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.

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.