This study focuses on the development of continue to grow, strengthening cybersecurity measures a Machine Learning Algorithms and Hybrid Model is essential in protecting businesses, organizations, and that combines Naïve Bayes and all other algorithms individuals from online fraud. By improving phishing which are the XGBoost, Support Vector Machine, detection models, this research contributes to the Random Forest and Decision Tree to enhance the development of more reliable an d secure digital detection of phishing w ebsites. The system was infrastructures, ensuring safer online transactions and trained and tested using three datasets (Dataset1, communications. Dataset2 and Dataset3) with various train - test split (50% - 50%, 60% - 40%, 70% - 30%, 80% - 20%, and Meanwhile, SDG 16 aims to promote peace, justice, 90% - 10%) to evaluate its performance under and strong institutions, which includes ensuring security in both different conditions. The preprocessing stag e physical and digital spaces. Phishing is a form of cybercrime that included normalization, feature selection, and data targets individuals and organizations by tricking them into balancing using SMOTE to improve accuracy. To giving away sensitive information. This study helps in the fight validate the model, 10 - Fold Cross Validation was against cybercrime by providing effective methods to detect and applied to ensure consistency and prevent prevent phishing attacks. Strengthening cybersecurity systems overfitting. The system's performance was assessed supports the protection of personal data, financial assets, and using key eval uation metrics such as accuracy, institu tional security, ultimately contributing to a safer and more precision, recall, and F1 - score. The results revealed trustworthy digital environment [2]. the XGBoost and hybrid model is Naïve Bayes and Decision Tree classifiers, demonstrating higher detection accuracy and reliability. II. R EVIEW OF RELATED LITERATURE

The growing movement of individuals through terminals in Western Visayas, serving as a gateway for regional Roll - on/Roll - off (RORO) ports poses a significant people traveling between Iloilo and Negros Occidental. challenge to law enforcement authorities, particularly in Given its strategic location and high passenger volume, the tracking wanted persons attempting to cross provinces or port is vulnerable to being used as an escape route by regions undetected. The study CrimeTra ck, an Intelligent Matching and Reporting System specifically designed for individuals with criminal records. Traditional manual the Dumangas RORO ports in Iloilo. The system aims to identity verification methods often prove insufficient due assist port security personnel and local law enforcement to limited manpower, time constraints, and the risk of agencies in identifying, matching, and reporting wanted human error. individuals based on real - time data verification and biometric analysis. To address this issue, this study proposes CrimeTrack: Intelligent Matching and Reporting System CrimeTrack utilizes biometric verification tools, for Wanted Persons. The system is designed to assist port including facial recognition and identity matching authorities and local law enforcement in automatically algorithms, to compare traveler information against active verifying the identity of passengers against national warrants and watchlists. Once a match is detected, the watchlists and warrant databases using intelligent system generates immediate alerts and incident reports for matching technologies such as facial recognition and security personnel and law enforcement officers on - site. biometric verification. By integrating with law enforcement databases and providing real - time alerts, CrimeTrack is built with a secure, user - friendly CrimeTrack aims to strengthen port security, improve interface, providing a centralized dashboard for monitoring, apprehension rates, and contribute to the overall safety of incident tracking, and generating analytical reports. The the community. system is designed to enhance public safety operations by reducing manual checks, minimizing human error, and This project highlights the importance of enabling faster response times. incorporating intelligent digital solutions in public safety operations and seeks to establish a scalable and efficient

Rice serves as a dietary staple for more than three who spoke on the health dangers associated with rice farming at billion individuals worldwide, yet notable postharvest losses the Philippine Rice Research Institute, instructed farmers on persist despite improvements in production methods. Although how to recognise the symptoms of heat stroke because, even in traditional sun drying is economical and environmentally rural health units, the disease is frequently overlooked or sustainable, it demands considerable labor, poses health hazards misdiagn osed. to farmers, and leads to inconsistent drying, which affects grain quality. To tackle these issues, this research introduced According to the statement of Mr. Nindro Paul "GrainBot: An Android Controlled Rice Grain Collector Robot." Pountero, one of the laguerta farmer, is that when sun - drying This robot, which operates on two wheels, employs a suction the rice or any grains, they encounter challenges like too much mechanism to gather sun - dried rice and can be controlled heat, time consumption, and difficulties in manually putting rice wirelessly through a specially designed Android app. The on a sun - dried mat. ( Sun drying of rice grains is very common, evaluation of the system's functionality, usability, efficiency, particularly in small and medium - sized batches of drying mat. compatibility, maintainability, rel iability, and portability was Uneven grain spreading and overheating on the drying mat can conducted following ISO 25010 standards by farmers, cause the grains to become tough, and will lost its nutrients. ) As agricultural experts, and IT professionals. The assessment a result, some grains may remain damp or under - dried while resulted in an "excellent" grand mean score of 4.61, reflecting others become early dry, leading to u neven grain spreading of high levels of user satisfaction and the system's e ffectiveness in grains, inadequate exposure to sunlight, and varying weather automating and streamlining the rice grain collection process. conditions. As a result, some grains may remain damp or under - The proposed system presents a promising technological dried while others become overly dry, leading to uneven quality approach to reducing manual labor, alleviating health risks for and potential spoilage. Achieving uniform dr ying id crucial to farmers, and enhancing the efficiency of postharvest rice ensuring the longevity and market value of the rice crop. handling . However, sun - drying has a limited capacity and is

A mobile - based Mango Sizing Application II. METHODOLOGY using an Image Processing was developed to address the challenges of manual fruit grading methods in the A. Application Overview agricultural industry. Traditional manual grading is time - consuming and often inconsistent due to human Our Mango Sizing Application — affectionately subject ivity. This application automates mango grading called Mangrade — was built using Cordova and based on size, color, and weight using image processing Android Studio to make it accessible on smartphones. and linear regression models. The application captures It’s designed to be user - friendly: users simply snap a mango images, processes them to extract relevant photo of a mango, and the app does the rest. Behind the features, and classifies them into pr edefined size grades. scenes, it analyzes the image to detect key features like Evaluated using ISO 25010 software quality standards, color and pixel dimensions. Using a linear regression the application scored high in functionality, efficiency, model, the app then estimates the mango’s weight and usability, maintainability, and security. The proposed automatically classifies it into size categories such as solution offers a reliable, fast, and consistent method for Grade A, B, or C. mango c lassification, providing a practical alternative to traditional methods. B . Image Processing and Feature Extraction