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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) MEDIA KOMUNIKASI TEKNIK SIPIL Jurnal Sains dan Teknologi Perfecting a Video Game with Game Metrics Jurnal Informatika Jurnal Online Mahasiswa (JOM) Bidang Teknik dan Sains Proceedings ACES (Annual Civil Engineering Seminar) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Teknik Sipil Jurnal Teknik International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Seminar Nasional Teknologi Informasi Komunikasi dan Industri Dinamisia: Jurnal Pengabdian Kepada Masyarakat SIKLUS: Jurnal Teknik Sipil Jurnal Rekayasa Sipil ABDIMAS: Jurnal Pengabdian Masyarakat JURNAL SAINTIS Jurnal Infrastruktur Jurnal Ilmiah Telsinas Elektro, Sipil dan Teknik Informasi Journal of Infrastructure and Civil Engineering SAINSTEK
Reni Suryanita
Department Of Civil Engineering, Engineering Faculty, Universitas Riau, Pekanbaru, Indonesia
Arts Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Transportation Other

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Journal : Perfecting a Video Game with Game Metrics

 1 
Intelligent Monitoring System on Prediction of Building Damage Index using Neural-Network Mardiyono Mardiyono; Reni Suryanita; Azlan Adnan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 1: March 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i1.773

Abstract

An earthquake potentially destroys a tall building. The building damage can be indexed by FEMA into three categories namely immediate occupancy (IO), life safety (LS), and collapse prevention (CP). To determine the damage index, the building model has been simulated into structure analysis software. Acceleration data has been analyzed using non linear method in structure analysis program. The earthquake load is time history at surface, PGA=0105g. This work proposes an intelligent monitoring system utilizing artificial neural network to predict the building damage index. The system also provides an alert system and notification to inform the status of the damage. Data learning is trained on ANN utilizing feed forward and back propagation algorithm. The alert system is designed to be able to activate the alarm sound, view the alert bar or text, and send notification via email to the security or management. The system is tested using sample data represented in three conditions involving IO, LS, and CP. The results show that the proposed intelligent monitoring system could provide prediction of up to 92% rate of accuracy and activate the alert. Implementation of the system in building monitoring would allow for rapid, intelligent and accurate prediction of the building damage index due to earthquake.
Intelligent Bridge Seismic Monitoring System Based on Neuro Genetic Hybrid Reni Suryanita; Mardiyono Mardiyono; Azlan Adnan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.6006

Abstract

The natural disaster and design mistake can damage the bridge structure. The damage caused a severe safety problem to human. The study aims to develop the intelligent system for bridge health monitoring due to earthquake load. The Genetic Algorithm method in Neuro-Genetic hybrid has applied to optimize the acceptable Neural Network weight. The acceleration, displacement and time history of the bridge structural responses are used as the input, while the output is the damage level of the bridge. The system displays the alert warning of decks based on result prediction of Neural Network analysis. The best-predicted rate for the training, testing and validation process is 0.986, 0.99, and 0.975 respectively. The result shows the damage level prediction is agreeable to the damage actual values. Therefore, this method in the bridge monitoring system can help the bridge authorities to predict the health condition of the bridge rapidly at any given time. 
Co-Authors ', Ismeddiyanto ', smeddiyanto Abrar Rifqi Pratama Afisha, Elly Ahmad Hamidi Ahmad Obi Narman Ahmad Riadi Alex Kurniawandy Andi Wijaya Anggi Agusstiawan Appriliya Destiyani Ardiansyah, M. Syukri Ari Sandhyavitri Ari Vera Indra Ariadi, Koko Putra Arif Rahman Azlan Adnan Azlan Adnan Benny Hamdi Rhoma Beny Setiawan Brian Priadana Mulrony Dandio Ahmad Fansuri Darmawan, Wan Fikri Debi Setiawan Debi Setiawan, Debi Dede Eldi Kurniawan Dimas Arief Wicaksono Djauhari, Zulfikar Dwiqhee Abdul Ghani Dyna Aulia R Efendi, M. Rizal Dika Eki Syahyudi Elsa Aprilia Andoni Elsyani Eka Putri Elva Nidya Sari Enno Yuniarto Erizal ' Fadrizal Lubis Firzal, Yohannes Florisa Florisa Florisa Florisa Geovani Meiwanda Hanantatur Adeswastoto Harnedi Maizir Hendra Fernando Hendra Jingga, Hendra Heru Nurcahyo Heru Satiadi, Heru Heru Setiadi Ilham Akbar Imam Mustafa Iqbal Maulia Iskandar Romey Sitompul Iskandar Romey Sitompul Ismail Rahmadtulloh Ismed Diyanto Ismeddiyanto Ismeddiyanto Ismeddiyanto Ismeddiyanto Ismeddyanto Ismeddiyanto, Ismeddiyanto Ismeddiyanto, Ismeddiyanto Ismeddyanto Ismeddyanto Ismediyanto Ismediyanto Joni, Mustika Kamaldi, Alfian Kampati, Tri Budi Maharani Miranda Mamoru Kikumoto Mardiyono Mardiyono Mardiyono Mardiyono Mardiyono, Mardiyono Maya Rumiati Monita Olivia Muhamad Zulfakar Muhammad Gala Garcya Mustika Joni Nila Kamelia Nopember Toni Nopember Toni, Nopember Puri Awanda Cantikawati Putri, Ade Septiani Rahmadi Rahmadi Rahmiasari Rahmiasari Raja Parulian Purba, Raja Parulian Rama Dwi Aryandi Ramalia Noratama Putri Ramalia Noratama Putri Rendy Wijaya Revo Sedrian Putra Rexi Putra Rian Fajri Ramadanas Ricky Andriano Ridwan Ridwan Ridwan Ridwan Rizki Zulapriansyah Rofika Ratna Ardyansah Roma Dearni Satria Makahani Siregar, Andi Saputra Soewignjo Agus Nugroho Sondra Raharja Sri Agustin Sri Agustin Sri Fatma Reza Sri Fatma Reza, Sri Fatma Sri Indarti Suyanto Suyanto Syahnandito Syahyudi, Eki Syamsul Fikri Syauqi, Muhammad Tia Aurelia Tiara Monica Vindi Trisatria Vindy Salim Vomania, Vomania Wahyu Rahmadhan, Wahyu Wicaksono, Adhithiya Widianto, Devit Yenita Roza Yon Subagiono Yosi Alwinda Zulfikar Djauhari Zulfikar Djauhari Zulfikar Djauhari Zulfikar Djauhari Zulkarnain Zulkarnain Zunwanis Zunwanis