The Academic Resources Recommender System (ARReS) includes collection of Theses and Dissertations available in the Camarines Sur Polytechnic Colleges Library.
Amidst the pandemic, education has remained an important sector that must continue for the children are the hope of the nation. With this, the government launched an online learning modality with the support and cooperation of the responsible government agencies allowing the students and teachers to continue their education without compromising their health and safety. Hence, this study was conducted to analyze and classify sentiment tweets in the Philippines on the said implementation of online learning. Quantitative research design was used for the study for it needed to collect a large data. The dataset is composed of 10001 tweets which are categorized as positive, negative, and neutral. Upon the evaluation of the data model, the researchers noticed that having inadequate data affects the performance and prediction accuracy of the sentiments analysis. Moreover, the results showed that the Neutral is prevailing with 46.9% followed by negative with 45.1%, and lastly positive with only 8.5% tweets. With the help of some classifiers the accuracy rate of the model has been determined; Multinomial Naïve Bayes - 61%, Bernoulli Naïve Bayes -64%, and the Complement Naïve Bayes - 59%. In conclusion, neutral and negative tweets have a large amount of labeled data, whereas positive tweets have a small amount of data. Furthermore, it is more accurate to analyze input sample data when the labeled basis data is adequate; the more labeled data there is the stronger the analytical accuracy data gathered.
Lagyap, Jessabel A.; Nabor, Zion B.; Obrero, Jullius Fiel J.; Sinfuego, Ryan G.
2022 Computer ScienceThe topic model Latent Dirichlet Allocation (LDA) is used to classify text in a document to a certain subject. In connection with this, the study aims to develop a model that extracts themes from students’ perceptions and attitudes towards online classes, based on the data provided by the CSPC stude...
Efren A. Ballester III Jr.; Cheloja L. Gonowon; Edralynn T. Dimaiwat; Brent Louie H. Pontillas
2022 Information TechnologyDuring in this technological era where almost everything can be accomplished with the help of the machines and computers. This makes every individual’s task can be accomplished in a short period of time in which also enables us to proceed from one task to another task or both in terms of multitaski...
Elena Clarexe R. Gulane; Jan Marc P. Culas; Albert P. Aquilino; Manny C Miñolas
2022 Computer ScienceData mining techniques are used to generate significant patterns, then to build data models for prediction. In this connection, this thesis aimed to utilize Educational Data Mining to mine Grade 10students' Grade Point to select a Senior High School Strand using student data from the target school. ...
John Paul O. Albao; Ysidore Nick Botor; Jieneth A. Ituralde; Mark Josef Gastilo
2022 Computer ScienceDue to its geographic location, the Philippines is a flood-prone country. According to the Asian Disaster Reduction Center, the Philippines is one of the most flood-prone countries in the world. With limited resources and a major portion of the population living below the poverty line, flood impacts...