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: Time Series Clustering and Multi-Input Transfer Function Model for Covid-19 Incidences in Jakarta
Abstrak: The coronavirus, known as the Covid-19 virus, has become a global issue since this virus was first identified in December 2019 in Wuhan, China. This virus is not only disrupting the medical order but also affecting socio-economic conditions around the world. To date, only six countries worldwide have recorded zero cases of Covid-19. The massive spread of the virus caused 3.17 million people to be infected within 20 months, with 83,000 deaths. Indonesia is one of the countries with a very high spread of Covid-19 cases. The positive rate for Covid-19 cases in Indonesia in July 2021 reached 23% or almost five times the standard set by WHO. This condition has brought various handling reactions to curb the spread of Covid-19 in Indonesia, starting from the imposition of restrictions on community activities, accelerating the distribution of vaccinations, and scientifically data-based studies in handling Covid-19 in Indonesia. Seeing the very high rate of spread of Covid-19 cases in Indonesia, this does not escape the contribution of Covid-19 cases in 34 provinces. Several provinces recorded the highest cases, including Jakarta, West Java, Central Java, East Java, and South Sulawesi. Based on the Covid-19 handling task force data, among the five provinces, it was noted that Jakarta was the province with the highest Covid-19 incidence in Indonesia. The incidence of Covid-19 in DKI Jakarta reached 1.91% and contributed 25% for national cases. This situation is critical considering that DKI Jakarta is the center of the economy and should be a role model for other provinces regarding handling Covid-19 cases in Indonesia. The study of Covid-19 spread in Jakarta is necessarily considered due to the high mobilization of the community in Jakarta so that the policies that can be taken are right on target. The research carried out in this study was based on daily data on Covid-19 cases in DKI Jakarta, which were recorded at the sub-district level, even at the village level. Based on the daily data recording, this study aims to classify sub-districts in Jakarta based on the similarity in the distribution pattern of Covid-19 cases. The grouping of these sub-districts is carried out through a hierarchical time series cluster analysis. The hierarchical time-series clustering analysis was carried out by calculating the distance between two sub-districts from 44 sub-districts in Jakarta. Distance calculation is done using Dynamic Time Warping technique. Calculating the distance between two sub-districts will produce a distance matrix measuring 44×44 which is the basis for hierarchical clustering. The two districts with the minimum distance will be combined in a temporary cluster, and the distance matrix will be evaluated to 43×43. This process is carried out until only one cluster is formed. Evaluation of the distance matrix is done through the average linkage method. The results of this study classify 44 districts in DKI Jakarta into six optimal clusters based on the size of the Silhouette coefficient. The six clusters provide several unique characteristics that can be used as one of the keywords in formulating policies for handling Covid-19 cases in Jakarta. The characteristics formed include that cluster A has the
Keyword: ARIMA, Covid-19, Time Series Clustering, Transfer Function

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