The government to provide the excellent public service performance must supported by existing resources. Human factors or man power are an important part of an organization, where talented, qualified human resources are needed, willing to cooperate with teams and have high spirit. Work spirit is needed in every employee cooperation effort to achieve organizational goals, because with the work spirit will result in high performance for the organization. Besides that, employee performance is also determined by the work environment both physical and non-physical. This study aims to analyze the influence of the work environment and work spirit on the performance of employees at the Tabanan District Health Office. Research uses Path Analysis as a method of data analysis, where data collection is done by observation, interviews, literature studies, and questionnaires. As the initial stage of the analysis, a validity and reliability test will be carried out on the research instrument. The results showed that the work environment and work spirit had a positive and significant effect on employee performance at the Tabanan District Health Office. Where the work spirit variable acts as an mediation variable in the influence of the work environment on employee performance at the Tabanan District Health Office.
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.
[Bahasa]: Pemerintah Kecamatan Petang telah menerapkan teknologi informasi dalam pengelolaan data desa yang dapat diakses melalui website https://petang.badungkab.go.id. Meskipun penerapan teknologi informasi telah dilakukan, pengelolaan data desa masih belum optimal. Kendala yang dihadapi adalah terbatasnya pengetahuan perangkat kecamatan dalam pengelolaan website yang dimiliki. Permasalahan lain yang dihadapi oleh pemerintah Kecamatan Petang adalah kesulitan dalam mendapatkan data valid dan up to date yang bersumber dari desa di Kecamatan Petang. Tujuan pengabdian kepada masyarakat ini adalah untuk membantu pemerintah Kecamatan Petang dalam mengotomatisasi pengelolaan data yang bersumber dari desa. Metode yang digunakan dalam kegiatan ini adalah Participatory Action Research (PAR) dengan dua pendekatan yaitu penyelesaian masalah dan peran serta. Dengan metode ini, Tim Pengabdian memberikan penyelesaian masalah yang dihadapi pemerintah Kecamatan Petang melalui (1) instalasi dan konfigurasi website kecamatan dengan OpenDK, (2) pelatihan pengelolaan website kecamatan dengan OpenDK, dan (3) integrasi data desa ke OpenDK. Pemerintah kecamatan Petang sebagai mitra dalam kegiatan ini ikut berperan serta aktif dalam seluruh program. Hasil yang diperoleh pada kegiatan ini adalah (1) pemerintah Kecamatan Petang memiliki OpenDK sebagai sistem pengelolaan data desa, (2) rata-rata sebanyak 78.57% peserta memahami pengelolaan website kecamatan dengan OpenDK, dan (3) pemerintah Kecamatan Petang telah memahami bagaimana mengoperasikan OpenDK untuk menampilkan dashboard hasil integrasi data desa dan OpenDK. Kata Kunci: data desa, Kecamatan Petang, OpenDK, website [English]: Petang sub-district has been implementing information technology in managing village data which can be accessed through the website https://petang.badungkab.go.id. Despite the fact, the data management is yet optimal. The obstacle faced is limited knowledge of the sub-district apparatus to manage the website. Another problem is the difficulty in obtaining valid and up-to-date data sourced from villages. The purpose of this community service program is to assist the Petang sub-district officers in automating the management of data. The method used in this program was Participatory Action Research (PAR) through two approaches, namely problem-solving and participation. In this method, the program team provides solutions to problems faced by Petang sub-district, including (1) installation and configuration of the website using OpenDK, (2) a website management training using OpenDK, and (3) integration of village data into OpenDK. Petang sub-district as a partner participated actively in all programs. The results obtained in this program are (1) the sub-district has OpenDK as a village data management system, (2) 78.57% of the participants understand the management of the sub-district website using OpenDK, and (3) the apparatus of Petang sub-district has understood how to operate OpenDK to display a dashboard of the integration of village data and OpenDK. Keywords: village data, Petang District, OpenDK, website
Status gizi balita mencerminkan tingkat perkembangan dan kesejahteraan masyarakat dalam suatu negara serta berhubungan dengan status kesehatan anak di masa depan. Pencatatan status gizi biasanya dilakukan setiap bulan oleh petugas dengan mencatat status gizi secara langsung dengan metode antropometri yakni mencatat berat badan dan umur balita pada KMS (Kartu Menuju Sehat). Pada penelitian ini untuk menentukan status gizi balita menggunakan data langsung yakni dengan data antropometri yang terdiri dari data umur, berat badan dan jenis kelamin, sedangkan untuk data tidak langsungnya menggunakan kuesioner dengan 30 respoden yang kemudian akan mendapatkan hasil status Gizi balita. Hasil dari penelitian ini dengan pengolahan data langsung dan data tidak langsung menunjukkan 3 buah cluster dimana gizi buruk 16.67%, gizi normal 43.33 % dan gizi lebih 40%. Sehingga masih terdapat nilai yang cukup tinggi pada gizi lebih.
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