Geographically and demographically, Indonesia has natural conditions that have the potential for floods disaster. There are at least 16,771 islands and 65,017 rivers that fill the archipelago. Unfortunately, the ever-increasing urban population accompanied by a lack of awareness and preparation for protecting the environment has resulted in a higher risk of flooding in urban areas. This study utilizes digital imagery to detect flood conditions in urban areas. In terms of access, digital images are available in urban CCTV monitoring systems as well as office areas, housing, and from people who have smartphones. The detection method used in this study is the VGG19 model which consists of 16 convolution layers and 3 standard classification layers. All convolution layers are divided into 5 blocks followed by a MaxPooling layer for each block to reduce the resolution of the input image. In the last layer, SoftMax layer is used to estimate the probability between flood labels and normal conditions. There are 4 parameters that were optimized during the VGG19 model training process, namely Batch Size, Learning Rate, Dropout and Epoch (training repetition). To test the proposed model, public datasets are used, namely the Roadway Flooding Image Dataset and Road Vehicle Images Dataset. The best flood detection results (or normal conditions) achieve the accuracy of 98.78%. As for the other three performance metrics, namely precision, recall and F1-score, they reach 99%. These results are generated by the VGG19 model with a Batch Size parameter of 20, a Learning Rate of 1e-5 (0.00001), 50% Dropout and 100 Epoch. The achievement values of the four metrics can be considered quite good, so that the VGG19 model has the opportunity to be developed for flood detection applications in order to monitor urban flood conditions.

Badung Regency, Bali is one of the famous tourist destinations in Indonesia that offers a variety of attractive tourist attractions. However, the lack of organized information access and the deficiency in selecting travel packages that suit user preferences can be obstacles in maximizing the tourism potential in the region. This research aims to develop a web-based tourism information system with a Decision Support System (DSS) feature using the Fuzzy Analytic Hierarchy Process (AHP) method in Badung Regency, Bali. The system is developed using the SDLC development method with a waterfall approach, which functions to provide information access about tourism objects, including their names, categories, photos, and descriptions. The main feature is the DSS that assists users in selecting travel packages based on their preferences, using five criteria: price, number of attractions, duration, popularity, and rating. The system also supports multi-level access for regular users and admin users responsible for creating posts and travel packages.

Before buying a laptop, you need to pay attention to the specifications and standards that are tailored to your needs and requirements. Some of the standards and requirements include looking at several aspects of the criteria including RAM (random access memory), laptop prices, hard disk capacity, processor, screen size, VGA (video graphic adapter), battery power, availability of spare parts, laptop weight, distance to service centers, long warranty. The fuzzy method is an algorithm used to find a value that is still vague and also linguistic, using the TOPSIS algorithm (Technique for Order by. Similarity to Ideal Solution) to support calculations in decision-making. Determination in using the TOPSIS algorithm results from careful calculations. From the results of calculations using the TOPSIS algorithm, the total ideal positive and negative ideal values ​​are generated with the following ratings: laptop 5 with a value of 4.637 in rank 1, laptop 3 with a value of 4.174 in rank 2, laptop 4 with a value of 4.077 in rank 3, for laptop 1 with a value 3.880 is ranked 4th, and laptop 2 with a value of 3.472 is ranked 5th.
 
Keywords: fuzzy, TOPSIS, laptop.