Pengabdian ini fokus pada memberikan berkesempatan kepada siswa/i untuk menjadi seorang UI/UX designer yang mampu merancang sebuah produk digital dalam menjawab setiap kebutuhan, baik sisi pengguna maupun pemilik/produsen. Software yang digunakan adalah Figma. Figma adalah editor grafik vektor dan alat pembuatan prototipe yang berbasis web, dengan fitur offline tambahan yang diaktifkan oleh aplikasi desktop untuk macOS dan Windows. Aplikasi pendamping Figma Mirror untuk Android dan iOS memungkinkan melihat prototipe Figma secara real-time di perangkat seluler. Para peserta pelatihan diharapkan mampu membuat user interface yang baik dan rapi menggunakan Figma dan mampu menggunakan Figma Plugins & GUI kits. Metode yang digunakan dalam pelatihan ini adalah metode pelatihan interaktif. Studi kasus pada pelatihan ini adalah pembuatan merancang Homepage/Sign in/Sign Up, dan Design shopping experience, checkout experience, profile, order history

Online lecture is a distance learning system that utilizes information technology in its implementation. Although it has been agreed, this lecture system has caused controversy. Not infrequently online lectures are considered to bring a variety of new obstacles in lectures, and not a few also consider that online lectures are the most appropriate solution to continue to run lecture activities in the midst of alarming pandemic conditions. In response to this policy, many people expressed various kinds of opinions and views on the implementation of online lectures which are generally stated on social media, one of which is through Twitter. Sentiment analysis is a branch of the science of machine learning that is carried out to obtain useful information or new knowledge by extracting, understanding, and processing text data automatically. Several methods are widely used by researchers to classify sentiment analysis datasets including K-Nearest Neighbor (K-NN). K-NN will be adapted to classify online lecture datasets because K-NN can produce good accuracy on a large number of data. The presence of feature selection also helps machine learning in improving its performance. The purpose of this study was to determine student sentiment toward online lectures and to determine the level of accuracy of the combination of K-NN with various feature selections. Based on 780 tweets data, a classification of 394 positive sentiments, 320 negative sentiments, and 39 neutral sentiments was obtained. So, the results of student opinions are on POSITIVE sentiments.  The accuracy result of the K-NN Algorithm was 56% and the accuracy of the K-NN Algorithm + Forward Selection was 51%, the accuracy of the KNN Algorithm + Adabost was 54%, and the accuracy of the KNN Algorithm + Genetic Algorithm was 55%.

Covid-19 is a disease of the virus that is shaking the world and has been designated by WHO as a pandemic. This case of Covid-19 can be a place of dissemination of disinformation that can be utilized by some parties. The dissemination of information in this day and age has turned to the internet, namely social media, Twitter is one of the social media that is often used by Indonesians and the data can be analyzed. This study uses the social network analysis method, conducted to be able to find nodes that affect the ongoing interaction in the interaction network of information dissemination related to Covid-19 in Indonesia and see if the node is directly proportional to the value of its popularity. As well as to know in identifying the source of Covid-19 information, whether dominated by competent Twitter accounts in their fields. The data examined 19,939 nodes and 12,304 edges were taken from data provided by the web academic.droneemprit.id on the project "Analisis Opini Persebaran Virus Corona di Media Sosial", using the period of December 2019 to December 2020 on social media Twitter. The results showed that the @do_ra_dong account is an influential actor with the highest degree centrality of 860 and the @detikcom account is the actor with the highest popularity value of follower rank of 0.994741605. Thus actors who have a high degree of centrality value do not necessarily have a high follower rank value anyway. The study ignores if there are buzzer accounts on Twitter.

A patient who is hospitalized generally gets health monitoring including 3 parameters including heart rate, body temperature and level of intravenous fluid usage. These three parameters are used as an indication of the patient’s significant health development. Body temperature is needed because in addition to being an indicator of a person’s health, it also has little to do with heart performance, namely the more the body temperature moves away from normal body conditions, then it affects how fast or slow the heart pumps blood. throughout the body. To solve this problem, the researchers intend to create a three-parameter monitoring system, namely heart rate, body temperature and intravenous drips for patients. This monitoring system is also designed to provide a sound warning indicator in case of abnormal conditions in the monitored parameters. From the test results, it can be concluded that the device can display indicators of patient health development with 3 parameters, namely heart rate, body temperature and the level of infusion usage.

Belum lama ini seorang hacker bersamarkan nama bjorka menjadi pembahasan hangat pada media sosial. Dikarenakan gerakannya meretas beraneka macam data pribadi pada kalangan masyarakat sekalipun dokumen pemerintah yang sering sebagai tujuan aksinya. Terlebih sebagian besar dokumen diduga kepemilikan Presiden Indonesia Joko Widodo telah dibongkar. Gerakan hacker bersamarkan nama Bjorka membongkar data pribadi kepemilikan pemerintah juga meraih dukungan dari sebagian besar warga netizen pada media sosial. Pada kasus ini penulis memakai metode Support Vector Machine guna menghasilkan tahapan optimal. Seiring meningkatnya penggunaan Twitter, media sosial yang berkomputasi dengan waktu nyata terhadap masyarakat mampu mengirimkan berbagai ungkapan maupun tanggapannya pada aksi yang dilakukan oleh bjorka, perlu dirancangnya sistem yang sanggup mengklasifikasi sejumlah cuitan berbobotkan opini mengarah pada suatu kelas, tergolong positif, negatif dan netral.