Judul: Predicting the COVID-19 Epidemic Using SEIR Dynamics Modeling
Abstrak: Penelitian ini bertujuan memprediksi epidemi COVID-19 menggunakan model Susceptible-Exposed-Infectious-Recovered (SEIR) COVID-19 di beberapa negara seperti Indonesia, Singapura, Iran, dan Filipina. Model SEIR empat kompartemen digunakan untuk menduga parameter beta (β) sebagai tingkat infeksi, gamma (γ) sebagai tingkat pulih atau kematian, dan sigma (σ) sebagai kebalikan dari waktu laten rata-rata. Pendugaan parameter tersebut dilakukan melalui proses reduksi sekuensial matematis dari persamaan model pertumbuhan logistik sehingga model selalu diuji dan diterapkan pada data terbaru dari kasus COVID-19 yang terkonfirmasi sampai terbentuk grafik prediksi yang sesuai dengan data aktual. Penelitian menunjukan fitting model terhadap data aktual dengan nilai akurasi kurang dari 30% dan dibutuhkan penyesuaian parameter yang lebih tepat. Model SEIR dapat mendemonstrasikan dengan jelas karakteristik parameter yang dapat mencerminkan upaya pencegahan penyebaran wabah COVID-19. Wilayah yang dijadikan objek penelitian meliputi Singapura, Arab Saudi, Filipina, dan Indonesia., This study aims to predict the COVID-19 epidemic using the Susceptible-Exposed-Infectious-Recovered (SEIR) model of COVID-19 in several countries such as Indonesia, Singapore, Iran, and the Philippines. The four-compartment SEIR model was used to estimate the parameters beta (β) as the infection rate, gamma (γ) as the recovery or death rate, and sigma (σ) as the reciprocal of the mean latency time. The parameter estimation is carried out through a mathematical sequential reduction process from the logistic growth model equation so that the model is always tested and applied to the latest data from confirmed COVID-19 cases until a predictive graph is formed that matches the actual data. The research shows that the model fits the actual data with an accuracy value of less than 30% and more precise parameter adjustments are needed. The SEIR model can demonstrate the characteristics of parameters that can reflect efforts to prevent the spread of the COVID-19 outbreak. The areas used as research objects include Singapore, Saudi Arabia, the Philippines, and Indonesia.
Keyword: prediction, COVID-19, data fitting, prediksi, epidemi, SEIR, epidemic

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: Sifat Pulp Campuran antara Pulp Asli Bambu dan Pulp Karton Bekas (Old Corrugated Containers)
Abstrak: OCC was soaked for 7 days and disintegrated afterward. Soda pulping of bamboo was carried out following the pulping parameters of 35% NaOH charge, L/W of 4/1, maximum temperature of 170 oC and total cooking time of 3 hours. Kappa number and pulping yield were determined based on TAPPI T236 cm-85 standard. Bamboo and OCC pulp was bleached following the method of D0ED1D2. Bleached bamboo pulp was beaten up to the freeness of 100, 200, 300, and 400 ml CSF. While that of OCC was up to 400 ml CSF only. The composisitions of bamboo/OCCpulp mixture (B/K) were 0/100, 20/80, 40/60, 60/40, 80/20 and 100/0. Physical and optical properties of pulp mixture were determined based on TAPPI T205 sp-02 standard. The pulp composition of (B/K) 20/80 at freeness level of 400 ml CSF was resulted in the highest strength properties based on Duncan scoring. Pulp beating was able to decrease the composition of bamboo pulp in pulp mixture while retaining the strength properties
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