student learning outcomes. This study employs a hybrid unsupervised-supervised machine learning approach to achieve two primary objectives: first, to uncover hidden learning profiles of Cambodian high school students, and second, to identify and validate the most significant factors contributi
Enhancing students’ academic outcomes in blended learning (BL) environments requires timely intervention for at-risk students, making early detection a critical task for educators and researchers. However, this task remains challenging due to imbalanced educational data and limited model sensitivity. This study investigated the application of machine learning (ML) for the early identification of at-risk students in BL environments, aiming to impr
Pesticides are essential tools for agricultural productivity, yet their inherent toxicity and high mobility pose significant environmental and health risks. This study investigates the mechanisms of hydraulic transport for soluble pesticides within Cambodia's major river systems: the Bassac (BSR), Tonle Sap (TSR), and Mekong (MKR). Our analysis integrates a re-analysis of published data from 48 surface-water samples (May-June 2020, covering BSR a
