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Abstract Topic: Big Data, Database System, Data Mining and Web Mining

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Classification of Seismic Signals by Evaluating Broadband Network Station in Sumatera Fore-ARC
Marzuki Sinambela1, Kerista Tarigan1, Syahrul Humaidi1, Marhaposan Situmorang1

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Corresponding Author
Kerista Tarigan

Institutions
1Department of Physics, FMIPA, Universitas Sumatera Utara, Jl. Bioteknologi No.1, Padang Bulan, Kec. Medan Baru, Medan, Sumatera Utara 20155, Indonesia

Abstract
Classification of seismic signal waveform is an essential component to realize the characteristics of the signal. The processing of the waveform signal is broadly used for the analysis of the real-time seismic signal. The numerous wavelet filters are developed by spectral synthesis using machine learning python to realize the signal characteristics. Our research aims to generate the performance of seismic signal and processing the waveform from Broadband Network Station by using Wavelet-Based on Machine Learning. In this case, we use Continuous Wavelet Transform (CWT) on Morlet to evaluate and classification the Phase in Tarutung earthquakes January 2019. CWT is also clearly to identify spectral amplitudes and frequency-energy from the component of signal seismic performed by Broadband Network in Indonesia. The characteristic of the digital broadband network in Sumatera Fore-Arc is variance. Our study tries to classification and evaluate the Broadband Seismic Network which deployed in Sumatera Region, Indonesia by using Power Spectral Density Probability Density Function (PSDPDF).

Keywords
Classification, Machine Learning, Morlet, Broadband Network, PSDPDF

Topic
Big Data, Database System, Data Mining and Web Mining

Link: https://ifory.id/abstract/pjWEGVJ8rkKg


Hotel Content-Based Recommendation System
Kristian Wahyudi, Johanes Latupapua, Ritchie Chandra, Abba Suganda Girsang

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Corresponding Author
Abba Suganda Girsang

Institutions
Bina Nusantara University

Abstract
Content based recommendation systems try to recommend items similar to those a given user has likely in the past, whereas systems designed according to the collaborative recommendation paradigm identify users whose preferences are similar to those of the given user and recommend items they have liked. The proposed recommendation system is discussing about Airbnb recommendations for a place in the city of Seattle. The selected process for the recommendation is calculating the rating of room types based on the environment. By calculating room types from several environments by combining two features namely room type and taken from the environment of the selected room type as well. The result of process and analysis will be provided into certain steps and images.

Keywords
recommendation, hotel, content

Topic
Big Data, Database System, Data Mining and Web Mining

Link: https://ifory.id/abstract/87nxdwaGbuV2


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