Judul: Analysis of  Covid-19 Risk Perception Survey Results Using Generalized Structured Component Analysis
Abstrak: Ibu kota Indonesia, DKI Jakarta, menjadi provinsi dengan jumlah Covid-19 tertinggi. Merespon hal ini, LaporCovid-19 bekerja sama dengan Social resilience Lab, Nanyang Technological University melakukan survei untuk mengukur bagaimana persepsi warga Jakarta terhadap risiko Covid-19 mulai 29 Mei hingga 20 Juni 2020. Peubah yang memengaruhi persepsi risiko merupakan peubah yang tidak dapat diukur. secara langsung sehingga dianalisis menggunakan pendekatan Structural Equation Modeling (SEM), yaitu Generalized Structured Component Analysis (GSCA). Skala likert bersifat ordinal tetapi ada beberapa penelitian menggunakan skala likert sebagai interval. Oleh karena itu, penelitian ini akan membandingkan metode GSCA dengan nonlinear GSCA dan mengevaluasi enam peubah, yaitu persepsi risiko, pengetahuan, informasi, peilaku kesehatan, modal sosial, dan ekonomi. Evaluasi model secara keseluruhan menunjukkan bahwa nonlinear GSCA dapat menjelaskan keragaman data kualitatif lebih baik daripada GSCA dengan FIT > 0.9. Nonlinear GSCA menghasilkan peubah informasi berpengaruh terhadap pengetahuan, ekonomi dan modal sosial memiliki hubungan timbal balik, sedangkan pengetahuan dan persepsi risiko berpengaruh terhadap perilaku kesehatan., The capital city of Indonesia, Jakarta, became the province with the highest number of Covid-19. Response this situation, LaporCovid-19 collaborate with the Social Resilience Lab, Nanyang Technological University conducted a survey to measure how Jakarta residents perceive the risk of Covid-19 from May 29 to June 20 2020. Factors of risk perception are variables that cannot be measured directly, so they are analyzed used a Structural Equation Modeling (SEM) approach, namely Generalized Structured Component Analysis (GSCA). The Likert scale used can be considered as interval or ordinal depending on the point of view of the theory built. Therefore, this study will compare the GSCA method with the nonlinear GSCA and evaluate six variables, namely risk perception, knowledge, information, health behavior , social capital, and economy. Evaluation of the overall model showed that the nonlinear GSCA model can explain the diversity of qualitative data better than the GSCA model with FIT > 0.9. Based on GSCA nonlinear model, information has significantly influence of knowledge, economy and social capital have a real reciprocal relationship, along knowledge and risk perception have significantly influence of health behavior.
Keyword: persepsi risiko, SEM, GSCA, nonlinear GSCA

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: Apatite Growth Optimation on Chicken Mucouse by Fourier Transform Infrared (FTIR) Characterization
Abstrak: Some experiment had been conducted to grow apatite from supersaturated solution of calcium phosphate ions on chicken mucouse. The calcium and phosphate ions were originated from Ca(NO3)2 and (NH4)2HPO4. Carbonate ions from (NH4)2CO3 was also used as starting solution. Experiment was carried out within about 5 hours at temperature 370 C and pH 7. Value of Ca+ : PO4 3- was 1.67, while molar ratio of CO3 2- : PO4 3- was 0.5 : 1. Molarity of molar ratio CO3 2- : PO4 3- variated approximately 0.15 : 0.30, 0.51 : 1.02, and 0.90 : 1.80. Mass of mucouse powder was constant 0.75 gram. The analysis result of Fourier Transform Infrared (FTIR) showed that the precipitation was apatite carbonate type A and B. In these experiment it was found out that the mucouse reduce the crystallinity of apatite precipitant, and the growth of apatite crystal was optimum at solution with molar ratio CO3 2- : PO4 3- about 0.15 : 0.30.
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