Interior Architecture Design Project: A Halal Restaurant Integrating the Culture of Songkhla, Thailand
สร้างเอกลักษณ์เด่นเเก่สงขลาทางด้านอาหาร
คณะวิศวกรรมศาสตร์
A platform that aims to connect students from all faculties and departments to promote joint activities and develop effective social and collaborative skills, focusing on: Promoting learning and self-development through reviewing lessons and collaborative learning that are relevant to all faculties and departments in the university, creating a space for negotiation and exchange of knowledge, and supporting joint activities to build relationships and cooperation among students.
คณะวิทยาศาสตร์
This special problem aims to compare the performance of machine learning methods in time series forecasting using lagged time periods as independent variables. The lagged periods are categorized into three groups: lagged by 10 units, lagged by 15 units, and lagged by 20 units. The study employs four machine learning methods: Decision Tree (DT), Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM). The time series data simulated as independent variables diverse including characteristics: Random Walk data, Trending data, and Non-Linear data, with sample sizes of 100, 300, 500, and 700. The research methodology involves splitting the data into 90% for training and 10% for testing. Simulations and analysis are performed using the R programming language, with 1,000 iterations conducted. The results are evaluated based on the average mean squared error (AMSE) and the average mean absolute percentage error (AMAPE) are calculated to identify the best performing method. The research findings revealed that for Random Walk data, the best performing methods are Random Forest and Support Vector Machine. For Trend data, the best performing methods are Random Forest. For Non-Linear data, the best performing methods are Support Vector Machine. When tested with real-world data, the results show that for the Euro-to-Thai Baht exchange rate, the best methods are Random Forest and Support Vector Machine. For the S&P 500 Index in USD, the best performing methods are Random Forest. For the Bank of America Corp Index in USD, the best performing methods are Support Vector Machine.
คณะเทคโนโลยีการเกษตร
This research aimed 1) to study the problems and needs in the packaging design of the community enterprise group 2) to develop packaging for the community enterprise group 3) to study the satisfaction with the packaging design of the members of the Klong Dan Shrimp Paste Community Enterprise Group 3 Klong Dan Subdistrict, Bang Bo District, Samut Prakan Province, consisting of 9 members The study found that the community enterprise group faced the problem of lacking suitable packaging for souvenirs and had a need to develop packaging that is appropriate for this purpose. The packaging material selected was paper, with a rectangular shape including a handle for portability It can be folded for easy transportation and stacked for storage, while maintaining durability The packaging color used was light brown, and the label color was white The label included the following details: shrimp paste recipe, ingredients, manufacturing and expiration dates, the background of the community enterprise group, a QR code, phone number, a short story, group name, production site, as well as illustrations of the group’s location and red krill. The results of developing packaging for the community enterprise group indicated that the new packaging design increased the credibility of the product, building customer confidence in the product. Regarding the satisfaction with the packaging design among the group members, it was found that Packaging Design 1 had the highest level of satisfaction (x ̅ = 4.57, S.D. = 0.22). Among the aspects, color received the highest satisfaction score (x ̅ = 4.74, S.D. = 0.06), followed by the label (x ̅ = 4.69, S.D. = 0.10), while the lowest was the properties aspect, which was rated at a moderate level of satisfaction (x ̅ = 3.83, S.D. = 1.58), respectively.