Romblon State University Research Journal

In Situ Synthesis of Bare Silver Nanoparticles on Paper for Copper (II) Ion Detection

2022-12-30T05:26:32-06:00

This study synthesized bare silver nanoparticles on paper and evaluated its response to copper (Cu(II)) ions to assess its potential as colorimetric sensing platform. The nanoparticles were synthesized in-situ on paper using silver nitrate and sodium borohydride as precursor and reducing agent, respectively. No stabilizer or functionalizing agent was added. A two-factor three-level full factorial design with varying concentration of reagents was employed in the synthesis process. The resulting sensor was successfully characterized using diffuse reflectance spectroscopy and scanning electron microscopy with elemental dispersive x-ray spectroscopy. The sensor was exposed to varying Cu(II) concentrations ranging from 1 to 30 mM and the developed color changes were analyzed using a computer imaging software. The changes in color were quantified using mean gray values from the imaging software. Based on the results, as the concentration of Cu(II) ions increased, the final mean gray value of the paper increased as well. The papers were observed to marginally lighten in color potentially due to the decrease in silver atoms or its interaction with copper. The relationship between Cu(II) concentration and the ratio of final and initial mean gray value was determined and although a weak linear relation existed from 1 to 30 mM, a positive slope supported the increase in mean gray value within the range tested. The changes in the elemental composition of the sensor due to exposure to Cu(II) ions were studied. Finally, the response of the sensor towards other metal ions was compared to that of Cu(II) in a selectivity study.

Predictors of Students’ Performance in Accounting 1 at Romblon State University

2024-01-10T20:35:22-06:00

In Romblon State University (RSU), the surge of enrolment but low cohort survival rate in the BS Accountancy program calls for an urgent review of its admission policies. This study analyzed whether gender, school type, academic track, senior high school report card grade, Overall College Admission Test (CAT) Score, and its subject components (Science, English, Mathematics and Filipino), and abstract reasoning can significantly predict students’ performance in Accounting 1. Correlation between accounting grade in senior high school and final grade in Accounting 1 in college was also determined. Multiple linear regression was employed in analyzing registration data and test results from 79 students with complete information out of 139 target respondents. Results showed that English CAT Score (β = 0.34 , p = 0.001), academic track (β = 0.32 , p = 0.001) and Abstract Reasoning Test Score (β = 0.31 , p = 0.002) can predict the performance of students in Accounting 1 but there was no significant relationship between accounting grade in senior high school and final grade in Accounting 1 in college (r = 0.21, n = 55, p = 0.12). The significant predictors are reflective of the important intellectual skills and competencies the accounting profession requires such as analytical, problem-solving and strategic critical thinking skills. The University may consider these factors in updating their admission policy to the program.

Structural and Functional Analysis of Bansag Narratives in Barangay Maslog, Legazpi City, Albay Philippines

2023-12-06T20:52:23-06:00

This paper collected, transcribed, translated, and analyzed the folk narratives on bansag in Barangay Maslog, Legazpi City. It employed the Labovian method to examine the narratives’ structures and Bascom’s functionalism approach to determine the functions of the narratives. This paper concludes that the narrator’s storytelling technique greatly affects the structural pattern of the folk narratives. The completeness or incompleteness of the structure of the narratives will never diminish the essential nature and functions of folk narratives. Folk narratives over time will always be an important oral tradition. They still served their purpose in the community. However, folk narratives as a form of oral literature are under threat since many details of the narratives diminished or were lost through oral transmission from generation to generation. Since oral narratives are on the verge of extinction, this paper recommends incorporating these narratives into the curriculum to safeguard and preserve the oral narratives.

RSUSafe: Student Daily Health Record Tracking System for RSU Romblon Campus

2023-11-27T23:18:20-06:00

This study developed RSUSafe, a COVID-19 website dedicated to tracking the daily health records of students at Romblon State University - Romblon Campus. The specific objectives include the creation of an easy-to-use mobile responsive website that can track daily health data for students participating in flexible face-to-face courses. Additionally, the system incorporates a notification mechanism for both the school nurse and symptomatic students, accessible through the school nurse's web portal. This study was conducted in the first semester of academic year 2022-2023. Considering time constraints and student availability, a sample of 100 responses was collected using the convenience sampling method. To ensure the effectiveness of RSUSAFE, proper reporting and evaluation of the acceptance of the system using the ISO/IEC 25010: 2011 standard was also conducted. Results showed that the RSUSafe system is evaluated as highly suitable, highly efficient, highly reliable and highly secured. The results of this study are expected to significantly contribute to improving health surveillance practices in academic institutions.

Perceiving Highest Faculty Performance Using Classification Algorithms

2022-04-18T01:19:24-05:00

The main objective of this study was to predict who among the faculty has the highest performance in terms of students’ evaluation and head of the department (HOD) evaluation using data mining. The authors proposed three different classification techniques such as Decision tree, Naïve Bayes, and KNN algorithms. These were used to build classifier models that will determine the faculty performance. Their performances were compared over a dataset composed of responses of students and evaluation coming from the HOD using accuracy, precision, and recall. According to the results, the Nave Bayes classifier demonstrated the lowest accuracy over other classifiers that separate the most important variables, "Strongly Agree" and "Agree," with an accuracy of 91.67 percent based on student perception. This result can be a big help to the faculty and administration in decision making in what ways the faculty members can improve their performances where it is most needed.