The term is a form of words or a combination of words used to express a concept to get a certain meaning. This study aims to describe the characteristic patterns of various language terms during the Covid pandemic 19. This research uses a qualitative descriptive approach where the results of the analysis are described in words but not in numerical form. The subjects in this study used new terms that existed during the Covid pandemic 19. While the object in this study was a characteristic pattern focused on the variety of Covid term languages 19. The technique used was observation and data collection techniques. The results showed that there were 38 data patterns of language characteristics of Covid 19 terms analyzed and then classified into 14 data in English form, 9 data in synonym form, 10 data in abbreviated form and 5 data in acronym form.

Bunga mawar merupakan tanaman dari genus Rosa yang memilik lebih dari 100 spesies dengan berbagai warna. Pada proses pemilihan bunga mawar akan ditemukan bunga mawar yang masih segar dan layu. Dengan itu kita dapat mendeteksi kelayuan bunga mawar dengan menerapkan metode HSI dan HSV pada aplikasi pengolahan citra, proses pengambilan data yaitu dengan melakukan preparasi data pada dataset kaggle yang kemudian dilakukan klasifikasi dan training data dengan menggunakan metode HSI dan HSV. Berdasarkan hasil klasifikasi dari total 820 gambar citra bunga mawar dilakukan pengujian sebanyak 757 gambar dengan menggunakan HSI dan HSV didapat nilai Range pada HSI, H=0-0.5, S=0-1, dan I=0.5372549-1 dengan kategori Segar, sedangkan kategori Layu HSI, H=0-0.5, S=0-1, I=0.5620915-1. Adapun nilai range HSV dengan kategori Segar H=0-0.5, S=0-1, V=0-1, dan kategori Layu H=0-0.5, S=0-1, V=0-1. Selanjutnya tingkat keberhasilan untuk pengujian bunga mawar dengan HSI mencapai 92.3% dimana data yang terbaca benar 757 dan terbaca salah 63 dari 820 data sampel bunga mawar, sedangkan pengujian pada HSV tingkat keberhasilan mencapai 93.2% dimana data yang terbaca benar 765 dan terbaca salah 55 dari 820 data sampel bunga mawar. Berdasarkan hasil diatas deteksi kelayuan bunga mawar dengan metode transformasi ruang warna HSV merupakan yang terbaik pada pengujian data. Kata Kunci : deteksi kelayuan; pengolahn citra; HSI; HSV; klasifikasi.

Based on information on the <span>BNPB website on 2 September 2020, the positive rate for coronavirus disease (COVID-19) in Indonesia reached 25.25% on 30 August 2020. This is a big challenge for the Indonesian government to reduce the positivity rate to meet the standards safe accepted by World Health Organization (WHO) is 5%. To ensure the accuracy of government policies, accurate data predictions are needed. Therefore, the prophet's machine learning algorithm can be used to see trends in the spread of COVID-19 in the next one year. This algorithm has a fairly high level of accuracy because the data contains time variables which are adjusted to the dataset. In several previous research, the dataset was vast uncertain and small. Meanwhile in this research, data was taken from 2 March 2020 to 12 February 2021 on the KawalCOVID19 website. This data is used to predict from 13 February 2021 to 12 February 2022. There are 3 data used; namely data confirmed, recovered and died. Based on the analysis, the confirmed patient was 22.60-42.11%, died amounted to 21.67%-39.00%, and recovered by 22.53-41.82%. The prediction percentage that the average cases died was 2.43% every day. The accuracy of data confirmed was 43.97%, died was 72.50% and recovered was 84.24%.</span>

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The coronavirus outbreak from 2019 had a significant impact on all sectors in Indonesia, especially the education sector, which requires learning from home. It provides a change in students' learning style to make educators change online-based learning using various platforms, one of which is the Physics Virtual Lab (PVL). This application is in a simulation designed explicitly physics practicum, accessed using a mobile phone. This study aims to determine how effective the use of PVL in fulfilling practicum activities is in terms of perceptions and competencies of students' attitudes. The research method is descriptive research to obtain an overview of PVL applications in physics practicum using domestic used materials. The subjects in this study were students of the first-semester science education study program who took the Basic Physics course-collecting data using perception questionnaires and attitude assessment sheets. The average student perception score is 4.22. Then, the students' attitude competence results obtained an average score of 80.88 integrity; independence 74.89; confidence 75.17 and responsibility 84.89. It shows that the implementation of PVL builds students' integrity and responsibility.