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All Journal J-Sil (Jurnal Teknik Sipil dan Lingkungan) Journal of Informatics, Information System, Software Engineering and Applications (INISTA)
Guruh Samodra
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Engineering Transportation

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Physical Vulnerability Modeling Based On Flood Inundation Model and Image Mining Maulana Ibrahim Rau; Guruh Samodra; Hendra Pachri; Edy Irwansyah; Muhammad Subair
Jurnal Teknik Sipil dan Lingkungan Vol. 1 No. 3: Desember 2016
Publisher : Departemen Teknik Sipil dan Lingkungan, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (12.81 KB) | DOI: 10.29244/jsil.1.3.137-146

Abstract

Flash flood disaster occurred within the City of Garut, West Java, Indonesia, on 20th September 2016, which caused many casualties and damages. Flood model could be performed to model the already-occurring disaster, as well as to depict future events that may occur to overcome any potential disasters, where the inundation flood model depicted the element at risk. In order to assist the analysis for the damages occurred, image mining could be used as part of the approach, where online media was utilized as well. The image mining resulted information about building damages caused by the flood. Afterwards, the physical vulnerability (buildings/residents) model could be further performed. Finally, the relationship between vulnerability and the flood inundation were portrayed. The resulted physical vulnerability model showed that larger height of the flood water caused higher degree of loss of the building, in which portrayed the need for total rebuild of houses as well. Considering available open source data and fast data acquisition, the approach showed such efficient approaches, where the results could be used in order to establish recommendation for building reinforcement, spatial planning, or protection wall in flood prone areas within the future time.
Akuisisi Data Prediksi Curah Hujan Secara Periodik Menggunakan Apache Airflow Erwin Eko Wahyudi; Muhammad Auzan; Andi Dharmawan; Danang Eko Nuryanto; Nanang Susyanto; Guruh Samodra; Danang Sri Hadmoko
Journal of INISTA Vol 4 No 2 (2022): Mei 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v4i2.574

Abstract

Akuisisi data, bertujuan untuk mengambil data awal, merupakan salah satu tahapan dalam metodologi penambangan data. Data awal akan diproses menjadi data akhir yang digunakan untuk proses pemodelan, seperti pembuatan model untuk memprediksi potensi terjadinya tanah longsor. Data prediksi curah hujan yang disediakan oleh Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) dapat digunakan untuk pemodelan tersebut. Data akan disimpan di komputer lokal dengan menggunakan alat atau aplikasi otomasi yang bernama Apache Airflow. Proses akuisisi data dari server BMKG ke komputer lokal dijalankan secara otomatis dalam dua kali sehari, yaitu pada pukul 00.00 dan 12.00. Terdapat dua task yang dibuat di Directed Acyclic Graph (DAG) untuk proses ini, yaitu task pertama sebagai sensor ketersediaan data dan task kedua yang melakukan proses utama. Status dari DAG pada Apache Airflow juga dapat diketahui secara cepat, misalnya status telah berhasil, gagal, atau sedang berjalan. Apache Airflow juga menyediakan log yang dapat diakses untuk mengetahui alasan kegagalan suatu task. Hasil dari penelitian ini adalah terdapat pipeline pada aplikasi otomasi Apache Airflow untuk membantu proses akuisisi data secara periodik.
Co-Authors Andi Dharmawan Danang Eko Nuryanto Danang Sri Hadmoko Edy Irwansyah Erwin Eko Wahyudi Hendra Pachri Maulana Ibrahim Rau Muhammad Auzan Muhammad Subair Nanang Susyanto