Artificial Intelligence-based Manifesto System (Record no. 88569)

MARC details
000 -LEADER
fixed length control field 04729nam a22002657a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251104125154.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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043 ## - GEOGRAPHIC AREA CODE
Geographic area code URS
245 ## - TITLE STATEMENT
Title Artificial Intelligence-based Manifesto System
Remainder of title / Nido, Tristan Stephen E.... [et al.].
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. March 2024
300 ## - PHYSICAL DESCRIPTION
Extent 125 leaves :
Dimensions 28 cm.
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
502 ## - DISSERTATION NOTE
Dissertation note Thesis
Degree type Bachelor of Science in Computer Engineering
Name of granting institution University of Rizal System-Morong
Year degree granted 2024
520 ## - SUMMARY, ETC.
Summary, etc. The study aimed to develop an Artificial Intelligence-Based Manifesto System, assessing its acceptability across dimensions like Functional Suitability, Performance Efficiency, Compatibility, Usability, Reliability, Security, Maintainability, and Portability. It also profiles respondents based on age, sex, and weight to understand differences in perception. Performance testing and generating passenger reports are part of the evaluation at Binangonan Port during 2023-2024. The study included three hundred sixty-seven (367) participants, comprising three hundred fifty-two (352) end-users and fifteen (15) experts, using frequency and percentage analysis. Performance of the Artificial Intelligence-Based Manifesto System was tested by calculating time response mean and standard deviation. Acceptability was evaluated across dimensions like functional suitability and compatibility using weighted mean analysis. An independent t-Test assessed differences based on respondent profiles, providing insights into system performance and acceptability levels. This study combined developmental and descriptive research methods to advance the Artificial Intelligence-Based Manifesto System. Using frequency and percentage analysis, researchers made significant progress in the developmental phase. Evaluation of system acceptability through weighted mean and analysis of differences based on respondent profiles enhanced understanding of functionality and user reception. The profile of respondents is categorized by age, with twenty-three (23) percent aged eighteen and below, and seventy-seven (77) percent aged nineteen and above, totaling one hundred. Similarly, the respondents' profiles are presented based on sex, with males accounting for forty-nine (49) percent and females comprising fifty-one (51) percent, summing up to one hundred. Moreover, respondents are categorized by weight, with thirty-five (35) percent weighing fifty and below, and sixty-five (65) percent weighing fifty-one and above, totaling one hundred (100) percent. The Artificial Intelligence-Based Manifesto System is rated "Very Much Acceptable" across various dimensions: Security scored highest at 4.58, followed closely by Usability at 4.57 and Maintainability at 4.55. Functional Suitability and Portability received ratings of 4.54 and 4.52, respectively. Performance Efficiency and Reliability scored favorably at 4.40 and 4.20, falling within the "Very Much Acceptable" range. Compatibility, slightly lower at 4.14, still falls within an acceptable range. Overall, the system demonstrates strong performance and reliability in manifesto management. The Artificial Intelligence-Based Manifesto System is successful, embraced by users aged nineteen and above, mainly female, with diverse weight categories. It employs Haar Cascade and LBPH algorithms for accurate face recognition. It's highly accepted, with no significant impact from age, sex, or weight, except for portability concerning sex. It generates CSV reports for managing passenger data efficiently, aiding in boat assignment and accommodation. Researchers recommend to enhance the Artificial Intelligence-Based Manifesto System by considering additional variables beyond age, sex, and weight. Improve face recognition accuracy with upgraded storage and movable, high-resolution cameras. Ensure compatibility across operating systems and develop a smaller kiosk version with a sign-up feature. Use PDF format for manifesto lists and create an internet-compatible version for easier access. Future research could explore optimizing facial recognition performance under changing light conditions and aligning the system with evolving technological standards.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Nido, Tristan Stephen E.
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Gondraneos, Ericson R.
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Oabel, Mark Dharyl
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Quiñones, Rheylan S.
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Alfonso, Paul Arvy V.
Relator term degree supervisor
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Online Request for Student Unpublished Works
Uniform Resource Identifier <a href="https://forms.gle/7LqvGGkaDrUQqz429">https://forms.gle/7LqvGGkaDrUQqz429</a>
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://drive.google.com/file/d/1fJ62f1-Kn4nEbCBinWA6i7j1qvXyc4KN/view?usp=drive_link">https://drive.google.com/file/d/1fJ62f1-Kn4nEbCBinWA6i7j1qvXyc4KN/view?usp=drive_link</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Theses and dissertations
Holdings
Withdrawn status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
  Library of Congress Classification     Reference Morong College Library Morong College Library 10/29/2025   URSMOR-CL-6752 10/29/2025 10/29/2025 Theses and dissertations

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