Sunspot is an area on photosphere layer which is dark-colored. Sunspot is very important to be researched because sunspot is affected by sunspot numbers, which present the level of solar activity. This research was conducted to make prediction on sunspot numbers using Gated Recurrent Unit (GRU) algorithm. The work principle of GRU is similar to Long short-term Memory (LSTM) method: the information from the previous memory is processed through two gates, that is update gate and reset gate, then the output generated will be input for the next process. The purpose of predicting sunspot numbers was to find out the information of sunspot numbers in the future, so that if there is a significant increase in sunspot numbers, it can inform other physical consequences that may be caused. The data used was the data of monthly sunspot numbers obtained from SILSO website. The data division and parameters used were based on the results of the trials resulted in the smallest MAPE value. The smallest MAPE value obtained from the prediction was 7.171% with 70% training data, 30% testing data, 150 hidden layer, 32 batch size, 100 learning rate drop.
Recently, education has been enlivened by the presence of the Merdeka Campus program initiated by Nadiem Makarim. It uses the Kampus Merdeka concept to learn to follow the development of education in the 4.0 era. This change has become a paradigm for Higher Education to build a Merdeka Campus to learn to face challenges in the 4.0 era. However, the challenge is not easy for universities, so that students join the independent program to learn quickly. This study aims to motivate students to participate in independent learning activities in a collaborative learning system with gamification techniques. Gamification is in the form of reward badges for student achievement in all learning activities carried out. The higher education independent learning system is designed using the library study method and Agile Development with two frameworks, namely Laravel and VueJS. It can be proven from the results of the SUS Score Analysis showing the number 92.5 indicating that the independent learning campus system provides positive benefits by gamification of students being more motivated and ready to face learning challenges in the 4.0 era.
Chicken is an animal that can provide many benefits for human life, meat and eggs can be used as food to fulfill the needs of human food, the excrement can be made fertilizer, and frequently its be used as a farm animal. Although it can provide many benefits, but for chicken farmers, the maintenance of chicken meet some obstacles that must be faced such as disease, poor environmental sanitation, and the production of eggs are declining. From some of the obstacles that have been mentioned, the most frequently encountered are animals infected with the disease. Based on the results of interviews that have been done to some chicken farmers, it can be said that the knowledge of chicken farmers against chicken disease and its handling is still very lacking. But the number of experts who understand and know about the type of chicken disease and the way of handling is limited, then it takes an expert system that can simulate knowledge and understanding of experts to overcome the problem. Based on the study of the libraries, the method suitable for use in the expert system is the Dempster shafer method by processing the value of belief in a disease. Dempster shafer method is a method used to calculate uncertainty due to the addition or reduction of new facts that will change the existing rules. Based on tests in 40 cases using an expert system applying the Dempster Shafer method, obtained the percentage of diagnostic compatibility result given by experts and system is 95%.
This study aims to optimize servers with low utility levels on hardware using container virtualization techniques from Docker. This study's primary focus is to maximize the work of the CPU, RAM, and Hard Drive. The application of virtualization techniques is to create many containers as each of the containers is for the application to run a cloud storage system with the CaaS service infrastructure concept (Container as a Service). Containers on infrastructure will interact with other containers using configuration commands at Docker to form an infrastructure service such as CaaS in general. Testing of hardware carried out by running five Nextcloud cloud storage applications and five MariaDB database applications running in Docker containers and tested by random testing using a multimedia dataset. Random testing with datasets includes uploading and downloading datasets simultaneously and CPU monitoring under load, RAM, and Disk hardware resources. The testing will be done using Docker stats, HTOP, and Cockpit monitoring tools to determine the hardware capabilities when processing multimedia datasets.
Hajj and Umrah are worship activities carried out by Muslims around the world. The problem that often occurs during the implementation of the Hajj and Umrah is that pilgrims are often lost and separated from the group. Pilgrims also find it difficult to look for prayers because they are still using guidebooks, they have to look for prayers one by one in the feeling of a busy and hot holy land. The case study was carried out at Dago Wisata Internasional. The solution used is utilizing geofencing technology and Firebase Cloud Messaging that allows the process of monitoring pilgrims to be carried out easily and the pilgrims can get prayer notifications in accordance with the location of pilgrims. Research supporting data obtained from interviews with employees of Dago Wisata Internasional and literature studies. Based on testing on the application that has been built, the following results are obtained 93.33% supervisor states that this application simplifies the process of monitoring pilgrims, 84% worshipers claim to be able to ask for help easily from the supervisor using this application, and 86% worshipers claim this application makes it easy for pilgrims in looking for the practice deeds.
