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INCREASING PUBLIC PARTICIPATION TO PREVENT THE SPREAD OF COVID-19 IN DUKUH KUPANG SURABAYA Winarno; Deny Arifianto; Myrna Adianti; Eva Inaiyah Agustin; Sisca Dina Nur Nahdliyah; Elsyea Adia Tunggadewi; Ali Suryaperdana Agoes
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 6 No. 1 (2022): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jlm.v6i1.2022.235-243

Abstract

Novel Coronavirus 2019 (covid-19) is a generation of the coronavirus that humans have never identified. This virus was first reported to cause an outbreak in Wuhan, China, in December 2019. Until now, covid-19 infection cases have been reported in many countries, such as Thailand, Japan, South Korea, Iran, Italy, Germany, and more than 90 countries worldwide. Until November 1, 2020, a total of 412.784 positive cases of covid-19 were recorded, with 341.942 recovered patients and 13.943 deaths in Indonesia. The purpose of this event is to anticipate the spread of Covid-19 by reminding the public to maintain health protocols and other alternatives in preserving health, also increasing body immunity through massage and traditional Indonesian herbal medicine. This event received a good response from the public. It was evidenced by the number of participants exceeding the predetermined quota and enthusiastic in following the speaker's material. The event was a success and was well received by the participants as well as the local government. After following this event, participants can practise the knowledge obtained from the presenters to maintain and protect their health and immunity from Covid-19. Keywords: Covid-19, Community service, body immunity DAFTAR PUSTAKA Amri, Sofan. Iif Khoiru Ahmadi. 2010. Proses Pembelajaran Kreatif dan Inovatif Dalam Kelas: Metode, Landasan Teoritis-Praktis dan Penerapannya. Jakarta: PT. Prestasi Pustakaraya. Badan Pusat Statistik Kota Surabaya. “Jumlah RT RW Kecamatan Dukuh Pakis Menurut Kelurahan Tahun 2017”. surabayakota.bps.go.id. https://surabayakota.bps.go.id/statictable/2018/04/19/594/jumlah-rt-rw-kecamatan-dukuh-pakis-menurut-kelurahan-tahun-2017.html. (diakses 15 Desember 2020). Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z. 2020. “Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China”. Lancet 2020: 395: 497-506. doi: https://doi.org/10.1016/S0140-6736(20)30183-5. Kementerian Kesehatan Republik Indonesia. 2020. Pedoman Kesiapsiagaan Menghadapi Coronavirus Disease (covid-19). Jakarta: Direktorat Jenderal Pencegahan dan Pengendalian Penyakit (P2P). Komite Penanganan Covid-19 dan Pemulihan Ekonomi Nasional. “Pasien Sembuh Harian Mencapai 4.141 Orang”. covid19.go.id. https://covid19.go.id/berita/pasien-sembuh-harian-mencapai-4141-orang. (diakses 15 Desember 2020). Kumar, M., & Dwivedi, S. 2020. “Impact of Coronavirus Imposed Lockdown on Indian Population and their Habits”. International Journal of Science and Healthcare Research Vol.5 Issue: 2: April-June 2020. ISSN: 2455-7587. Li, S., Wang, Y., Xue, J., Zhao, N., & Zhu, T. 2020. “The impact of covid-19 epidemic declaration on psychological consequences: A study on active weibo users”. International Journal of Environmental Research and Public Health, 17(6), 1–9. doi: https://doi.org/10.3390/ijerph17062032. Pemerintah Kota Surabaya, “Statistik”. lawancovid-19.surabaya.go.id. https://lawancovid-19.surabaya.go.id/visualisasi/graph. (diakses 15 Desember 2020). Rizma Riyandi. “Data Kecamatan Surabaya: Dukuh Pakis, Penduduk dan Wilayah”. ayosurabaya.com. https://www.ayosurabaya.com/read/2020/09/28/3230/data-kecamatan-surabaya-dukuh-pakis-penduduk-dan-wilayah. (diakses 15 Desember 2020). Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, Zhao X, Huang B, Shi W, Lu R, Niu P. 2020. “A novel coronavirus from patients with pneumonia in China, 2019”. New England Journal of Medicine 2020: 382: 727-733. doi: 10.1056/NEJMoa2001017
PREDIKSI WATER REMOVAL PADA PROSES DEHYDRATION GAS ALAM MENGGUNAKAN JARINGAN SYARAF TIRUAN Sisca Dina Nur Nahdliyah; Deny Arifianto; Winarno .
Jurnal Teknologi Informasi dan Komputer Vol 7, No 4 (2021): Jurnal Teknologi Informasi dan Komputer
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

ABSTRACTRaw natural gas contains water vapor or hydrates that must be purified to meet sales gas specifications. The most commonly used water vapor purification process is the natural gas absorption dehydration process with TEG. The optimal natural gas dehydration process is indicated by the water removal value in accordance with gas sales standards, where the water removal value is influenced by the operating conditions and the raw natural gas feedstock. Therefore, this study predicts the water removal value of the natural gas dehydration process using MLP (Multi-Layer Percepton) neural network with NARX structure (Nonlinear AutoRegressive, eXternalinput) using Levenberg-Marquardt learning algorithm in order to obtain optimal operating conditions. The input parameters of the artificial neural network are operating conditions, raw natural gas components, and TEG content, while the output is the value of water removal and reboiler energy. The results showed that the Root Mean Square Error (RMSE) on the training data was 0.0005 kgmole/h for water removal and 0.0010 kW for reboiler energy, proving that the ANN model used had a fairly good performance in capturing complex and nonlinear characteristics in the natural gas dehydration process.Keywords: Natural Gas, Dehydration, Artificial Neural Networks, Prediction, Water RemovalABSTRAKGas alam mentah mempunyai kandungan uap air atau hidrat yang harus dimurnikan agar memenuhi spesifikasi gas penjualan. Proses pemurnian kandungan uap air yang paling sering digunakan adalah proses dehydration gas alam absorpsi dengan TEG. Proses dehydration gas alam yang optimal ditunjukkan oleh nilai water removal yang sesuai dengan standart penjualan gas, dimana nilai water removal dipengaruhi oleh kondisi operasi dan bahan baku gas alam mentah. Oleh karena itu, penelitian ini memprediksi nilai water removal proses dehydration gas alam menggunakan jaringan syaraf tiruan MLP (Multi Layer Percepton) struktur NARX (Nonlinear AutoRegressive, eXternalinput) dengan algoritma pembelajaran Levenberg-Marquardt agar mendapatkan kondisi operasi yang optimal. Parameter input jaringan syaraf tiruan adalah kondisi operasi, komponen gas alam mentah, dan kandungan TEG, sedangkan output adalah nilai water removal dan energi reboiler. Hasil penelitian diperoleh nilai Root Mean Square Error (RMSE) pada data latih sebesar 0,0005 kgmol/jam untuk water removal dan 0,0010 kW untuk energi reboiler, membuktikan bahwa model JST yang digunakan memiliki kinerja yang cukup baik dalam menangkap karakteristik komplek dan nonlinear pada proses dehydration gas alam.Kata Kunci : Gas Alam, Dehydration, Jaringan Syaraf Tiruan, Prediksi, Water Removal