Authors :
Emmanuel G. Galupo Jr.; Jeffrey F. Calim; Emmie Faye Marione L. Matabile; Johani D. Basaula; Luisa M. Mariano; Arnel Balasta; Aerob C. Robles; Antoniette C. Mariano
Volume/Issue :
Volume 9 - 2024, Issue 1 - January
Google Scholar :
http://tinyurl.com/4ktjr2k9
Scribd :
http://tinyurl.com/42khcn3e
DOI :
https://doi.org/10.5281/zenodo.10715027
Abstract :
In order to grow, businesses nowadays
must ob- tain customer feedback, such as reviews
or comments. They are thereby collecting additional
information. The process of manually collecting and
analyzing data is becoming more and more onerous
for the owners of these changes. The purpose of this
research is to develop an algorithm-based system that
can au- tomatically extract data and support business
activities. The tech- nology will reduce the effort of
human workers in data analysis because it will
automatically examine the entered data. It features a
sentiment analysis graph. It also offers a word cloud
that makes things easy to comprehend for the business
administrator by displaying the most relevant
keyword in different sizes according to how
frequently the system identified the word from
reviews or collected data. The system will forecast
which department or sector of the enterprise needs
improvement. The researchers will build the system
using the Iterative System Design Life Cycle since
it is most equipped for handling erratic behavioral
shifts and even data science. Using brainstorming
approaches, the project concept and approach for
this study were explored or written. The
instruments for requirements formulation, such as
customer interviews and system functionality,
usability, and security assessments, must be chosen
by the researchers.
Keywords :
Sentiment Analysis, Machine Learning, Feed- backs, Sentiment, Multinomial Na ̈ıve Bayes.
In order to grow, businesses nowadays
must ob- tain customer feedback, such as reviews
or comments. They are thereby collecting additional
information. The process of manually collecting and
analyzing data is becoming more and more onerous
for the owners of these changes. The purpose of this
research is to develop an algorithm-based system that
can au- tomatically extract data and support business
activities. The tech- nology will reduce the effort of
human workers in data analysis because it will
automatically examine the entered data. It features a
sentiment analysis graph. It also offers a word cloud
that makes things easy to comprehend for the business
administrator by displaying the most relevant
keyword in different sizes according to how
frequently the system identified the word from
reviews or collected data. The system will forecast
which department or sector of the enterprise needs
improvement. The researchers will build the system
using the Iterative System Design Life Cycle since
it is most equipped for handling erratic behavioral
shifts and even data science. Using brainstorming
approaches, the project concept and approach for
this study were explored or written. The
instruments for requirements formulation, such as
customer interviews and system functionality,
usability, and security assessments, must be chosen
by the researchers.
Keywords :
Sentiment Analysis, Machine Learning, Feed- backs, Sentiment, Multinomial Na ̈ıve Bayes.
