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Online news is a media for people to get new information. There are a lot of online news media out there and a many people will only read news that is interesting for them. This kind of news tends to be popular and will bring profit to the media owner. That's why, it is necessary to predict whether a news is popular or not by using the prediction methods. Machine learning is one of the popular prediction methods we can use. In order to make a higher accuracy of prediction, the best hyper parameter of machine learning methods need to be determined. Determining the hyper parameter can be time consuming if we use grid search method because grid search is a method which tries all possible combination of hyper parameter. This is a problem because we need a quicker time to make a prediction of online news popularity. Hence, genetic algorithm is proposed as the alternative solution because genetic algorithm can get optimal hypermeter with reasonable time. The result of implementation shows that genetic algorithm can get the hyper parameter with almost the same result with grid search with faster computational time. The reduction in computational time is as follows: Support Vector Machine is 425.06%, Random forest is 17%, Adaptive Boosting is 651.06%, and lastly K -Nearest Neighbour is 396.72%.

<p class="Abstrak">Antrian konvensional sudah menjadi polemik yang umum di masyarakat. Lamanya proses dan waktu tunggu antrian sangat mengganggu aktivitas sehari-hari. Pada instansi kesehatan seperti rumah sakit dan poliklinik, dimana pasien juga diharuskan mengantri, dapat berpengaruh pada kondisi pasien. Sistem pendaftaran online yang ada hanya menyediakan pengambilan nomor antrian, namun untuk proses menunggu antrian masih harus datang ke lokasi. Sistem yang ditawarkan memiliki kelebihan pada pilihan variasi jadwal poliklinik, dan pemberian informasi antrian yang sedang berjalan. Pada penelitian ini membahas tentang perancangan dan pengembangan sistem antrian poliklinik yang berbasis pada <em>mobile phone</em>, sehingga pengguna dapat mengakses sistem kapanpun dan dimanapun. Perancangan menggunakna metode MVC untuk memisahkan antara data dan tampilan serta cara pemrosesannya. Pengembangan aplikasi menggunakan <em>hybrid mobile web framework</em> yang dapat digunakan untuk pengembangan <em>multiplatform</em>. Pengujian sitem menggunakan <em>White Box</em>, <em>Black Box</em>, dan <em>Usability Testing</em> telah menunjukkan bahwa struktur dan hasil desain sistem dapat diimplementasikan dengan baik, sehingga sistem dapat berjalan sesuai kebutuhan.</p><p class="Abstrak"> </p><p class="Abstrak"><em><strong> Abstract</strong></em></p><p class="Abstract">The conventional queue has become a common polemic in society. The length of processes and waiting time of the queue is very disturbing on daily activities. In health agencies such as hospitals and polyclinics, where patients are also required to queue up, may affect the patient's condition. Existing online registration system only provides queue number retrieval, but for the waiting process, the queue still has to come to the location. The offered system has advantages over the choice of polyclinic schedule variations, and the provision of queue information is running. This research discusses the design and development of a polyclinic queuing system based on a mobile phone so that users can access the system anytime and anywhere. The design uses the MVC method to separate data and display and how to process it. Application development using hybrid mobile web framework that can be used for multiplatform development. System validation method is using White Box, Black Box, and Usability Testing has shown that the structure and results of system design can be implemented well, so the system can run as needed.<strong></strong></p><p class="Judul2"> </p>

<span lang="EN-US">Student’s performance is the most important value of the educational institutes for their competitiveness. In order to improve the value, they need to predict student’s performance, so they can give special treatment to the student that predicted as low performer. In this paper, we propose 3 boosting algorithms (C5.0, adaBoost.M1, and adaBoost.SAMME) to build the classifier for predicting student’s performance. This research used ¹UCI student performance datasets. There are 3 scenarios of evaluation, the first scenario was employ 10-fold cross-validation to compare performance of boosting algorithms. The result of first scenario showed that adaBoost.SAMME and adaBoost.M1 outperform baseline method in binary classification. The second scenario was used to evaluate boosting algorithms under different number of training data. On the second scenario, adaBoost.M1 was outperformed another boosting algorithms and baseline method on the binary classification. As third scenario, we build models from one subject dataset and test using onother subject dataset. The third scenario results indicate that it can build prediction model using one subject to predict another subject.</span>

<p class="0abstract">The lack of recognition of the current Banjar language is one of the causes of knowledge and the introduction of children about the reduced Banjar language. In an attempt to recognize, introduce, and improve the re-knowledge of the Banjar language is to recommend the design and implementation of an educational game application called Bekantan Educational Game (BEG) containing material content and quizzes. Before this game application is used, it must be tested first. Test method used is black box testing, to test the functionality of game applications. Other tests are also conducted to obtain information about the material access frequency and reset quizzes by players. The result of black box testing is all the functionality in the BEG application in accordance with what is expected. The result of the frequency testing accessing the menu on BEG of Material Section is Wadai Banjar 2 Menu with 59 times, and the frequency reset on BEG of Quiz Section is a type of Drag and Drop quiz with 21 times and generate feedback from quiz in the form of final value with average 89.17%.</p>

No abstract

Problem High school teenagers are facing significant challenges during the COVID‐19 pandemic. Teenagers are at risk of experiencing physical, mental, and social health problems due to the COVID‐19 pandemic. This narrative review aims to explore the impact of COVID‐19 on the emergence of mental health problems in high school adolescents. Methods This study employed a narrative review method. We conducted a systematic search using PRISMA on three databases: Medline, PubMed, and ScienceDirect. A total of 40 articles met the inclusion and exclusion criteria set based on the research objectives. Findings The study uncovered that high school adolescents had an increased risk of experiencing mental health problems, namely psychological distress, worry, loneliness, anxiety, depression, traumatic symptoms, other psychological disorders, suicide risk, sleep disorders, and psychosocial functioning. Anxiety, depression, and psychological stress were the most discussed mental health problems among high school adolescents during the COVID‐19 pandemic. Conclusions There is a need for efforts to identify health problems and intervene in mental health problems early in high school adolescents. Schools, mental health workers, and the government (e.g., policy stakeholders) need to implement the recommendations given as a follow‐up effort for mental health services for high school youth.

The advancement of computer and communication technologies has enabled researchers to conduct and analyze the learning process of posing problems. This study investigates what learners think while posing problems as sentence integration in terms of intermediate products as well as the posed problems as the resultant product. Problem posing as sentence integration defines the arithmetic word problem structure, and posing a problem is a task to satisfy all the constraints and requirements to build a valid structure. A previous study shows that, in problem posing as sentence integration for arithmetic word problems, learners try to satisfy a relatively large number of constraints in the posed problems. In contrast, this study focuses on the violation of constraints in the intermediate products while posing problems. The result shows that learners were inclined to avoid as many violated constraints as possible throughout the problem-posing process. Although learners tend to avoid the violated constraints, naturally, they cannot avoid some mistakes. Further analysis shows that learners actually have difficulty in fulfilling particular constraints while posing the problems. Based on this analysis, it is possible to detect the difficulty of learners' actions from the model perspective. Hence, it is possible to give accurate feedback and appropriately support the learners.