Over time, people needs are increasing. Needs that must be met, often cause problems in the people in determining a choice. People must make the right choice and according to their needs. Not an easy thing for people to make these choices. Therefore, a recommendation system is needed to support people in making decisions that fit their criteria. This research provides a system that can provide recommendations for decision support people according to their criteria, which are web-based. The decision-making system in this research uses the analytical hierarchy process (AHP) method. AHP is a multi-criteria decision-making method, which in this research one of the criteria is using sentiment analysis. Sentiment analysis is the process of understanding, extracting, and processing textual data to get sentiment information from an opinion sentence. The opinion sentiment value of each alternative will be included in the AHP calculation to get the best alternative recommendations according to the criteria of people. The result of this research is that the system can provide recommendations to people or users according to their criteria and alternatives as well as public opinion about each alternative.

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In Indonesia, there are many types of cakes that are categorized as traditional snacks. Refer to the Kamus Besar Bahasa Indonesia; snacks are defined as foods that are peddled or mean bites. Snacks are classified based on how they are made, and some are based on the taste of the snacks. Traditional snacks are a part of Nusantara culture that is mandatory for those born and live in Indonesia to preserve them. But in reality, many people tend to consume and know more about modern snacks than traditional ones. In fact, not many people have even tried traditional snacks or even made their own at home. This application was developed to help people distinguish and recognize the various kinds of cakes on the market. With convolutional neural networks technology in machine learning, people can use image classification presented through mobile applications with accuracy above 90% for Indonesian traditional cake recognition.

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Indonesia is very vulnerable to flooding due to urbanization of land use, industrialization and made worse by climate change. Sidoarjo is an urban area that frequently experiences regular flooding every year. The flooding break up local traffic, disrupting economic distribution and transportation routes. Minimum information about areas that are often flooded causes a lack of people and government attention to the effects of floods. In this paper, we develop a Fuzzy approach to determine the level of urban flood risk in Sidoarjo. The parameters consist of flood inundation, rainfall, population affected, and drainage. The Fuzzy sets produce fuzzy membership values, and evaluation rules determine the level of flood disaster in each village in Sidoarjo, classified into three levels of vulnerability, they are high, medium and low level of flood vulnerability. Analysis of the results of the calculation of flood risk assessment with Fuzzy multi-criteria decision making (FMCDM) shows a good result with accuracy of 66% compared to the analysis of the Sidoarjo Regional Disaster Management Agency inundation data. However, in reality flood risk is not only caused by inundation factor, the FMCDM method is represented a better assessment in real world. The spatial decision support system using geographical information systems (GIS) provides effective, efficient and useful in flood risk management for local and national governmental agencies.