UM Research (University of Mindanao)
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Workforce Diversity and Employee Performance among Officers in LGU Panabo City
No full textThis study explored the link between workforce diversity and employee performance in LGU Panabo offices. Diversity was assessed in terms of education, gender, ethnicity, and socio-cultural background. A non-experimental quantitative approach was used, with 269 LGU Panabo City employees surveyed through questionnaires. Data reliability and validity were ensured through statistical analysis and expert reviews. Results showed that LGU Panabo City promotes workforce diversity, resulting in positive interactions and attitudes among employees. The organization treats all employees equally. Workforce diversity received a high mean score of 4.06, as did employee performance with a mean of 3.87. Furthermore, the study found a significant relationship between workforce diversity and employee performance in LGU Panabo offices, indicating that a diverse workforce positively impacts employee performance in the organization
Assessing the Influence of Social Interaction on Student’s Learning
No full textThis study dealt on the influence of social interaction on students learning. The main goal of the study was to determine the significant influence of social interaction on students learning. The study was conducted at Balagunan Elementary School and Tulalian Elementary School in the municipality of Sto. Tomas Davao Del Norte involving 110 Grade VI pupils, as respondents of the study. Mean, Pearson (r) and Multiple Regression Analysis were the statistical tools used for the data treatment. Results showed a high level of social interaction in terms of teacher- student partnership, student-student partnership, family involvement, teacher- school community partnership and school community- community at large. The study also showed a high level of students learning in terms of physical health and well-being, connectedness, social-emotional development, school experience and use of after school time. Furthermore, there was a significant relationship between social interactions on the students learning. Therefore, all the domains in the social interaction as independent variable influenced the dependent variable students learning
Consumer\u27s Attitude and Eco-friendly Products among Selected Vegetable Suppliers in Panabo City Supermarket
No full textThis study aimed to determine the relationship between consumer’s attitude as independent variable and eco-friendly products as dependent variable among selected vegetable suppliers in Panabo City supermarket. This study used adapted questionnaire and universal sampling technique. The statistical tools used were weighted mean and Pearson-r, and a quantitative descriptive correlational design was employed. The researchers found out that the overall mean in consumer’s attitude is 4.52, indicating a high level, while the eco-friendly products mean is 4.62, also indicates high level. The r-value is 0.569 and the p-value is 0.000, thus the null hypothesis (Ho) was rejected since the p-value is less than 0.05. It means that there is a significant relationship between consumer’s attitude and eco-friendly products among selected vegetable suppliers in Panabo City supermarket
Comparison of Supervised Machine Learning Approaches in Predicting Employability of Students
No full textThis study investigates the efficacy of various supervised machine learning approaches in predicting the employability of graduates using data from mock job interviews conducted in multiple universities and agencies across the Philippines. Employing a dataset comprising 2,982 observations, the research aims to determine which machine learning algorithm—NaiveBayes, Logistic Regression, k-nearest neighbors (IBK), or Random Tree—yields the most accurate predictions. Additionally, the study assesses the impact of eight non-cognitive factors on employability: general appearance, manner of speaking, physical condition, mental alertness, self-confidence, ability to present ideas, communication skills, and student performance rating. Using WEKA software, the analysis reveals that the Random Tree algorithm provides the highest prediction accuracy, followed by k-nearest neighbors. The findings underscore the significance of non-cognitive skills in graduate employability, with general appearance, manner of speaking, and physical condition emerging as the top predictors. This research highlights the potential of machine learning in enhancing employability outcomes by identifying critical attributes that influence job market success
The Financial Literacy and Entrepreneurial Intention among Young Professionals
No full textEntrepreneurial activity is perceived as vital mechanism to attain social development and economic progress. To ensure a continuous supply of entrepreneurs, it must be identified what determinants can led in shaping the intention in venturing entrepreneurship. However, factors affecting entrepreneurial intention suchlike, the association of financial literacy towards entrepreneurial intention have not been adequately investigated in the local setting. Hence, to cover the gap, a study using a quantitative non-experimental research design based on a correlational technique was carried out. This research aims to ascertain the relationship between financial literacy and entrepreneurial Intention. Data was collected from 150 young professionals residing in Tagum City, using a random sampling technique. The findings of the study showed that financial literacy has a positive influence on young professionals’ entrepreneurial intention. Therefore, when the financial literacy of young professionals is high, the entrepreneurial intention is also observed to be high. The recommendation of this research is to support the importance of acquiring enough financial education for young professionals and for further improvisation of the educational curriculum in higher education institutions to encourage students in considering entrepreneurship as a career path in the future
A Feasibility Study of Academic Tutoring Services in Cateel, Davao Oriental
No full textThis feasibility study evaluates the viability of launching Academic Tutoring Services in Cateel, Davao Oriental, focusing on its cost-effectiveness and potential market dominance. Initiated in response to the shift towards virtual and modular learning systems due to the COVID-19 pandemic, the proposed business aims to address significant educational challenges faced by students from kindergarten to grade 10. The study thoroughly assesses the marketing, management, financial, and socio-economic aspects of the business, demonstrating that the service is not only needed but also financially viable. Key findings indicate that the service could effectively monopolize the local market due to the high demand for personalized educational support, which current providers are unable to fully meet. Financial projections show a promising return on investment with steady growth in service revenue over five years, underpinned by comprehensive marketing strategies and operational plans that ensure cost-efficiency. Furthermore, the business is set to provide substantial social benefits by offering employment opportunities to teachers and enhancing educational outcomes for students. The overall analysis confirms that Academic Tutoring Services could be a sustainable and profitable venture, contributing positively to the educational landscape of Cateel, Davao Oriental
Predicting Customer Churn in Travel and Tour Industry Using Machine Learning Algorithm Approaches
No full textPredicting customer churn in the airline sector of tour and travel poses unique challenges, necessitating advanced machine learning approaches to proactively tackle dissatisfaction, optimize service reliability, and fortify loyalty within fluctuating travel patterns and preferences. This study analyzed the application of machine learning algorithms to predict customer churn in the tour and travel industry. Leveraging data obtained from Kaggle, including factors like frequent flights, annual income, and social media engagement, the study employs various classifiers and attribute selection techniques to identify key predictors of churn. Through rigorous evaluation using five-fold cross-validation, the J48 decision tree classifier emerges as the most reliable model, achieving an accuracy of 84.53% and demonstrating good agreement. The findings underscore the potential of machine learning in enabling proactive customer retention strategies and enhancing business performance in the tour and travel sector
Assessing Destination Competitiveness of Mati City: Utilizing Importance-Performance Analysis
No full textThis paper aims to assess the destination competitiveness of Mati City utilizing importance-performance analysis. This paper utilized a quantitative, non-experimental design using the correlation technique to recognize the different scales in the importance analysis of Mati City as a destination when examining 516 beach goers. The study used descriptive statistics, frequency, mean, Pearson r, and ANOVA for the statistical tools. The study reveals the competitive importance of Mati City as a Tourist Destination concerning services, safety and security, attraction, Festival, transportation, and cuisine are found to be very important. Thus, developing a competitiveness model for destinations could assist tourism stakeholders in the public and private sectors in identifying the location\u27s strengths and weaknesses from the viewpoint of travelers, as well as in highlighting chances for tourism development and formulating plans to address any risks to future tourism. The competitive performance of Mati City as a Tourist Destination was outstanding in terms of services, safety and security, attraction, festivals, transportation, and cuisine. Therefore, development results should be given more weight in tourist performance evaluations. The results show that Mati City has an outstanding destination performance overall. This does not, however, imply that Mati City does not require renovation. Several sectors need upgrading to boost Mati City\u27s standing as a travel destination. The results show that transportation rates are the best, indicating that Mati City has a solid infrastructure that increases efficiency and supports the tourism industry. Lastly, there is no significant difference in sex, age, and marital status, while educational attainment significantly differs in assessing the destination competitiveness of Mati City utilizing performance analysis
Attitude Towards Science and Science Process Skills of Junior High School Students
No full textThis paper incorporated attitude towards science and science process skills as the independent variable (IV) and dependent variable (DV), respectively. This study aimed was to determine the relationship of attitude towards science and science process skills of junior high school students of Bongabong National High School through employing quantitative non-experimental process using correlation technique, with 275 students enrolled for the academic school year 2020-2021 as respondents. Mean, Pearson (r), and Regression Analysis were used as the statistical tools for data treatment. Results revealed students’ very high level of attitude towards science in terms of academic value, science activity, and classroom environment, and their science process skills at a moderate level in terms of basic process skills and integrated process skills. Accordingly, results showed no relationship between the students’ attitude towards science and science process skills which depicts that no domains of attitude towards science that relates to the science process skills of junior high school students of Bongabong National High School
Analysis of Filipino Family Households Income Classification and Expenditure Patterns Using Machine Learning
No full textThis study employs machine learning algorithms to analyze income and expenditure patterns in Filipino family households, aiming to support socioeconomic development and effective policy-making. Utilizing a comprehensive dataset from across the Philippines, which includes demographic details, monthly income, and expenditure data, the study applies Naïve Bayes, IBk, and decision trees to categorize household income levels and identify spending trends. Among the 11 algorithms tested, Naïve Bayes proves most effective, achieving the highest accuracy rate (70%), F-measure (0.695), and kappa statistics (0.5579). By leveraging these machine learning techniques, the research provides nuanced insights into the financial behaviors of Filipino families, enhancing the precision of socioeconomic planning and resource allocation. This analysis not only facilitates a deeper understanding of economic stability at the household level but also aids in tailoring governmental support to those in need, particularly during challenging economic times