In 2020, online learning rapidly grows due to the pandemic of COVID-19 that affected the changes in global conditions. All learners and educators have to be ready for online learning. This research was aimed to explore the implementation of the flipped classroom during the Covid-19 pandemic outbreak in 2020. This research setting was at Universitas Negeri Jakarta, one of the campuses that eliminated campus activities due to the high Covid-19 spread in Jakarta. Referring to the learning standards of AECT, the researchers used qualitative descriptive methods. The techniques of collecting data were observation, interviews, and questionnaires to all students who took E-Learning Design courses at the Master of Educational Technology, Postgraduate Program, Universitas Negeri Jakarta. The research results proved that learning during the Covid-19 pandemic using flipped classrooms in the E-Learning Design course has met ten online learning standards by AECT and provides satisfaction for students and lecturers. In addition, according to research results, the use of technology does not need to be grandiose. Accordingly, it should optimize the platform often used on daily basis to utilize the flipped classroom.
Supervisors are parties who are expected to provide professional development for teachers in teaching and learning activities and provide the latest information related to educational policies, provide alternative solutions when schools have difficulty improving quality or running educational programs. However, limited attention is paid to primary school supervision issues during the current COVID-19 pandemic. This article discusses the implementation of primary school supervision in Bontang City during the COVID-19 pandemic. A qualitative approach with a descriptive method is used to describe the conditions that occurred at the time the research was conducted and then examine the causes of the conditions under study. Then, the researcher also explained how the supervisory plan for monitoring, implementing and evaluating Bontang City elementary schools during the Covid-19 pandemic. The results showed that school supervision during the pandemic was not carried out properly. The implementation of supervision does not follow the supervisor's technical instructions during the COVID-19 pandemic. As a result, the supervision process does not provide real implications for the implementation of effective learning.
Simpang lima patung pramuka (Ex Tugu Blue Band) Kota Parepare sebagai titik temu dari beberapa ruas jalan yang merupakan titik kritis pada jaringan jalan. Penelitian dilakukan di simpang lima jalan Jendral Ahmad Yani Kota Parepare yang merupakan simpang lima tak bersinyal yang setiap harinya dilalui berbagai jenis kendaraan meliputi : sepeda motor, mobil, truck dan sebagainya. Kinerja simpang yang ditinjau pada penelitian ini : " berupa besar arus lalu lintasyang melintasi simpang dan bagaimana kinerja simpang tak bersinyal pada kondisi existing. Penelitian ini dilakukan menggunakan metode MKJI (Manual Kapasitas Jalan Indonesia), waktu penelitian dilaksanakan selama 7 hari, dengan priode pagi pada jam 07.00 -08. 00 wita, priode siang 12.00 -13.00 wita dan priode sore hari 16.00 -17.00 wita. Dengan mendata volume kendaraan yang melewati persimpangan, yakni kendaraan berat, kendaraan ringan, sepeda motor. Dari data yang di dapat, Arus Lalu Lintas priode pagi (0,219), priode siang (0,343), priode sore (0,160)sedangkan untuk Kapasitas Simpang priode pagi ( 1052), priode siang (946), priode sore (1095) untuk Derajat Kejenuhan priode pagi (0,642), priode siang (0,864), priode sore (0,666) , serta Tundaan Simpang priode pagi (5,515), priode siang (2,091) dan priode sore ( 2,745
Pasar tradisional Lakessi Kota Parepare memiliki intensitas kunjungan yang sangat besar karena sebagai penyangga 2 Kabupaten yakni Kabupaten Pinrang dan Kabupaten Barru. Tarikan itu sendiri dipengaruhi banyak variabel. Untuk itu, penelitian ini dilakukan guna membuat model dari tarikan pergerakan tata guna lahan dan tarikan pergerakan berbasis pada rumah pasar Lakessi Kota Parepare. Pemodelan dilakukan dengan menggunakan analisis regresi linear berganda. Pengumpulan data untuk tarikan pergerakan tata guna lahan akan diperoleh dengan teknik survei kendaraan dan pengumpulan data untuk tarikan pergerakan berbasis rumah akan menggunakan teknik kuisioner. Hasil analisis regresi linear pada penelitian ini adalah Y1 = 2,379X1b + 21,079X1c -11,649 dan Y2 = 1,407X2b + 0,601X2d + 0,495X2n -2,200, dengan Y1 adalah tarikan pergerakan kendaraan dalam satuan mobil penumpang, Y2 adalah intensitas kunjungan ke Pasar, X1b adalah jumlah pedagang sayur dan buah, X1c adalah jumlah pedagang daging dan ikan, X2b adalah jenis kelamin pengunjung, X2d adalah penghasilan perbulan, dan X2n adalah kelengkapan barang di pasar. Kata Kunci : Tata guna lahan, Tarikan pergerakan berbasis rumah, analisis regresi linear; pasar tradisional ABSTRACT The Lakessi traditional market in Parepare City has a very large intensity of visits because it serves as a buffer for two regencies, namely Pinrang Regency and Barru Regency. Many variables influence the attraction itself. For this reason, this research was conducted to create a model of the Attraction of land use movement and theAttraction of movement based on the Lakessi market house in Parepare city. Modeling is done using multiple linear regression analysis. Data collection for land-use movement attraction will be obtained by means of a vehicle survey, and data collection for house-based movement attraction will be obtained using a questionnaire technique. The results of linear regression analysis in this study are Y1 = 2.379X1b + 21.079X1c -11.649 and Y2 = 1.407X2b + 0.601X2d + 0.495X2n -2.200, where Y1 is the drag of the vehicle movement in passenger car units, Y2 is the intensity of visits to the market, X1b is the number of vegetable and fruit traders, X1c is the number of meat and fish traders, X2b is the gender of visitors, X2d is monthly income, and X2n is the completeness of goods in the market.
Twitter is a social media application that is widely used. Where as many as 18.45 million users in Indonesia, Twitter users can send and read messages with a maximum of 280 characters displayed. Many opinions and reviews uploaded by users via tweets on social media are experienced in everyday life. Lately, comments about internet service providers in the covid-19 pandemic have been widely reviewed by Twitter users. Problems about internet providers through words often uploaded include internet provider complaints related to network quality, package prices, user satisfaction, and others. This study aims to classify Twitter users' tweets against internet service providers in Indonesia by analyzing the sentiments of 3 internet service providers, namely with the keywords Biznet, first media, and Indihome, using the Naïve Bayes algorithm and optimization with Particle Swarm Optimization. This research is also helpful in helping to become a measure where prospective new users will see the quality of an internet service provider in Indonesia through tweets and then divide the opinion into positive and negative. The results of Biznet's research using Naïve Bayes produce an accuracy of 77.94%, and after optimization, it becomes 81.62%. First media using Naïve Bayes produces 91.39% accuracy, and after optimization, it becomes 92.88%. Indihome using Naïve Bayes produces an accuracy of 85.78%, and after optimization, it becomes 87.48%. It can be concluded that the Naïve Bayes algorithm is a good algorithm for classification, and optimization using Particle Swarm Optimization has an effect on increasing accuracy results
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