Purpose: This community service aimed to provide counseling on utilizing technological advances at the Bikul Bali White Rat Farm Business for marketing purposes. Method: Thee methods applied were accompaniment counseling on technological advances, lectures, and direct practice by applying digital marketing to reach and get new consumers. Result: The Partner understands the importance of implementing digital marketing and is confident in promoting their white rats through the marketplace even though there are extra costs for promotion. Conclusion: This community service activity has a positive impact as an additional knowledge of partners in understanding digital marketing. The partner now takes advantage of the availability of the marketplace as a medium for selling as a form of application of digital marketing and starting to reach new potential consumers who are accustomed to using marketplaces in shopping.
The absorpstion of CO2 is aimed to increase the methane gas fraction in biogas. Enhancing methane fraction hopefully will increase the total energy of the biogas it self. The purification process of biogas minimizing another elements maintains combustion, especially minimizing H2O, CO2, and H2S. The purification using KOH as the absorbent to decrease the CO2. The result shown that the content of CO2 decreased into 27% from 35.5%, the average content of CH4 increased from 18% to 48.5%. Increasing KOH composition decreases bubble generator diameter and mass flow.
Aktivitas pariwisata di Indonesia mulai membaik, dimana hal ini tercermin pada kinerja sektor pariwisata yang menunjukkan peningkatan. Salah satu faktor pendorongnya ialah adanya pergeseran preferensi masyarakat dalam memanfaatkan teknologi digital. Pengelola sektor wisata perlu beradaptasi dengan situasi tersebut, yakni dengan menggunakan strategi promosi secara <em>online. </em>Salah satu bentuk promosi <em>online</em> yang dimaksud ialah penggunaan <em>electronic word of mouth (e-Wom). </em>Promosi <em>e-Wom </em>diharapkan dapat meningkatkan keputusan wisatawan untuk berkunjung. Berdasarkan ulasan tersebut, maka penelitian ini bertujuan untuk mendeskripsikan strategi-strategi optimalisasi <em>electronic word of mouth (e-Wom) </em>sebagai media promosi destinasi wisata di Indonesia. Penelitian ini merupakan penelitian deskriptif kualitatif dengan teknik pengumpulan data melalui studi literatur yang dianalisis dengan analisis konten/ isi. Hasil penelitian menyimpulkan bahwa terdapat 6 (enam) strategi optimalisasi <em>e-Wom </em>sebagai media promosi destinasi wisata, yaitu: 1) <em>Creating Opinion Strategy; 2) Using Digital Media Strategy; 3) Creating Content Strategy</em>; 4) <em>Opinion Filter Strategy; 5) Tourist Cruise Strategy; 6) Concern to Tourist Experience Strategy.</em>
Data shared between hospitals and patients using mobile and wearable Internet of Medical Things (IoMT) devices raises privacy concerns due to the methods used in training. the development of the Internet of Medical Things (IoMT) and related technologies and the most current advances in these areas The Internet of Medical Things and other recent technological advancements have transformed the traditional healthcare system into a smart one. improvement in computing power and the spread of information have transformed the healthcare system into a high-tech, data-driven operation. On the other hand, mobile and wearable IoMT devices present privacy concerns regarding the data transmitted between hospitals and end users because of the way in which artificial intelligence is trained (AI-centralized). In terms of machine learning (AI-centralized). Devices connected to the IoMT network transmit highly confidential information that could be intercepted by adversaries. Due to the portability of electronic health record data for clinical research made possible by medical cyber-physical systems, the rate at which new scientific discoveries can be made has increased. While AI helps improve medical informatics, the current methods of centralised data training and insecure data storage management risk exposing private medical information to unapproved foreign organisations. New avenues for protecting users' privacy in IoMT without requiring access to their data have been opened by the federated learning (FL) distributive AI paradigm. FL safeguards user privacy by concealing all but gradients during training. DeepFed is a novel Federated Deep Learning approach presented in this research for the purpose of detecting cyber threats to intelligent healthcare CPSs.
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