Judul: Kinerja Model Deret Waktu berbasis Richard dan Logistik dalam Prediksi Kasus Baru COVID-19
Abstrak: A growth curve is a non-linear model to capture the growth process. Growth curves have been applied in many sectors, especially in the health sector. It can capture the growth of bacteria or cancer cells. Recently, the growth curve widely used to capture the future situation of the pandemic situation because of COVID-19 that spread all around the world. The Logistic growth curve is a growth curve that has characteristics such as taking very slowly at the early growth process, then rising sharply, and then slowing as it approaches the maximum carrying capacity. Another growth curve is the Richard growth curve which has a more flexible form than the Logistic growth curve to form the s-line in the cumulative curve. The first derivative of growth curves can be transformed into linear equations and hence, it can be modelled using time series analysis. This research interest is to evaluate performance of time series models based on Logistic and Richard growth curves in predicting new cases of COVID-19. This research used two types of data to evaluate the models. First, it is based on simulation methods to evaluate the bias, RMSE, and variance of the parameter estimates. Furthermore, the RMSEP of forecasting based on testing data is also calculated by means of simulation. The result showed that the Richard model tended to have a small bias and RMSE of parameter estimates when compared to Logistic model if the period of the training data was prolonged. However, if the data is generated from Logistic growth curve bias and RMSE of Logistic model are smaller than Richard model. These results were also shown by the RMSEP calculated based of the testing data. Regarding the evaluation of the variance of the parameter estimate, the result showed that Logistic growth curve tended to produce smaller variance when compared to the variance of Richard growth curve. The second evaluation is based on empirical dataset, in this case the weekly new cases of COVID-19 in Jakarta have been used. Using this empirical data the Richard growth curve performed better than the Logistic growth curve. This has been indicated by the RMSE and MAPE of predicting the training data. Moreover, this was also shown by RMSEP and MAPE calculated based on testing data in which the Richard growth curve tended to produce smaller values than the Logistic growth curve. This situation also has been shown by the 95% prediction interval of forecasting the testing data in which the prediction interval based on Richard model has included more testing data than the prediction interval based on Logistic model.
Keyword: Kurva Pertumbuhan, COVID-19, Peramalan, Kurva Pertumbuhan Richard, Kurva Pertumbuhan Logistik, Growth Curve, Forecasting, Richard Growth Curve, Logistic Growth Curve

Judul: Prediksi Epidemi Coronavirus Disease 2019 Menggunakan Model Dinamika SIR
Abstrak: Penelitian ini bertujuan memprediksi epidemi Coronavirus Disease 2019 (COVID-19) menggunakan model Susceptible-Infectious-Recovered (SIR). Model ini telah banyak digunakan untuk menggambarkan evolusi waktu epidemi penyakit menular. Versi asli model Kermack dan McKendrick yang digunakan dalam penelitian ini mencakup laju penyebaran infeksi oleh individu yang terinfeksi per hari ketika individu tersebut berinteraksi dengan populasi yang rentan (parameter β) dan laju pemulihan untuk menentukan jumlah individu yang pulih (parameter γ). Estimasi parameter tersebut ditentukan dalam model SIR tiga kompartemen dengan proses reduksi sekuensial matematis dari persamaan model pertumbuhan logistik. Karena parameter ini merupakan karakteristik dasar evolusi waktu epidemi, maka model selalu diuji dan diterapkan pada data terbaru dari kasus COVID-19 yang terkonfirmasi. Model sederhana ini dapat diandalkan untuk menggambarkan dinamika epidemi COVID-19, tidak hanya secara kualitatif tetapi juga secara kuantitatif dengan tingkat korelasi tinggi antara data aktual dengan hasil prediksi. Model SIR dapat mendemonstrasikan dengan jelas karakteristik parameter yang dapat mencerminkan upaya pencegahan penyebaran wabah COVID-19. Penelitian ini menjadikan Singapura, Arab Saudi, Filipina, dan Indonesia sebagai wilayah yang dijadikan objek penelitian., This study aims to predict the Coronavirus Disease 2019 (COVID-19) epidemic using the Susceptible-Infectious-Recovered (SIR) model. This model has been widely used to describe the time evolution of infectious disease epidemics. The original version of the Kermack and McKendrick model used in this study included the rate of spread of infection by infected individuals per day when the individual interacted with a susceptible population (parameter β) and recovery rate to determine the number of recovered individuals (parameter γ). The parameter estimates were determined in a three-compartment SIR model with a mathematical sequential reduction process from the logistic growth model equation. Since this parameter is a basic characteristic of the time evolution of the epidemic, the model is always tested and applied to the latest data from confirmed COVID-19 cases. This simple model still seems reliable enough to describe the dynamics of the COVID-19 epidemic, not only qualitatively but also quantitatively with a high degree of correlation between the actual data and the predicted results. This model can clearly demonstrate the characteristics of the parameters that can reflect the efforts to prevent the spread of the COVID-19 outbreak by each country. This research makes Singapore, Saudi Arabia, Philippines, and Indonesia as the research object.
Keyword: compartement, COVID-19, epidemic, estimation, pandemic

Judul: Elektrodeposisi Film Tipis Semikonduktor Cu2ZnSnS4 (CZTS) pada Substrat Kaca ITO
Abstrak: Semiconductor Cu2ZnSnS4 (CZTS) thin film that can be used as absorber layers on solar cell module was made via electrodeposition method. CZTS thin film was electrodeposited on the surface of a silicate glass coated with a thin layer of indium tin oxide (ITO). Deposition process was done using potentiostatic mode at room temperature with a potential of 1.05 V for 30, 45, and 60 minutes, followed with annealing the film at 2 different temperatures, 500 ºC using furnace and 180 ºC using hot plate, both treatments for 45 minutes in N2/H2S atmosphere. The X-ray difractograms were analyzed using Match 2 program and showed that the CZTS thin films had kesterit crystalline structure, with a low percentage of CZTS phase. The thin film also contained secondary phases such as Cu2S, ZnS, and SnS. The obtained CZTS thin films had a thickness between 1.039 and 1.676 μm. Absorption study showed that the band gap energy of CZTS thin films which was annealed using furnace ranged from 1.50 to 1.52 eV, whereas that annealed using the hot plate was not observed. The band gap energy value showed that CZTS thin films can be used as sunlight absorber layers on solar cell. The formation of CZTS crystal film on this investigation was effectively performed using furnace annealing process at a temperature of 500 ºC with deposition time of 45 minutes.
Keyword: Thin film, Electrodeposition, Cu2ZnSnS4