In the rapid development of the food and beverage industry, overproduction and unsold food have led to a high amount of food waste, making Indonesia one of the largest food waste producers in the world. Data from the Central Bureau of Statistics (BPS) in 2021 shows that Indonesia produces 23-40 million tons of food waste annually, which negatively impacts the environment, natural resources, and the economy. This research aims to create a website that serves as a platform for selling leftover food to reduce food waste issues in Indonesia. The method used in designing this website is the Design Thinking method, which consists of five stages: Empathize, Define, Ideate, Prototype, and Test. Data for this method is collected through surveys and interviews with respondents. By creating this website, it is hoped to connect food business operators, such as restaurants, cafes, and bakeries, with consumers, allowing them to interact and providing an effective solution to reduce food waste in Indonesia. Additionally, it is expected that this website can minimize the waste of still-edible food for everyone. By ordering through this online platform, customers can get food at half the normal price.

Online learning is widely used by various groups, especially in higher education/schools. Online learning has many benefits for students and lecturers due to its practical and flexible learning process. However, there are complaints in online learning, such as students having difficulty understanding the material shared by lecturers and the lack of interaction between lecturers and students, making the lessons monotonous and boring. Students also cannot review the targeted lecturers. Therefore, the Midori Clon application was created to address students' problems in online learning. The application design was developed using the Design Thinking method. The Midori Clon application offers several advantages, including a Live Video feature for more interactive sessions between students and lecturers, a Bot feature to summarize materials and translate languages, and a Lecturer Review feature to review the targeted lecturers. With these advanced features, it is expected that online learning issues can be resolved and online learning can meet the desired expectations.