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All Journal Edumatsains AMMA : Jurnal Pengabdian Masyarakat
Ratna Widayati
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Agriculture, Biological Sciences & Forestry Humanities Chemistry Education Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Nursing Physics

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Edukasi Vaksinasi Covid-19 di Desa Henda Kabupaten Pulang Pisau Kalimantan Tengah Ratna Widayati; Herlina Eka Shinta; Angeline Novia Toemon
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Covid-19 is a highly contagious infectious disease. Transmission can be through coughing or sneezing droplets, or indirectly through objects contaminated with droplets from coughs or sneezes of Covid-19 sufferers. One of the reasons is is the lack of public understanding of the importance of the Covid-19 vaccination. One attempt to increase people's understanding is by providing health education about the importance of vaccination as an effort to reduce the incidence of Covid-19. By providing this health education, the public will have good understanding about the importance of Covid-19 vaccination, and will voluntarily participate in the Covid-19 vaccination program to support the government, especially Central Kalimantan Province in suppressing the growth rate of Covid-19 incidence. The purpose of this activity is to increase public awareness. about the importance of the Covid-19 vaccination. This activity was carried out in Henda Village, Jabiren District, Pulang Pisau Regency face-to-face, with lecture and discussion methods using leaflet media. The participants of the activity were very enthusiastic, and based on the results of the evaluation, it was found that the participants became more knowledgeable about the importance of the Covid-19 vaccination.
Markov Chain Model for Daily Rainfall Modeling in Bengkulu City Rachmawati, Ramya; Firdaus; Ratna Widayati; Siska Yosmar; Risfa Fadila; Ajeng Siti Nurul Kharima
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 10 No 4 (2026): April
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v10i4.8000

Abstract

Bengkulu City is a region in Indonesia that is particularly vulnerable to shifts in rainfall patterns, which can have significant impacts on the agricultural sector, water resource management, and disaster mitigation. The uncertainty in rainfall patterns often complicates long-term planning. Hence, it is necessary to adopt a statistical approach that can model and predict rainfall characteristics with greater accuracy. This research aims to develop a Markov Chain model to represent the daily rainfall regime in Bengkulu City. The daily rainfall data are categorized into rainfall intensity states, namely: no rain, light, moderate, heavy, or very heavy rainfall. By leveraging historical daily rainfall data, this model is expected to identify the transition probabilities between these states. Based on the obtained steady-state probabilities, it can be concluded that regardless of today’s rainfall condition in Bengkulu City, the long-term probabilities for tomorrow’s weather are as follows: 38% for no rain, 43% for light rain, 13.8% for moderate rain, 4.2% for heavy rain, and 1% for very heavy rain.
Co-Authors Ajeng Siti Nurul Kharima Angeline Novia Toemon Firdaus Ramya Rachmawati Risfa Fadila Siska Yosmar