Purpose of the study: The strategic and learning media course in the Informatics Engineering Education department for pre-service student teachers apply a blended learning method. The purpose of this method is to integrate between face-to-face meetings in the classroom and distance learning by using internet-based Learning Management System (LMS) media. This study aims to determine the perceptions of the informatics’ pre-service student teacher, which utilize the Google Classroom LMS. Methodology: The research method used online questionnaires and divergent questionnaires were analyzed with the Technology Acceptance Model (TAM) approach and descriptive statistics. The factor analysis included the ease of access, perception of usefulness, communication and interaction, a perception of lecture delivery, student comfortability, and the effectiveness of the Google Classroom LMS. Main Findings: The results showed that most students felt the ease and improvement of the quality of the blended lectures using Google Classroom, although several notes needed further improvement and evaluation. Practical Implications: The findings suggest that the stakeholders of teacher training and education faculty could measure the level of perceivers and readiness of their pre-service student teachers on using Google Classroom in a blended-setting course. Further, the pre-service student teachers have experience in using this LMS so that they could apply this learning model for their students. Novelty/Originality of this study: This article found that students feel the satisfaction of using Google Classroom as an active and independent learning tool. This study also demonstrated consistency based on observations, surveys, and analysis of college students’ perceptions that the design of blended learning by using Google Classroom is still beneficial to the success of reaching the course outcomes.

There have been many efforts to improve elementary school students’ critical thinking skills in science through various learning methods. However, only a few research results show efforts to improve critical thinking skills through HOTS-based science questions for elementary school students. Therefore, the purpose of this study is to test the effectiveness of student habituation with HOTS-based science questions in improving elementary school students’ critical thinking skills in science. Quasi-experimental methods were employed in this research with a nonequivalent control group design involving a treatment class and a control class. The treatment class gets treatment in HOTS-based science questions habituation during the learning process, while the control class in conventional approaches. A total of 60 students is from one of the elementary schools in Surakarta, Indonesia. To take data related to students’ critical thinking skills, they were given pretest and posttest where each test used HOTS-based science questions in an essay. The obtained data from the tests were then analyzed using descriptive and inferential statistical techniques. This study showed that the average of critical thinking skills in science of students in the experimental class was higher than the control class, with a positive mean difference of 0.4226. Based on these results, it is recommended that the results of this study can provide an overview to educational practitioners at the elementary school level and researchers in the field of science education related to efforts to improve elementary school students’ critical thinking skills in science through the habituation of HOTS-based science questions.

BMT Artha Mandiri is a cooperative that provides savings and loans services. In providing credit, BMT Artha Mandiri still uses the manual method, namely by looking at the ledger and history of each customer, to find out whether the applicant is worthy or not worthy of credit so that it is not effective and efficient. The purpose of this research is to make an application that can predict whether a prospective customer is eligible or not to be given credit. Predictions are made using the data mining classification method, namely the C4.5 algorithm based on the supporting data each customer has to classify which factors have the most influence on the level of credit payments in the cooperative. In a built application, the C4.5 algorithm produces a decision tree that is easy to interpret based on the existing variables. In the application, there are features that can be used to make decisions about customers who will apply for credit at the cooperative. The blackbox test results on the application show that the application has been able to run as expected, while the results of the algorithm test also show that the application has been able to implement the C4.5 algorithm correctly. In addition, the results of testing for accuracy show that the maximum average value of Accuracy is 79.19%.

One of the methods used in detecting the intrusion detection system is by implementing Naïve Bayes algorithm. However, Naïve Bayes has a problem when one of the probabilities is 0, it will cause inaccurate prediction, or even no prediction was found. This paper proposed two modifications for Naïve Bayes algorithm. The first modification eliminated the variable that has 0 probability and the second modification changed the multiplication operations to addition operations. This modification is only applied when the Naïve Bayes algorithm does not find any prediction results caused by zero probabilities. The results of this research show that the value of precision, recall, and accuracy in the modification made tends to increase and better than the original Naïve Bayes algorithm. The highest precision, recall, and accuracy are obtained from modification by changing the multiplication operation to the addition. Increasing precision can reach 4%, increasing recall reaches 2% and increasing accuracy reaches 2%.