https://hdl.handle.net/20.500.12852/79 Fri, 13 Nov 2026 15:24:39 GMT 2026-11-13T15:24:39Z https://hdl.handle.net/20.500.12852/3991 Online voting system using Rivest Shamir Adleman encryption algorithm Canatoy, Roda Katrina E. The Online Voting System Using Rivest-Shamir-Adleman Encryption Algorithm is a system designed to manage elections in a college and to allow voters to cast their votes online using their Android mobile devices. The traditional voting process faces challenges such as invalidating the bona fide voters, time-consuming results generation, and low voter turnout. The system allows the system administrators to create elections, define positions, add candidates, add departments and degree programs, and manage voter registrations. Voters can log in using their Android mobile devices by entering their unique credentials and a one-time password sent to their registered mobile numbers or email addresses. After successful verification, users can securely cast their votes and can view election results when the election period is done. Votes are encrypted using the RSA encryption algorithm for secure and tamper-proof voting. The real-time tallying and displaying of the partial result functionalities improve the transparency and speed of the election process. After the election period, the generation of results is faster and more reliable. Since the system can be accessed online, it can help increase the voter turnout. The system helps increase efficiency, improve accessibility, save costs, provide convenient administration, minimize human error, provide faster election results, and quickly generate reports. Abstract only Thu, 01 May 2025 00:00:00 GMT https://hdl.handle.net/20.500.12852/3991 2025-05-01T00:00:00Z https://hdl.handle.net/20.500.12852/3676 Faculty attendance performance monitoring and decision support system using multiple linear regression algorithm Eregia, Rodolfo C., Jr. The Faculty Attendance Performance Monitoring and Decision Support System Using Multiple Linear Regression Algorithm is a system designed to organize and support decisions on University scheduling of courses through analysis of faculty performance through multiple linear regression algorithm. The system allows profiling of faculty, buildings, courses, and schedules through input or through import though a batch file. Faculty Attendance and Monitoring enhanced though auto filtering and sorting based on the need of the attendance checker, streamlining only important schedules at the current time and place. Using Multiple Linear Regression Algorithm, the system then analyzes whether a faculty is best fit for a certain schedule or not. The analysis is can be used as a guide by the schedule coordinator on assignment of schedules during the beginning of the semester. The methodology used is Evolutionary Prototyping Model, a variant of a prototyping methodology where the prototype is not discarded rather used as an initial resource for developing the next prototype based on the customer’s feedback after testing the prototype. The method has six (6) key phases: Planning, Analysis, Design, Prototype Implementation, Customer Feedback, Final Testing and Implementation and Deployment. The processes from the Analysis Phase to the Customer Feedback Phase comprise the Prototype Building, the core of the system development. The Faculty Attendance Performance Monitoring and Decision Support System Using Multiple Linear Regression Algorithm provides the university the support in making the optimal decisions in the matter of scheduling and monitoring of faculty performance. Abstract only Wed, 01 May 2024 00:00:00 GMT https://hdl.handle.net/20.500.12852/3676 2024-05-01T00:00:00Z https://hdl.handle.net/20.500.12852/1519 Document management system using optical character recognition, clustering, watermarking and QR coding algorithms Censoro, Keith C. The Document Management System is a stand-alone desktop application that provides the employees of the Department of Budget and Management Regional Office VI a service that would secure the circulars and memorandum documents. The Document Management System will accept an official document sent by the Central office to be scanned into the system thru a scanning module that will use Optical Character Recognition (OCR). The captured image of the scanned document is converted to text and clustered into supervised keywords to facilitate searching using the Term Frequency-Inverse Document Frequency (TF-IDF) Algorithm. The scanned document will then undergo authentication by imprinting a watermark image and a QR Code using the watermarking algorithm using Text Brush Embedding and a QR Code Model 2 matrix code. The Evolutionary Prototyping model was used throughout the system development process. It has phases where system evaluation is made directly by the evaluators and the system is refined based on feedbacks which fastened the system process. Employees of the Department of Budget and Management Regional Office VI evaluated the system and based on feedback, the scanned documents that underwent the authentication process was very secured as the watermark and QR code is imprinted on the document accurately. The features of the system was able to generate a scanned document with watermark and QR Code imprint and was scanned via the verifier that accepted the document as an authenticated and secured copy generated by the system. Abstract only Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/20.500.12852/1519 2021-01-01T00:00:00Z https://hdl.handle.net/20.500.12852/1344 Tryk: A mobile transportation application using Bellman Ford algorithm Fuentes, Anntoniete A. Tryk is a mobile transportation application for a transport service provider that facilitates communication between the commuters and tricycle drivers regarding transportation services with the localities. Tryk is linked to the global positioning system (GPS), a navigations satellite system that provides location, velocity and time synchronization. The main features of the system conveniently allows to connect the commuters and drivers for transportation services, uses the Bellman Ford Algorithm to determine the shortest path from pick-up point to travel destination based on LTFRB transport fare and travel distance, provides the users with an interface for selecting point of origin, destination and ride type and administering particularly on ensuring the validity and reliability of transport services by the registered tricycle drivers. The Rapid Application Development model was used as modification of the modules throughout the process of development caters to the needs of the software without affecting the end product. It has the facility to frequently receive feedback from the users directly interfacing with the application during the development process. Experts and users feedback showed that the application was able to conveniently connect commuters and drivers for transportation services in determining the shortest path. Abstract only Wed, 01 Jan 2020 00:00:00 GMT https://hdl.handle.net/20.500.12852/1344 2020-01-01T00:00:00Z