Development of an Online Management System for Village Homeowners’ Association

Elneo Albert E. Ancajas, Sheena Maeve P. Ambon, Joemark Luis S. Chan, Angelica B. Orido and Mengvi P. Gatpandan

José Rizal University, Mandaluyong City, Philippines

ABSTRACT

Every village has its own homeowner’s association consisting of people living in the same village and pay fees for maintenance. However, the vast population of the community might be problematic and inefficient when they have village transactions, appointments, or concern. The Online Management System for the Village Homeowners’ Association is proposed to resolve the problem. The objective of this study is to develop a web application that increase the productivity and emphasize the efficiency of the business process. The homeowners can use their computer devices to manage their transactions and appointments in the village, also to keep in touch with the administrators and to the whole community. The existing studies of literature related to this study prove the importance and convenience of having an online management system for village homeowners’ associations. This study used a Crisp-DM methodology with the data gathered from different resources. The system was tested using the evaluation form ISO 25010 and garnered an overall weighted mean of 3.74, equivalent to an excellent rate. This result showed that the system developed is functional, adequate, and streamlines the village’s processes and transactions.

Keywords: Village System, Management System, Village Homeowners’ Association, Online Management System, Homeowners’ Association, Village Association

Cite this Article:

E.A.E. Ancajas, S.M.P.Ambon, J.L.S. Chan, A.B. Orido & M.P. Gatpandan, “Development of an Online Management System for Village Homeowners’ Association,” J. Eng. Comput. Tech., vol. 2 no. 2, pp. 1-14, Aug. 2023.

Valorant Players’ Sentiment Analysis on Chat and Voice Toxicity

Johndel N. Encabo, Mark Kenneth L. Satsatin, Maria Cassandra B. Vitug, Rolando Barrameda, Emelyn Mayuga, and Josephine Eduardo

De La Salle University- Dasmariñas, City of Dasmariñas, Cavite, Philippines

ABSTRACT

This study is about sentiment analysis on text and voice chat toxicity among the players of Valorant Community in the SEA server. Since disruptive behavior became a major problem in Valorant chats, specifically in the SEA server, this study aims to determine the words that most players use for trash-talking and then determine in which medium most trash-talk comes from. Finally, we determined which sentiments are dominant. The data was collected through an online survey using Google Forms, which was distributed through different gaming communities in SEA with Valorant players. Through this method, researchers were able to get over 753 respondents, and from which, were able to gather over 8,117 English and Tagalog words, phrases, and sentences. Using Logistic Regression, the researchers were able to have a 90.22% accurate prediction, while using the Random Forest Algorithm allowed the researchers to get 85.88% of accuracy. However, this method is unable to determine neutral sentiment. In addition, the researchers were able to determine that the dominant sentiment in the gathered data was negative. Therefore, the researchers find that the Valorant community in SEA servers is dominated by disruptive behaviors rather than healthy conversation. Also, using Logistic regression gives a good performance in determining the sentiments in chat. Hence, the researchers recommend deriving an even more efficient way to gather data and use a deep learning technique to make precise predictions in sentiments.

Keywords: Trashtalk, Valorant, Random Forest Algorithm, Logistic Regression, Toxicity, Disruptive behavior, sentiment analysis

Cite this Article:

J.N. Encabo, M.K.L. Satsatin, M.C.B. Vitug, R. Barrameda, E. Mayuga, & J. Eduardo, “Valorant Players’ Sentiment Analysis on Chat and Voice Toxicity,” J. Eng. Comput. Tech., vol. 2 no. 2, pp. 15-35, Aug. 2023.

Predicting the Popularity of K-pop Songs among Students Based on Spotify’s Audio Features using Support Vector Machine and Decision Tree

Lalaine Joy C. Bejarin, Francheska Christine C. Mojica, Samantha P. Sampot, Maryli F. Rosas, Josephine T. Eduardo, Emelyn D. Mayuga, and Rolando B. Barrameda

De La Salle University- Dasmariñas, City of Dasmariñas, Cavite, Philippines

ABSTRACT

This study aimed to predict the popularity of K-pop songs using Support Vector Machine and Decision Tree. The dataset used in the study was obtained through an online survey where participants were asked for their age, sex, year level, and ten favorite K-pop songs. By the end of the data gathering procedure, the proponents were able to acquire 1000 samples of data from senior high school and college students. Meanwhile, the audio features of the songs entered by the respondents were obtained through Spotify API. Through feature selection, the proponents determined that danceability, energy, mode, and valence were the best features to use for the Support Vector Machine model. This model yielded an accuracy score of 58%, a precision score of 50%, and a recall score of 66%. On the other hand, energy, key, acousticness, and tempo were used for the Decision Tree model, which earned an accuracy of 51%, precision of 55%, and recall of 62%. The study demonstrates that although no single formula can predict the success of K-pop songs, key audio features offer significant insights. Practical implications suggest musicians and producers can benefit from understanding these features, and the findings lay the groundwork for future research in K-pop music analytics.

Keywords: K-pop, support vector machine, decision tree, Spotify API, audio features, popularity

Cite this Article:

L.J.C. Bejarin, F.C.C. Mojica, S.P. Sampot, M.F. Rosas, J.T. Eduardo, E.D. Mayuga, & R.B. Barrameda, “Predicting the Popularity of K-pop Songs among Students Based on Spotify’s Audio Features using Support Vector Machine and Decision Tree,” J. Eng. Comput. Tech., vol. 2 no. 2, pp. 37-53, Aug. 2023.

Early Warning Bike Assistant using Mobile Android Application

Irwin Maxwell T. Day, Joh-Ann P. Golingan, Mark Joshua S. Tabor, and Amelia S. Liwanag

De La Salle University- Dasmariñas, City of Dasmariñas, Cavite, Philippines

ABSTRACT

Bicycling offers health benefits and reduces exposure to traffic. However, it also poses high risks due to cyclists’ limited ability compared to motorized vehicles. Regular checking for rear or slight of sight can reduce safety and prevent accidents. The researchers aim to enhance cyclist safety by using a mobile application that uses GPS data and internet connection for accurate GPS locator. The application uses a sensor on the rear of the bicycle, with an in-voice alert system and color indication. The device can stop detection when the bike is on standby or stops at intersections. A Bluetooth module is used for hardware connection. The mobile application requires user information, including first and last names, passwords, and email and stores an activity history log. However, it does not work offline and does not measure vehicle momentum. The study tested the research prototype and Android application for accuracy, functionality, and performance. The prototype performed well in 4-5 second latency but had inconsistent results with 2.5 second delay. The project improves cyclist safety and prevents accidents using a mobile Android app with an in-app voice assistant.

Keywords: Android Application, In-app Voice Assistant, Early Warning System, Ultrasonic Sensor, Mobile Application

Cite this Article:

I.M.T. Day, J.P. Golingan, M.J.S. Tabor, & A.S. Liwanag, “Early Warning Bike Assistant using Mobile Android Application,” J. Eng. Comput. Tech., vol. 2 no. 2, pp. 55-58, Aug. 2023.

JOURNAL OF ENGINEERING, COMPUTING AND TECHNOLOGY

The Journal of Engineering, Computing and Technology (JECT) is a scholarly peer-reviewed, and academic research journal for engineers, computer scientist, academicians, and research scholars aiming to publish innovative, state of the art results coming from research and advances in different aspects of engineering, architecture, computer science and information technology.  JECT is dedicated to the dissemination of advanced technologies that will be beneficial to professionals and academic researchers. It is a bi-annual publication published by the University Research Office, De La Salle University-Dasmariñas.

The journal is governed by an editorial board whose members specialize in each of the mentioned disciplines.  The editor in chief is elected by the members of the editorial board.

Editorial Board

Editor-in-Chief

Maryli F. Rosas, DIT (Computer Science, De La Salle University-Dasmariñas)

Associate Editor

Ma. Cristina A. Macawile, PhD (Engineering, De La Salle University- Dasmariñas)

Managing Editor

Mr. Jaime Zeus C. Agustin (University Research Office, De La Salle University-Dasmariñas)

Members

Paulino H. Gatpandan, DIT (Computer Science, De La Salle University- Dasmariñas)

Maryjoie A. Lituanas, MSES (Engineering, De La Salle University- Dasmariñas)

Mengvi P. Gatpandan, DIT (Computer Science, Jose Rizal University, Mandaluyong City)

Daniel Dasig Jr., PhD (Field, Change Management Engineer, TELUS Communication Inc., Canada)

Nestor Tiglao, PhD (Electrical and Electronics Engineering Institute, University of the Philippines – Diliman)

Atty. Rudolph Val F. Guarin (Field, FGNG Law Office)

Prof. Sonia M. Pascua (Field, Drexel University, United States of America)

Brojo Kishore Mishra, PhD (Department of CSE, School of Engineering, GIET University, Gunupur, India)

Valentina Emilia Balas, PhD (Automation and Applied Informatics, Intelligent Systems Research, University of Arad, Romania)