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All Journal Jurnal Meteorologi Klimatologi dan Geofisika Social, Humanities, and Educational Studies (SHEs): Conference Series Proceedings of International Conference on Multidiciplinary Research
Dedi Sucahyono
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Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences

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PREDIKSI CURAH HUJAN BULANAN DI DELI SERDANG MENGGUNAKAN PERSAMAAN REGRESI DENGAN PREDIKTOR DATA SUHU DAN KELEMBAPAN UDARA Saragih, Immanuel Jhonson Arizona; Inlim Rumahorbo; Ricko Yudistira; Dedi Sucahyono
Jurnal Meteorologi Klimatologi dan Geofisika Vol 7 No 2 (2020): Jurnal Meteorologi Klimatologi dan Geofisika
Publisher : Unit Penelitian dan Pengabdian Masyarakat Sekolah Tinggi Meteorologi Klimatologi dan Geofisika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36754/jmkg.v7i2.192

Abstract

A simulation of monthly rainfall prediction (RR) using a regression equation with a predictor of air temperature (T) and humidity (RH) has been tried at Deli Serdang Climatology Station, North Sumatra. The RR, T and RH data for 30 years (1989-2018) were obtained from the Deli Serdang Climatology Station. This prediction simulation for total monthly rainfall uses simple linear regression and multiple linear regression. Evaluation is done by comparing and calculating the Pearson correlation value and the deviation of the predicted total monthly rainfall against the actual total rainfall. The results of data processing showed that the simulation of the total monthly rainfall forecast for 2019 in the Deli Serdang area obtained a correlation value of r = 0,72 and an average of RMSE = 77,42 mm / month using air temperature predictors, obtained correlation values r = 0,73 and RMSE = 77,13 mm / month using the air humidity predictor, and the correlation value r = 0,70 with RMSE = 80,53 mm / month using a predictor of air temperature and air humidity as well.
Validation of Rainfall Reanalysis Data to Explore Changes in Oldeman Agricultural Climate Patterns Due to Variability of Surface Temperature Anomalies with Time Series Analysis Techniques (Case Study of Dumai City for 30 Years Period) Bagus Primohadi Syahputra; Dedi Sucahyono
International Conference on Multidisciplinary Research Vol 4, No 1 (2021): ICMR
Publisher : Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/pic-mr.v4i1.3773

Abstract

Indonesia is a country with a population that still uses the agricultural sector as the highest livelihood. The Central Statistics Agency said 38.61% were in this sector. However, the issue of climate change caused by an increase in global temperature has begun to impact the agricultural sector in several regions. Therefore, this study aims to understand the effect of increasing surface temperature anomaly on the Oldeman climate pattern in Dumai City. The data used are in-situ observation rainfall data for 1981 - 2010, rainfall reanalysis data for 1991 - 2020, surface temperature anomaly data for 1991 - 2020. The data validation methods used are spearman correlation and Kendall-tau methods. The approach to explore changes in the Oldeman climate pattern uses time series analysis techniques such as ACF, PACF, and moving average of 1 year lag-time with a period of 10 years. The rainfall data validation test result show that the average spatial correlation value is 0.86. It can be used to explore time-series climate data in 3 locations in Dumai. As a result, time series analysis found a positive trend in rainfall data significantly along with the temperature anomaly but the Oldeman's climate pattern analysis in Dumai is monitored as stable in type B1. Overall, it is concluded that the change in the surface temperature anomaly variability and trend as a manifestation of climate change in Dumai has not impacted in the Oldeman agricultural climate patterns. Keywords: Climate Change, Oldeman, Time Series, Rainfall, Temperature
State of the Art of Remote Sensing in Flood Early Warning System: Review Article Agustina Rachmawardani; Giarno Giarno; Hapsoro A. Nugroho; Suharni Suharni; Dedi Sucahyono; Hariyanto Hariyanto; Sastra K. Wijaya
Social, Humanities, and Educational Studies (SHES): Conference Series Vol 5, No 4 (2022): Social, Humanities, and Educational Studies (SHEs): Conference Series
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (827.046 KB) | DOI: 10.20961/shes.v5i4.68977

Abstract

Sebagai negara tropis, Indonesia khususnya Jakarta sebagai ibukota negara mempunyai resiko terjadinya banjir yang cukup tinggi. Dampak banjir akan berpengaruh pada seluruh aspek kehidupan manusia. Selama kejadian banjir, laporan situasi yang tepatwaktu dan terperinci diperlukan oleh otoritas manajemen bencana untuk menemukan dan mengidentifikasi daerah yang terkena dampak  untuk menerapkan mitigasi kerusakan. Peringatan dini  banjir konvensional memanfaatkan data-data pengamatan ground station seperti data curah hujan, ketinggian aliran sungai maupun data debit sungai. Tidak semua wilayah yang terdampak banjir dicover oleh jaringan sensor ground station. Penginderaan jauh menyediakan data yang tepat dan berbiaya rendah dibanding dengan pengamatan lapangan, selain itu sistem penginderaan jauh juga dapat melakukan deteksi banjir lebih tepat dan mendekati real time. Sistem penginderaan jauh pada satelit dapat memberikan banyak informasi yang diperlukan untuk menggambarkan daerah yang terkena dampak banjir, menilai kerusakan, dan input yang tepat pada pemodelan banjir sehingga dapat memprediksi kerentanan banjir di daerah yang terkena dampak banjir.
Co-Authors Agustina Rachmawardani Arno, Giarno Bagus Primohadi Syahputra Hapsoro Agung Nugroho Hariyanto Inlim Rumahorbo Ricko Yudistira Saragih, Immanuel Jhonson Arizona Sastra K. Wijaya Suharni Suharni