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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) BERKALA FISIKA SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Jurnal Penelitian dan Pengembangan Pendidikan YOUNGSTER PHYSICS JOURNAL Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Geoplanning : Journal of Geomatics and Planning Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Register: Jurnal Ilmiah Teknologi Sistem Informasi JOURNAL ONLINE OF PHYSICS Jurnal Penelitian Pendidikan IPA (JPPIPA) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control IRJE (Indonesian Research Journal in Education) Journal of Physics and Its Applications Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL METEOROLOGI DAN GEOFISIKA Journal of Electronics, Electromedical Engineering, and Medical Informatics Indonesian Journal of Electrical Engineering and Computer Science Jurnal Aisyah : Jurnal Ilmu Kesehatan Journal of Social Research TAKSONOMI Jurnal Ekonomi, Teknologi dan Bisnis Journal of Emerging Science and Engineering Jurnal INFOTEL Sainteknol : Jurnal Sains dan Teknologi
Rahmat Gernowo
Department Of Physics, Faculty Of Science And Mathematics, Diponegoro University, Semarang
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Journal : YOUNGSTER PHYSICS JOURNAL

 1 
EVALUASI MODEL JARINGAN SYARAF TIRUAN METODE BACKPROPAGATION UNTUK PREDIKSI IKLIM EKSTRIM DENGAN KORELASI CURAH HUJAN DAN TINGGI MUKA LAUT DI SEMARANG Siti Yuniar Pangestu; Rahmat Gernowo
Youngster Physics Journal Vol 4, No 1 (2015): Youngster Physics Journal Januari 2015
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Global warming is an event average temperature rise of the atmosphere, ocean, and land. Atmosphere temperature changes cause the physical conditions of the atmosphere becomes unstable, causing anomalies weather parameters that cause climate change. The impact of climate changes is increasing frequency of natural disasters or extreme weather, changes in rainfall patterns, and rising sea level rise. To minimize disaster prediction is carried out by making modeling with artificial neural network method, algorithm of backpropagation models.The research was conducted in Semarang, using data from rainfall, precipitation, temperature, cloud cover, and sea level rise in 2002 until 2012.Artificial neural network modeling was used Matlab R2010a. Network training by using one unit of input layer, two hidden layer units, and one unit of output layer. The first hidden layer with 10 neurons and the second hidden layer used 5 neurons.The best results on the training and testing of the network by using the parameter learning rate 0.3 and a momentum 0.6. The results obtained in the training get a percentage value of correlation is 79.0% and in the testing process to get the percentage correlation is 77.5%. Keywords: Artifical Neural Network, Backpropagation, extreme climate, rainfall, sea level rise
INTERPRETASI STRUKTUR BAWAH PERMUKAAN DATA GAYABERAT MENGGUNAKAN ALGORITMA JARINGAN SARAF TIRUAN STUDI KASUS DAERAH PANAS BUMI UNGARAN, JAWA TENGAH Ratih Rundri Utami; Agus Setyawan; Rahmat Gernowo
Youngster Physics Journal Vol 5, No 4 (2016): Youngster Physics Journal Oktober 2016
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Artificial neural networks have been used in an application of geophysical such as seismic, electromagnetic, restivity, and gravity. In this study, artificial neural network system used is the method of propagation of gravity to produce anomalies corresponding to the desired anomalies on the geothermal area of Mount Ungaran, Central Java. In the training process to produce the best weight with 4 hidden layer with a correlation coefficient of 0.99 and the testing process using the results of the best training with a correlation coefficient of 0.97 and a yield value that resembles Bouguer anomaly in the research area., so it can be seen under the surface of the structure with the results of the best network where there is a high density value of 2.70 to 2.80 g/cm3 in lava basalt as geothermal systems Mount Ungaran. Density 2.40 to 2.80 g/cm3 Low contained in the surface area of Mount Ungaran with the majority of sedimentary rocks of andesitic pyroclastic products of Mount Ungaran Young.
ANALISA PENYIMPANGAN IKLIM DARI FENOMENA ENSO MENGGUNAKAN MODEL KORELASI STUDI KASUS BOGOR Annisa Luthfianti Panular; Rahmat Gernowo
Youngster Physics Journal Vol 5, No 4 (2016): Youngster Physics Journal Oktober 2016
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Cases of climate anomalous in Indonesia, many have influences on the climate in several areas such as the dry or rainy season that does not occur periodically or the precipitation decrease that does not normal and deviated from ought. This study aimed to analyze the climate anomalous and correlation patterns of ENSO towards rainfall variability in Darmaga Bogor, then compared the results with rainfall of Tanjung Priok Jakarta. Both places have minimum ENSO influence because they being away from the center of ENSO events that is in the Pacific Ocean and located in the west Pacific. Climate anomalous due to ENSO (El Niño Southern Oscillation) in the Indonesian archipelago can occur if in the Pacific El Niño is more decreasing rainfalls or La Niña which further adds to the amount of rainfall.This research using a linear correlation analysis model and contour of the sea surface temperature (SST) from GrADS software. The data used are Index Nino 3.4 anomaly, IOD (Indian Ocean Dipole) anomaly, precipitation and SST anomaly data. Data is processed from January 2004 - December 2013 (10 years). Correlation of index Nino 3.4 years 2004-2013 showed a lot more going to negative index that means more towards the La Niña in Pacific Ocean. The results of correlation analysis in August in Darmaga between ENSO - IOD with rainfall that more affects the rainfall pattern is a ENSO factor either La Niña nor El Niño and also it followed by west monsoon wind pattern, whereas at Tanjung Priok that more affects the rainfall pattern is monsoonal rainfall patterns. Upon the precipitation in Darmaga generally has high enough intensity and some graph pattern follows monsoonal rainfall patterns whereas Tanjung Priok generally has low intensity and the graph pattern follows the type of monsoonal rainfall patterns. SST contour in West Java is on average warmed up that caused that region more easily condensed the clouds and atmospheric pressure at the waters becomes high.
ANALISIS KORELASI CITRA DATA PRIMER DENGAN DATA SEKUNDER MENGGUNAKAN CITRA GRID ANALYSIS AND DISPLAY SYSTEM (GrADS Wahyu Jatmiko; Rahmat Gernowo
Youngster Physics Journal Vol 3, No 1 (2014): Youngster Physics Journal Januari 2014
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Indonesia has 13 (thirteen) the threat of catastrophic earthquakes, tsunamis, floods, landslides, volcanic eruptions, extreme waves and abrasion, extreme weather, drought, forest fires and land, buildings and residential fires, epidemics and disease outbreaks, failed technology, and social conflict. Research related to hydrometeorological predictable by doing a variety of approaches, one using remote sensing methods provided by the World Meteorological Organization (WMO) with the advantages of data is not affected by the location of the location such as the presence of a cliff, lake, or mountain.In the study image correlation analysis of primary data with secondary data using imagery Grid Analysis And Display System (Grads) have been analyzed the correlation between the image of the primary data with secondary data using Grid software image Analisys And Display System. The data used are rainfall, air temperature, and humidity, all of the data is the data on average monthly. Primary data were obtained from Badan Meteorologi, Klimatologi dan Geofisika (BMKG) Semarang and secondary data obtained by downloading from the National Oceanic And Atmospheric Administration (NOAA) website.The value of the correlation between the primary data with secondary data for rainfall data indicate a strong relationship , occurs when the amount of rainfall maximum correlation value is 0,67 and the value of correlation in the event the minimum rainfall is 0,79 . On air temperature data the value of the correlation time of maximum rainfall is 0.69 and the value of correlation in the event of rainfall minimum is -0,37 . Correlation values for air humidity data at the time of maximum precipitation is 0,01 and the magnitude of the correlation value at the time the minimum rainfall is 0,95 .Keywords : GrADS , disaster, correlation, extreme weather, dryness
Analisis turbulensi pada pesawat Etihad Airways EY-474 tanggal 4 Mei 2016 dengan metode Weather Research and Forecasting Nuriyana Muthia Sani; Rahmat Gernowo
Youngster Physics Journal Vol 7, No 1 (2018): Youngster Physics Journal Januari 2018
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

The micro weather analysis for turbulence incident of EY-474 Eithad Airways aircraft on May 4, 2016 involving injured passengers, was numerically simulated using the Weather Research and Forecasting (WRF) numerical model software. The input data is obtained from the predicted Final Analysis (FNL) that can be downloaded at the site. Elements obtained from WRF output include Richardson Number Index (Ri) and Vertical Wind Shear (VWS). Flight data to determine the time and location of the turbulence events obtained from the site address. The results obtained events around the waters of Palembang and Bangka Island. And supported by Himawari 8 satellite image data infrared (IR) canal and visible canal (VIS) and Kochi University infrared (IR) satellite to see the condition of the clouds. The results of the Kochi University satellite data show there are no convective clouds. However, on the Himawari 8 satellite shows there are clouds with peak temperatures cool enough and showing a central cloud. Simulation results show turbulence with strong intensity explaining turbulence incident on May 4, 2016 in Palembang and Bangka Island waters. Keywords: himawari, turbulence, WRF
ANALISIS PERUBAHAN IKLIM BERBAGAI VARIABILITAS CURAH HUJAN DAN EMISI GAS METANA (CH4) DENGAN METODE GRID ANALYSIS AND DISPLAY SYSTEM (GrADS) DI KABUPATEN SEMARANG Ismi Dian Kusumawardhani; Rahmat Gernowo
Youngster Physics Journal Vol 4, No 1 (2015): Youngster Physics Journal Januari 2015
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

Global climate change as the implications of global warming caused by greenhouse gas increases from time to time. Methane (CH4) is a greenhouse gas that causes the greenhouse effect and has the effect of 20-30 times greater than carbon dioxide. The rate of CH4 emissions to the atmosphere is the fastest among other greenhouse gases.The research was conducted by analyzing climate change using the data of precipitation, air temperature, and methane emissions. Data of Ungaran - kabupaten Semarang precipitation obtained from Badan Meteorologi, Klimatologi dan Geofisika (BMKG) Climatological Station Semarang. Globally available data of precipitation and air temperature, that is downloaded from the website National Oceanic and Atmospheric Administration (NOAA). While the emission data of methane (CH4) is obtained from Badan Lingkungan Hidup (BLH) Central Java with data that covers an area of Central Java. To determine the existence of climate change in the research area of data analysis is carried precipitation and air temperature during the last 30 years. The method used is the method of Grid Analysis and Display System (GrADS) that can be used for processing and visualizing the earth science data.The results of this study, the increase in precipitation and air temperature every year in a period of 30 years in kabupaten Semarang. The average amount of precipitation every year is obtained by 1579.86 mm. Precipitation in Central Java region shown by the pattern of monsoon rainfall. The average maximum precipitation in January, while the minimum in August. The average air temperature increase annually by 0.014oC or 0.051% every year. Similarly, the amount of methane emissions (CH4) in all parts of human activity in the region of Central Java has increased every year. The average increase of CH4 emission obtained annually by 14.99 Gg or 1.36%. On average generated methane emissions from human activities annually by 1104.54 Gg.Keywords: Global warming, climate change, GrADS, precipitation, methane emissions (CH4)
PEMODELAN BAWAH PERMUKAAN DAERAH PANASBUMI KALIULO BERDASARKAN DATA RESISTIVITAS KONFIGURASI SCHLUMBERGER DENGAN ALGORITMA JARINGAN SYARAF TIRUAN-BACKPROPAGATION Frysca Putti Muviana; Agus Setyawan; Rahmat Gernowo
Youngster Physics Journal Vol 5, No 4 (2016): Youngster Physics Journal Oktober 2016
Publisher : Jurusan Fisika, Fakultas Sains dan Matematika, Universitas Diponegoro

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Abstract

This research used secondary data configuration Schlumberger geoelectric method in the area of geothermal manifestations Kaliulo Mount Ungaran to implement the use of artificial neural network algorithm in geophysical this case to obtain the actual value of the thickness and resistivity. In this artificial neural networks do two processes, namely the training and testing, the training using synthetic data and on testing using field data Then in training the neural network produced the best architectural which is used train resilient propagation (train rp) with three hidden layers with each neuron in the hidden layer consist of 300 neuron, this architecture will be used in testing. The output of the test data is value of the thickness and true resistivity which can be modeled. Result modeling of data processing from ANN is almost the same with IPI2WIN, MSE value obtained is equal to 0.10519 and 0.088304 respectively on the thickness and resistivity actually. The result of 3D model shows the lower part of the earth's subsurface its rock consists as following: topsoil, clay, volcanic breccias, tuff and limestone. 
Co-Authors Adi Wibowo Adiyono, Soni Agus Setyawan Agus Sutejo Agusta Praba Ristadi Pinem Ahmad Lubis Ghozali Aldi Setiawan, Aldi Andryani, Ria Annisa Luthfianti Panular Ardima, Muhammad Basyier Arfriandi, Arief Ari Bawono Putranto Aria Hendrawan, Aria Aries Dwi Indriyanti, Aries Dwi Aris Sugiharto Atik Zilziana Muflihati Noor Bayong Tjasyono H. Kasih Bayu Surarso Beta Noranita Budi Prasetiyo, Budi Budi Warsito Budi Warsito Catur Edi Widodo Cholil, Saifur Rohman Christine Dewi D Febrianty Dafiz Adi Nugroho Dedy Kurniadi Edi Surya Negara Eko Nur Hidayat Eko Sediyono F M Arif Faliha Muthmainah Fauzan Ishlakhuddin Frysca Putti Muviana Ghufron Ghufron Gumay, Naretha Kawadha Pasemah Hengki Hengki Heri Mulyanti Hidayat, Agung Rahmad I. Istadi Ikhthison Mekongga Iryanto Iryanto Ismi Dian Kusumawardhani Isnain Gunadi Istadi I’tishom Al Khoiry Khusnah, Miftakhul Koesuma, Sorja Kuresih, Kuresih Kurnia Adi Cahyanto Kusworo Adi M. Solehuddin Mahrus Ali Michael Andreas Purwoadi Moh Ali Fikri Muchammad A Rofik Mulyani, Esti Munengsih Sari Bunga Munji Hanafi Nabiel Putra Adam, Nabiel Putra Novita Mariana Nuriyana Muthia Sani Nuriyana Muthia Sani Nursamsiah Nursamsiah Oky Dwi Nurhayati Prayitno R. Rizal Isnanto Radini Sinta, Radini Ratih Rundri Utami Rosyalia, Syofi Sakhina, Friska Ayu Setiabudi, Nur Andi Shahmirul Hafizullah Imanuddin Siti Yuniar Pangestu Slamet, Vincencius Gunawan Suryono Suryono Syibli, Mohammad Tri Mulyono Triyono, Liliek Victor Gayuh Utomo Wahyu Jatmiko Wahyul Amien Syafei Wicaksana, Hilman Singgih Widagdo, Krisan Aprian Widiyatmoko, Carolus Borromeus Wulandari, Rosita Ayu Yenny Ernitawati Zaenal Arifin