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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JOIV : International Journal on Informatics Visualization INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi J-Dinamika: Jurnal Pengabdian Kepada Masyarakat DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Bakti Masyarakat Indonesia TEPIAN International Conference on Industrial Revolution for Polytechnic Education Archive: Jurnal Pengabdian Kepada Masyarakat Seminar Nasional Ilmu Terapan Jurnal Informatika: Jurnal Pengembangan IT Cahaya Pengabdian
Kusuma, Dedy Hidayat
Politeknik Negeri Banyuwangi
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Journal : JOIV : International Journal on Informatics Visualization

 1 
Neural Network for Earthquake Prediction Based on Automatic Clustering in Indonesia Mohammad Nur Shodiq; Dedy Hidayat Kusuma; Mirza Ghulam Rifqi; Ali Ridho Barakbah; Tri Harsono
JOIV : International Journal on Informatics Visualization Vol 2, No 1 (2018)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1115.541 KB) | DOI: 10.30630/joiv.2.1.106

Abstract

A model of artificial neural networks (ANNs) is presented in this paper to predict aftershock during the next five days after an earthquake occurrence in selected cluster of Indonesia with magnitude equal or larger than given threshold. The data were obtained from Indonesian Agency for Meteorological, Climatological and Geophysics (BMKG) and United States Geological Survey’s (USGS). Six clusters was an optimal number of cluster base-on cluster analysis implementing Valley Tracing and Hill Climbing algorithm, while Hierarchical K-means was applied for datasets clustering. A quality evaluation was then conducted to measure the proposed model performance for two different thresholds. The experimental result shows that the model gave better performance for predicting an aftershock occurrence that equal or larger than 6 Richter’s scale magnitude.
Detection Object on Sea Surface to Avoid Collision with Post-Processed in Background Subtraction Image Alif Akbar Fitrawan; Mohammad Nur Shodiq; Dedy Hidayat Kusuma
JOIV : International Journal on Informatics Visualization Vol 3, No 2 (2019)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1110.18 KB) | DOI: 10.30630/joiv.3.2.207

Abstract

Data on shipping accident investigations from the National Transportation Safety Committee (NTSC) throughout 2010-2016 of fifty-four accident cases at sea, seventeen of which were accidents caused by collisions on ships in Indonesian waters, act to avoid a collision by detecting an object on the sea surface. Detection object is challenging because so many varieties object on the sea surface. Illumination variations with different seasons, periods, illumination intensity and direction affect the detection of objects directly. A rough sea is seen as a dynamic background of moving objects with size order and shape. All these factors make it difficult to object detection. Therefore, it is possible to conclude that background subtraction on sea surface problem remains open and a definitive robust solution is still missing. In this paper, we have applied a selection of background subtraction algorithms with post-processed to the problem. Experimental results with our dataset verify the high efficiency of our proposed method
Adaptive Neural Fuzzy Inference System and Automatic Clustering for Earthquake Prediction in Indonesia Mohammad Nur Shodiq; Dedy Hidayat Kusuma; Mirza Ghulam Rifqi; Ali Ridho Barakbah; Tri Harsono
JOIV : International Journal on Informatics Visualization Vol 3, No 1 (2019)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1452.798 KB) | DOI: 10.30630/joiv.3.1.204

Abstract

Earthquake is a type of natural disaster. The Indonesian archipelago located in the world's three mega plates; they are Australian plate, Eurasian plate, and Pacific plate. Therefore, it is possible for applied of earthquake risk of mitigation. One of them is to provide information about earthquake occurrences. This information used for spatiotemporal analysis of earthquakes. This paper presented Spatial Analysis of Magnitude Distribution for Earthquake Prediction using adaptive neural fuzzy inference system (ANFIS) based on automatic clustering in Indonesia. This system has three main sections: (1) Data preprocessing, (2) Automatic Clustering, (3) Adaptive Neural Fuzzy Inference System. For experimental study, earthquake data obtained Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG) and the United States Geological Survey’s (USGS), the year 2010-2017 in the location of Indonesia. Automatic clustering process produces The optimal number of cluster, that is 7 clusters. Each cluster will be analyzed based on earthquake distribution. Its calculate the b value of earthquake to get the seven seismicity indicators. Then, implementation for ANFIS uses 100 training epochs, Number of membership function (MFs) is 2, MFs type input is gaussian membership function (gaussmf). The ANFIS result showed that the system can predict the non-occurrence of aftershocks with the average performance of 70%.
Co-Authors Ali Ridho Barakbah Alif Akbar Fitrawan Annisa Rani Maulida Carenza Al Kharraz Devit Suwardiyanto Dianni Yusuf Eka Mistiko Rini Endi Sailul Haq Herman Yuliandoko, Herman I Putu Sudhyana Mecha Indah Kurnia Fitriani Lailatus Saadah Lilik Sumaryanti Lukman Hakim Lutfi Hakim Mirza Ghulam Rifqi Mirza Ghulam Rifqi Mistiko Rini, Eka Moh Nur Shodiq Moh. Nur Shodiq Moh. Nur Shodiq, Moh. Nur Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq, Mohammad Nur Mohammad Shodiq Muhamad Fuad Al Haris Muhammad Al Haris Muhammad Fuad Alharis Muhammad Najibulloh Muzaki Nuraini Lusi Pamuji, Dian Ridlo Rosmala Widijastuti Sepyan Purnama Kristanto Tovia Oktalita Sari Tri Harsono