What to eat today

H'ng, Ivan Zheng Quan (2023) What to eat today. Final Year Project, UTAR.

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Abstract

In recent years, the food industry has seen a significant increase in the variety of dishes and catering options available to consumers. This has led to an overabundance of choices, especially for people living in culturally diverse areas such as Kampar Malaysia. I, in particular, have always wasted a lot of my precious time on my three meal choices. Therefore, in order to address this challenge, my final year project aims to collect information through consultation and questionnaires in the Kampar area in order to develop a mobile application that will help users to make better choices by selecting and discovering food based on their preferences, dietary restrictions, and location in the Kampar area. This project is a data science design project for development purposes. We will illustrate this by building the application. The application to help choose food was implemented in the project as it is well-suited for analysis. The focus of the project is on the process of designing the application from the perspective of analysing data. The data science lifecycle consists of five distinct phases ranging from acquisition (data collection and data extraction), maintenance (data warehousing, data cleansing), processing (mining data, classification, data modelling and aggregation), analysis (exploratory qualitative analysis, confirmatory analysis, predictive analysis, and qualitative analysis) to communication (data reporting). This project also highlights the importance of data as a factor influencing food choices and how it can be incorporated into data processes to aid analysis and use in design work. The tools used in this project were Flutter and Android Studio. Regarding data collection and data analysis/design, the application was developed by collecting restaurant data with the help of Google Maps Service and then performing manual calculations for classification and analysis. This includes using some questionnaires to get the user preferences etc. and then categorising them into data that can be calculated. The output material for this project will be DART, Flutter, and Android Studio programs etc.

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