This study aims to analyze the growth trend of covid-19 using prediction algorithms in data mining for covid-19 data throughout Indonesia. This can be used as a decision support to analyze several government policies towards regulatory intervention so far. The method used is the best prediction method in time series data, including Neural Network, SVM, Linear Regression, K-Neirest Neighborn and optimizes it with optimization algorithms. This research is focused on the application of these applications. It is hoped that this research will produce an analysis of the growth trend of Covid cases every day, in addition to its contribution so that it can assist the government in determining the best policy direction and also as an education to the public. in addition, the research will contribute to science in the field of predictive analysis by finding the best RMSE formulation. The results of this study show that Neural Network-Particle Swarm Optimization has the smallest Roort Mean Square Error which is 265,326, and the two Neural Network Genetic Algorithm are 266.801, Neural Network Forward Selection is 275,372 and Neural Network without optimization has the largest RMSE which is 297.204. These results can be used as a reference for the use of similar algorithms in time series data, both Covid-19 data and other data.

Sektor wisata merupakan hal yang menjadi perhatian pemerintah pada saat ini. Peningkatan terhadap pengelolaan tempat wisata khususnya di Provinsi Gorontalo menjadi perhatian melalui Dinas Pariwisata. Tujuan penelitian ini yaitu dengan membuat aplikasi berbasis mobile android dengan teknologi Geographic Information System guna mempermudah wisatawan nusantara dan mancanegara untuk eksplorasi ke daerah Gorontalo. Metode pengembagan aplikasi ini yaitu prototype dengan membuat aplikasi yang kemudian akan disempurnakan melalui proses permintaan dari user. Aplikasi ini memberikan kemudahan dari segi informasi tempat wisata, rute jalan, serta tarif dari setiap tempat wisata yang akan dikunjungi. Dengan adanya aplikasi wisata Gorontalo selain mempermudah wisatawan juga meningkatkan perekonomian masyarakat karena meningkatnya jumlah kunjungan wisatawan nusantara dan mancanegara di daerah Gorontalo.

This research was conducted at SMK N 3 Gorontalo, which aims to develop learning media applications using augmented reality technology. At first the teaching system only led to conventional teaching, namely through power point teaching materials and print media as well as the lack of available hardware or network equipment and the absence of computers that were ready to be disassembled and then developed using augmented reality technology. Through this research, it is hoped that the learning process will be more interactive. This application was developed using a prototype system development method that has a Requirements Gathering and Analysis phase, Quick Design, Build Prototype, User Evaluation, Refining Prototype and Engineer Product. The result of this study is a software application, namely an android-based augmented reality technology learning media application.

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This research aims to propose new solutions for alternative sources of electrical energy in open spaces. We validated this solution by implementing a solar cell in a park bench object. Furthermore, analyzing the statistical data by taking the average value of; current, voltage, and power generated by the smart bench object. The experimental results show that the proposed solution has the same performance as conventional lighting. Electric park benches can operate longer using a solar cell with an output power of 26.76 Watt-peak hours. With the large potential of solar power, solar cells' application in an open environment is very suitable. With this electric bench, it is still energy efficient and green energy