Judul: SEIRU Model Analysis on Jakarta’s COVID-19 Cases
Abstrak: Sejak masa awal penyebaran COVID-19, banyak negara yang menerapkan kebijakan pembatasan aktivitas publik guna menekan laju penularan COVID-19. Pemerintah Indonesia memilih menerapkan Pembatasan Sosial Berskala Besar (PSBB) yang pertama kali diterapkan di Provinsi DKI Jakarta. Efek kebijkan yang diterapkan dapat diteliti menggunakan model epidemi SEIRU. Model epidemi SEIRU merupakan model epidemi dengan periode laten yang memperhitungkan efek kebijakan pembatasan aktivitas publik. Pada penelitian ini penulis telah mengimplementasi model SEIRU pada kasus COVID-19 di Jakarta, mengevaluasi parameter yang paling sesuai dalam merepresentasikan kasus COVID-19 Jakarta, serta mengetahui efek sistem pemberlakukan PSBB Jakarta terhadap kesesuaian implementasi model. Implementasi dilakukan menggunakan bahasa pemrograman Julia. Hasil implementasi menunjukkan bahwa model SEIRU sesuai untuk menggambarkan dinamika kasus COVID-19 sampai akhir masa pemberlakuan PSBB pertama, namun tidak sesuai untuk masa perpanjangan pemberlakuan PSBB. Didapatkan pula perkiraan efek PSBB yang diterapkan dapat menurunkan jumlah kasus terlapor sebanyak 41% dengan rata-rata waktu individu infektif di Jakarta tak memiliki gejala ialah 7 hari dan rata-rata durasi periode latennya adalah 6 jam., Since the early days of the spread of COVID-19, many countries have implemented policies to limit public activities due to reducing the transmission rate of COVID-19. The Indonesian government chooses to implement the Large-Scale Social Restrictions (PSBB) which were first implemented in DKI Jakarta Province. The effect of the applied policy can be studied using the SEIRU epidemic model. The SEIRU epidemic model is an epidemic model with a latency period that takes into account the effects of public activity restriction policies. In this research, the author will implement the SEIRU model on Jakarta’s COVID-19 cases, evaluate the parameters that are most suitable in representing the Jakarta’s COVID-19 cases, and determine the effect of the Jakarta’s PSBB system on the suitability of the model implementation. The implementation is done by using the Julia programming language. The result of the implementation shows that the SEIRU model is suitable for describing the dynamics of the COVID-19 case until the end of the first period of PSBB, but it is not suitable for the extension period of the PSBB. It is also found that the PSBB could reduce the number of reported cases by 41% with the average time of the infective individuals in Jakarta without symptoms is 7 days and the average duration of the latent period is 6 hours.
Keyword: COVID-19, PSBB, SEIRU, epidemic model, latency period

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: Morfologi Organ Reproduksi Betina Walet Linchi (Collocalia linchi)
Abstrak: This research is aimed to describe the morphology of the female reproductive organs of the cave swiftlets (C. linchi ) macroscopic and microscopically. Four female reproduction organs were used in this study. Microscopic observation was done using Hematoxilin – eosin (HE), alcian blue (AB) pH 2.5 and periodic acid Schiff (PAS) staining methods. The reproductive organs were consisted of ovarium and oviduct. The oviduct has five parts: infundibulum, magnum, isthmus, uterus and vagina. The mucosa of oviduct has mucosal folds and lined with columnar ciliated epithelial cells. Glandular glands were found in the lamina propria of oviduct, except in the vagina. The thick muscle of sphincter uterovagina was found in the border between uterus and vagina. Using AB-PAS staining methods, it was detected that oviduct contained neutral and acid carbohydrate, especially in the secrete glands of oviduct.
Keyword: oviduct., ovarium, Collocalia linchi