The food service industry has increasingly adopted e-commerce as a means of improving service and accessibility for customers. The popularity of e-commerce mobile applications has also surged due to their convenience on mobile devices, which have become an integral part of people's daily lives. These applications enable businesses to enhance their market presence and attract a larger customer base. Additionally, food businesses are utilizing Financial Management Systems (FMS) to effectively track cash inflows and outflows. FMS is typically integrated with various features such as sales and inventory tracking. The primary objective of this study was to develop an e-commerce coupled with a financial management system and its mobile application counterpart. The employed methodology for this study was descriptive research. A survey was conducted to evaluate the acceptability of the system based on functionality, usability, reliability, performance, and supportability (FURPS) criteria. The developed system received a favorable rating, with a weighted mean of 4.05. This indicates that the system successfully executed required tasks, offered user-friendly features, effectively monitored orders, consistently performed, and was accessible from any device.

Learning programming languages like Python can be difficult, especially for those who have no background in the subject. This study intends to design a mobile application and online Python learning lesson to solve the challenges experienced by senior high school S.T.E.M. students. S.T.E.M. students in senior high school who participated in a survey found that academic pressure, a lack of engagement, and a lack of practice chances were the main issues affecting their learning experience. For beginner to advanced levels, the PySkuwela provides a user-friendly interface with video tutorials, hands-on activities, and assessments. The PySkuwela forum promotes student cooperation and knowledge exchange. Students may study Python conveniently and without added academic pressure thanks to the self-paced learning strategy. The FURPS evaluation gave the system an overall acceptability rating of 4.21, which is a high level of agreement. According to the study’s findings, the created system is advantageous and appropriate for senior high school S.T.E.M. pupils, offering a thorough platform for learning Python.

E-commerce shows steady growth in the marketplace since it makes the lives of people easier. Today’s generation is more inclined toward convenience in purchasing goods. The COVID-19 shut down many food establishments across the Philippines, resulting in an online bakeries boom. Pastries are one of the most sought goods online, especially with the pandemic surge where physical stores are seldomly open. E-commerce with a recommender system is the trend that helps customers choose products, which helps in decision-making on what to purchase. On the other hand, a mobile application counterpart could increase brand recognition and customer engagement as it is now the most effective, direct, and personalized way to deliver product information. In this study, the descriptive research method was used, with a questionnaire using the functionality, usability, reliability, performance and supportability (FURPS) serving as the instrument for testing the acceptability. The overall quality of the system was given an acceptable rating with a weighted mean of 4.07, indicating that the system’s functions were well integrated, that navigation was simple, performed consistently, and that the system was accessible regardless of device.

While several content management systems (CMS) and audience analytics tools are available for digital signage in the market, they are often sold separately and can be expensive. Therefore, this project aims to design a cost-effective and unified web-based solution for digital signage that combines content management and audience analytics functions, reducing the need for multiple purchases. This can be achieved by utilizing Raspberry Pi technology, known for its cost-effectiveness and versatility in integrations, along with a face recognition camera and machine learning methods. This proof of concept demonstrates the integration of these components to create a dynamic digital signage system. Overall, this project has the potential to offer an affordable solution for companies aiming to efficiently manage and optimize their digital marketing strategies, especially in the Digital Out-of-Home (DOOH) Advertising space.

Online shopping has become one of the most prominent forms of retail for businesses. This is due to the advancement of web services, and mobile applications that have become accessible, and effective with the utilization of the Internet. Accordingly, this study aims to further scrutinize the discussed application of online shopping. Therefore, an online retail system with mobile application through Android was developed, deployed with the purpose of managing the products, and services that are offered by the company, with the standardization of data forecasting to make accurate prediction of future trends. To standardize and validate the attributes of the said system, a descriptive research method that used a survey instrument based on the Likert scale, and the functionality, usability, reliability, performance, and supportability (FURPS) model. The said survey instrument collected 200 responses with purposeful sampling treatment and converted into distinct inputs with the use of the weighted mean formula. The functionality, usability, and reliability were rated as acceptable, with weighted means of 4.5, 4.5, and 4.5, respectively. The performance and supportability were rated as perfectly acceptable, with weighted mean scores of 4.7 and 4.6, accordingly. The system’s overall attributes were rated perfectly acceptable, with a weighted mean of 4.6, suggesting that it managed and analyzed sales, services, and inventory data.