Judul: Content Analysis of Covid-19 Hoax News on Facebook Social Media
Abstrak: Penyebaran Covid-19 di Indonesia diiringi dengan menyebarnya berita hoaks terkait virus tersebut. Tujuan penelitian ini adalah untuk mengidentifikasi bentuk pesan, karakteristik konten, dan klasifikasi konten berita hoaks Covid-19 pada media sosial Facebook. Metode penelitian yang digunakan yaitu analisis isi yang menggunakan data primer dengan teknik pengambilan sampel purposive sampling sebanyak 100 unggahan di Facebook yang dinyatakan hoaks oleh Hoax Buster pada situs https://covid19.go.id/p/hoax-buster selama periode Desember 2020 – Februari 2021. Data yang dikumpulkan dikategorikan dan diolah dengan proses tabulasi dan diinterpretasi secara deskriptif menggunakan aplikasi Microsoft Excel for Mac, Qualitative Software Statistical Package for Social Science (SPSS) 23.0 dan NVivo for Mac untuk menganalisis data kualitatif. Hasil analisis menunjukkan bahwa sebagian besar unggahan hoaks Covid-19 di Facebook adalah dalam bentuk pesan gambar. Penggunaan kata terbanyak dalam judul berita pada periode penelitian ini adalah vaksin. Hampir semua unggahan berita hoaks diunggah oleh akun pribadi dan jenis berita hoaks terbanyak adalah misleading content.
Keyword: analisis isi, covid-19, facebook, hoaks, media sosial

Judul: Analisis Sentimen Terhadap Vaksinasi Covid-19 di Indonesia Menggunakan Data Twitter
Abstrak: Jenis baru virus corona ditemukan di Kota Wuhan, Tiongkok pada Desember 2019 dan terus menyebar ke seluruh dunia. Virus ini menyebabkan penyakit yang dinamakan Coronavirus Disease-19 (Covid-19). World Health Organization (WHO) telah menetapkan wabah ini sebagai pandemi global pada 11 Maret 2020. Salahsatu cara untuk menghentikan pandemi adalah dengan membentuk kekebalan komunitas yang bisa didapat melalui program vaksinasi. Program ini masih menimbulkan pro dan kontra pada awal pelaksanaannya di Indonesia. Masih banyak yang meragukan keamanan dan efek samping yang ditimbulkan dari vaksin. Penelitian ini membagi sentimen menjadi tiga kelas yaitu positif, negatif, dan netral. Proses pelabelan dilakukan secara manual dan kemudian dilakukan pemodelan menggunakan metode Bernoulli naive Bayes dan regresi logistik. Hasil penelitian menunjukkan Bernoulli naive Bayes menghasilkan model dengan performa lebih baik dan stabil dengan rataan nilai F1-score sebesar 0,63 dan simpangan baku 0,02. Mayoritas tweet pada tanggal 15 Januari 2021- 28 Januari 2021 memiliki sentimen netral. Banyaknya tweet dengan sentimen negatif mengalami tren penurunan setelah pekan pertama program vaksinasi. Topik yang sering dibicarakan pada tweet dengan sentimen negatif adalah mengenai hasil uji klinis dan efek samping dari vaksin., A new variant of coronavirus was discovered in Wuhan, China on December 2019 and has spread to worldwide. This virus causes a disease called Coronavirus Disease-19 (Covid-19). World Health Organization (WHO) have stated Covid-19 as a global pandemic on March 11, 2020. One way to end this pandemic is to make herd immunity that can be obtained through the vaccination program. This program still raises pros and cons at the beginning of its implementation in Indonesia. Many people doubt the safety and side effects of the vaccine. This research divides sentiment into three classes: positive, negative, and neutral. The labelling process is done manually and modeled using Bernoulli naive Bayes and logistic regression. The result shows Bernoulli naive Bayes produces more good and stable model with 0.63 average F1-score and 0.02 standard deviation. The majority of tweet from January,15 2021 until January,28 2021 have neutral sentiment. There is a decreasing trend on negative sentiment after the first week of vaccination program. Frequently discussed topic for negative sentiment is about clinical trial results and side effect of vaccine.
Keyword: Bernoulli naive Bayes, Covid-19 vaccination, Twitter

Judul: Thermal Characteristics and Dynamics of Tropical Cyclone over Western North Pacific Ocean: A Case Study of Typhoon Songda (Chedeng) 2011
Abstrak: The frequent occasion of Tropical Cyclone (TC) over Western North Pacific (WNP) Ocean lies from 10˚N to 26˚N and 121˚E to 170˚E. Sources of TC development come from warm ocean temperature where latent heat is released during condensation processes and subsequently concentrated in the boundary layer. Relative humidity at 850-700 hPa is responsible to produce the most intense storm. Meanwhile, weak vertical wind shear between 850-200 hPa is one of the dynamical factors that lead to the development of TC. Pressure level of 850-200 hPa is chosen to minimize the thermodynamic effect in the lower troposphere. Typhoon Songda (Chedeng in the Philippines) or TSC lasted from May 18th to 30th, 2011 and strengthened into powerful Super Typhoon stage between May 24th and 27th. Long curving track and the exhibition of all sequences of TC life cycle, TSC is then considered as an ideal case of TC. The objective of the study with case of TSC is to investigate the role of thermal characteristics and dynamics on TC intensity. The research is carried out by using Advanced Research of Weather Research and Forecasting model (WRF ARW model) version 3.3. Two domains are employed in the model. The first domain situate from 02˚N to 40˚N and 118˚E to 149˚E and cover spatial resolution () of 33.1 km. The second domain situate from 09˚N to 27˚N and 119˚E to 132˚E with of 11 km. Timestep of the model () is 120 seconds. The model is supported by the following physical parameterization, i.e., Yonsei University Scheme (YSU) in the boundary layer, Kain-Fritsch scheme (KF) in the cumulus, and WRF Single-Moment 3-class scheme in the microphysics. Initial meteorological condition prior to the formation of the cyclone is generated using WRF ARW standard-release model. Sensitivity of the model output is obtained from a selected single-parameter change scenarios, namely, 10 % to 20 % decrease and increase of wind shear initial data at 850-200 hPa, and by 10 % to 20 % decrease of relative humidity initial data at 850-700 hPa. The result showed that the negative correlations between wind shear and intensity are found in wind shear scenarios. Wind shears of 10 ms-1 which lead to strengthening of the wind intensity in the early period of Typhoon development are found in wind shear scenarios. The effect of wind shear changes on wind intensity is statistically significant in the 20 % wind shear scenarios. During mature stage, weak wind intensity occurred when wind shear increase as given in the WRF standard-release and the 20 % decreasing scenario. Different situation is found in the 20 % increasing scenario where wind shear tend to weak and lead to strong wind intensity at this stage. Meanwhile, the reduction of moisture supply at 850-700 hPa resulting from 20 % decreasing relative humidity play a major role in the weakening of wind intensity and reduces mechanical energy of the cycle process as much as 300 J kg-1.
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