Judul: Description and Prediction Analysis of the Spread of COVID-19 Cases in East Java Province
Abstrak: Coronavirus Disease 2019 (COVID-19) merupakan penyakit menular yang dapat menyebabkan gangguan sistem pernapasan. Penyakit ini memiliki sifat yang mudah menular antar individu. Laju penyebaran COVID-19 dapat dipengaruhi oleh keadaan sosial-ekonomi suatu wilayah. Penelitian ini akan menggunakan model Autoregressive Integrated Moving Average (ARIMA) untuk memprediksi jumlah kasus COVID-19 di Provinsi Jawa Timur. Model ARIMA (1,1,1) yang diperoleh mampu memprediksi jumlah kasus penyebaran COVID-19 dengan baik ditunjukkan dengan nilai Mean Absolute Percentage Error (MAPE) sebesar 12,70%. Nilai tersebut menunjukan bahwa kesalahan peramalan berkisar 12,70% saja dari nilai aktual di lapangan. Model yang diperoleh baik untuk memprediksi dalam jangka pendek harian. Selain itu, dilakukan analisis pengaruh faktor sosial-ekonomi terhadap laju transmisi COVID-19 di Provinsi Jawa Timur. Faktor yang paling berpengaruh terhadap banyaknya jumlah kasus COVID-19 di Provinsi Jawa Timur adalah Produk Domestik Regional Bruto-Atas Dasar Harga Konstan (PDRB-ADHK), Persentase Penduduk Lansia, dan Jumlah Populasi.
Keyword: COVID-19, deskripsi, ekonomi, prediksi, sosial

Judul: Prediction Model Number of COVID-19 Cases and Analysis Based on Demography, Social and Economy Using Long Short Term Memory (Case Study: East Java Province)
Abstrak: Coronavirus Disease 2019 atau (COVID-19) disebabkan oleh jenis virus corona baru yang dapat menimbulkan penyakit pernapasan. Penyakit ini ditemukan pertama kali di Wuhan, China, pada bulan Desember 2019. Virus ini ditularkan melalui cairan atau kontak langsung dan menginfeksi saluran pernapasan yang mengakibatkan pneumonia di sebagian besar kasus. Faktor demografi, sosial dan ekonomi merupakan faktor-faktor yang mendorong penyebaran penyakit menular. Antisipasi dan pengukuran dari berbagai faktor yang terlibat dalam penyakit menular dapat dimodelkan secara matematis dengan pemodelan matematika. Penelitian ini melakukan pemodelan prediksi kasus COVID-19 di Jawa Timur menggunakan Long Short Term Memory (LSTM). Berdasarkan hasil penelitian, kabupaten/kota di Jawa Timur terbagi menjadi lima cluster sesuai karakteristik demografi, sosial dan ekonominya. Jumlah kasus positif COVID-19 yang tinggi terdapat di cluster dengan PDRB yang tinggi. Hasil analisis regresi menunjukan bahwa atribut PDRB merupakan atribut yang berpengaruh signifikan terhadap jumlah terkonfirmasi COVID-19 di Jawa Timur. Penelitian ini memperkirakan jumlah terkonfirmasi positif COVID-19 masih terus naik hingga akhir Juli 2021., Coronavirus Disease 2019 or (COVID-19) is caused by a new type of coronavirus that can cause respiratory disease. This disease was first discovered in Wuhan, China, in December 2019. This virus is transmitted through fluids or direct contact and infects the respiratory tract resulting in pneumonia in most cases . Demographic, social and economic factors are factors that encourage the spread of infectious diseases. The anticipation and measurement of various factors involved in infectious diseases can be modeled mathematically. This research conducts predictive modeling of COVID-19 cases in East Java using Long Short Term Memory (LSTM). Based on the research results, districts/cities in East Java are divided into five clusters according to their demographic, social and economic characteristics. Many positive cases of COVID-19 are found in clusters with a high value of Gross Regional Domestic Product (GDP regional). The results of the regression analysis indicate that GDP regional attribute is an attribute that has a significant effect on the number of positive confirmed cases of COVID-19 in East Java. This study estimates that the addition of the positive number of COVID-19 will continue to rise until the end of July 2021.
Keyword: COVID-19, demographic, economic, long short term memory, prediction modeling, social

Judul: Hybrid solar cells of ZnO nanoparticles/chlorophyll was modified metal ions (Zn2+ and Cu2+ )
Abstrak: Zinc Oxide (ZnO) is a n-type semiconductor with a wide the energy band (Band Gap) is 3.37 eV at room temperature and 3.34 eV at low temperature with a large exiton binding energy is 60 meV. ZnO has been synthesized by hydrothermal method, resulting in a decrease in particle size over the duration of the hydrothermal changes. Crystallographic structure of ZnO were characterized using XRD, has shown the characteristic pattern of a hexagonal wurtzite structure, the crystallite size increases to changes in particle size. Changes in particle size has also led to a change in the absorption peak of ZnO as has been demonstrated posted under test using the optical properties of UV-Vis spectrophotometer. Changes of this uptake has also led to changes in the energy band gap, which increases its band gap energy of the particle size. In electronic applications, especially in solar cells. Chlorophyll is considered less effective, because of their very nature are easily degraded as a result of several reactions which are acid, lighting and temperature. The results of the stability test using a halogen lamp 34 W/m2 for 5 hours, that the substitution of chlorophyll with metal ions Zn2+ and Cu2+ has been shown to form more stable than natural chlorophyll. The characterization of the optical properties, the combination of ZnO / chlorophyll in the form of hybrid films has led to a shift in the absorption region of ZnO becomes more widely from the UV to Visible. ZnO/chlorophyll has absorption range of 350-515 nm, ZnO / Zn-feofitin 332-401 nm and 332-632 nm for Cu-feofitin. The combination of ZnO/chlorophyll and CuSCN as a solid electrolite in hybrid solar cell, a modified chlorophyll with metal ions Zn2+ and Cu2+ has been shown to form a more stable I-V curve. It is characterized by its fill factor value greater than natural chlorophyll. Nevertheless, solar cells with natural chlorophyll has been able to produce higher efficiency values of chlorophyll were substituted.
Keyword: Hydrothermal, ZnO/Chlorophyll modified, Hybrid Solar Cell