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Universitas Negeri Yogyakarta is one of the state universities in Indonesia that assigned Student’s Single Tuition Fee (UKT) policy. UKT is an Indonesian government policy of tuition fees charged to every student with nominal based on the student’s financial capabilities. Although the implementation of UKT nominal has been arranged in such ways, there are problems occurred, such as inconsistency and inaccuracy of UKT nominal classification. This causes so many dissatisfactions between students to the UKT nominal that did not meet the expectations and raises questions about the transparency of the determination of student’s UKT nominal. Therefore, the application of Fuzzy Multi Attribute Decision Making (FMADM) can improve the accuracy and the effectivity of the determination of student’s UKT nominal also answering the student’s questions and giving clarifications about student’s UKT nominal. The result of this research was an Android-based application that can be used for determining student’s UKT nominal and determining what group that nominal belongs to with ease for under 5 minutes fast. With this android application, determining and calculating student’s UKT nominal will be much faster and more accurate when groupping the UKT nominal than the conventional method used before.

As a rice-producing plant, rice plant (Oryza sativa L.) is one of the most important crops in Indonesia. Rice production is increasing every year along with an increase in rice demand and population.The amount of rice production is affected by the condition of the rice plants. The worse the condition of rice plants, the rice production will also lower. Rice plant is very susceptible to diseases or pests that can reduce its productivity, including brown spot disease, leaf smut and bacterial leaf blight. As the development of science and technology, currently known as Artificial Intelligence. Artificial intelligence is a combination of several scientific disciplines such as mathematics, statistics, computer science, and even social science. Using artificial intelligence, the system now have the ability to interpret external data correctly to learn from the data and then use the learning to achieve certain goals through flexible adaptation. The artificial intelligence fields consists of several branches, such as machine learning and deep learning. Neural Network (NN) is one of the methods used in the deep learning.NN has many types, one of which is the Convolutional Neural Network (CNN). CNN is the best-knownmethod used for processingimages data compared to other types of NN. Therefore, in this study the identification of rice plants diseases was carriedout using CNN method. From this study,better results were obtained compared to other methods, obtaining 100% accuracy for training data and 86,67% for testing data. The model obtained by the CNN method can be used for detecting 3 different types of rice plants diseases, there are brown spots, leaf smuts, or bacterial leaf blight disease based on the physical images of rice plant leaves.

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