<p class="Text"><strong>Sesuai Peraturan Presiden no 39 tahun 2019 tentang Satu Data, untuk memperoleh Data yang akurat, mutakhir, terpadu,, mudah diakses, dan dibagipakaikan, diperlukan perbaikan tata kelola Data yang dihasilkan oleh pemerintah. Studi kasus penelitian ini di Pemerintah Kabupaten Trenggalek Jawa Timur di 35 Organisasi Perangkat Daerah (OPD) dengan metode kuisioner dan wawancara untuk penggalian permasalahan data. Perumusan pengolahan data menggunakan pedoman Data Management Body Of Knowledge (DMBOK. Data Management Body Of Knowledge (DMBOK) merupakan salah satu framework tata kelola data yang memberikan pendekatan model tata kelola data secara fungsional, lengkap dan menyeluruh dalam membangun tata kelola data di organisasi. Penelitian ini merumuskan struktur tatakelola data, peran tata kelola data dalam struktur organisasi pemerintahan Kabupaten Trenggalek, peran aktivitas tata kelola data dan pemetaan solusi 18 masalah data di Pemerintah Kabupaten Trenggalek berdasarkan pedoman DMBOK. Hasil dari penelitian ini menunjukkan bahwa tata kelola data dengan pedoman DMBOK dapat digunakan sebagai solusi untuk masalah data yang terjadi. Struktur tata kelola data yang telah dirancang diharapkan dapat membantu Kabupaten Trenggalek dalam mengimplementasikan tata kelola data di pemerintah daerah secara efektif</strong></p><div style="mso-element: comment-list;"><div style="mso-element: comment;"><div id="_com_2" class="msocomtxt"><!--[if !supportAnnotations]--></div><!--[endif]--></div></div>
The Covid-19 pandemic that has hit the world, including Indonesia, has forced the government to take policies to prevent the spread of this deadly virus. One of the efforts is socialization to gain people's awareness to keep their distance and stay home. One of the media that can be used for this purpose is Twitter. However, even socialization efforts have been carried out, the spread of Covid-19 cases still has not yet decreased. Many aspects have to be evaluated to fix the situation. One of them is to evaluate the level of community compliance compared to the spread of Covid-19. This study aims to determine the level of community compliance to stay at home and its correlation with the number of positive cases of Covid-19 in Indonesia. This study takes the data from the tweets of the Indonesian people. The algorithms used are logistic regression and random forest combined with the ensemble algorithm, namely bagging. Twitter data taken are those that contain the word covid19, tetapdirumah, stayathome, mudik, psbb; location in Indonesia within a period of March 3 rd to July 7 th 2020. The data obtained from 705 tweets shows that noncompliance community has increased starting mid-June 2020 which is in line with the increasing data trend on the Covid-19 cases in Indonesia.
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