Current Use of technology is very rapid, especially in the field of education. The process of using technology so fast can make it easier to process the data. Students 'grades are very complex in the form of students' 'leger' grade data and academic data. Stacking of student data repeatedly has an impact on the search for that data information. By using data mining process This research aims to classify the data of students of Hisba Buana Senior High School vocational class of 2017. The mining process is done through: business understanding, data understanding, data processing, modeling, evaluation and development. Using the Naive Bayes Algorithm is expected to calculate the probability of predicting passing, variable data that are not interrelated to whether or not other features are in the same data. Implement Rapit Miner to help manage accurate and accurate predictions. This study uses the attributes of subjects tested on the graduation exam from the beginning to the last semester. The result of this research with the accuracy level of 83.06% resulted in graduation group with value 0,506 and group did not pass with value 0,494. Decisionmaking is obtained from the Data and used as a basis for determining school policy.

The study conducted at the National Potential Young Athletes Training Center (SLOMPN) of Unesa provides a crucial perspective on the use of an Android-based match statistics application. The research aims to optimize athletes' potential through the Long Term Athlete Development (LTAD) approach, integrating knowledge of athlete development with the application of technology in training. The survey results from 5 coaches indicate that the application aids in planning training, understanding application features, and assessing athlete development with positively skewed average scores. However, there is room for improvement, especially in terms of comfort during matches and communication with athletes. Meanwhile, 18 athletes showed positive acceptance of the application by rating its ease of use and impact on performance enhancement highly. Nevertheless, there is a need for improvement in injury recovery features and data security. This study underscores the importance of continuous collaboration between application developers and users to enhance the effectiveness of technology in sports training.

The catfish (Pangasius sp.) is a popular freshwater fish among consumers, both in Indonesia and internationally. One of the main challenges in catfish farming is the suboptimal use of feed. The commonly used feed consists of natural and artificial types. Natural feed is divided into two categories: animal-based and plant-based. The animal-based natural feed frequently used by farmers is tubifex worms. However, tubifex worms have a drawback, as their availability in the market is limited. Therefore, a study was conducted to explore the use of Azolla as an alternative feed for catfish. This study used a Completely Randomized Design (CRD) with one treatment and two levels, namely 100% Azolla and 100% tubifex worms. The study was conducted over a period of 14 days. The observed parameters included fish growth (length and weight), survival rate (SR), Feed Conversion Ratio (FCR), and water quality (temperature, pH, and dissolved oxygen). The data from the study were analyzed using a mean value test. The results showed that the use of Azolla as feed had a positive impact on catfish growth, although it was not yet effective in fully replacing 100% tubifex worms. There was an increase in biomass of 13.8 grams and an average length increase of 0.56 cm during the 14-day maintenance period.