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APLIKASI PERAMALAN KURS BITCOIN-RUPIAH DENGAN MENGGUNAKAN METODE DOUBLE EXPONENTIAL SMOOTHING Hizamrul jaen; Eva Darnila; Muhammad Fikry
TECHSI - Jurnal Teknik Informatika Vol 11, No 1 (2019)
Publisher : Teknik Informatika Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/techsi.v11i1.1295

Abstract

Perkembangan teknologi meghadirkan banyak inovasi. Salah satu inovasi teknologi adalah berkembangnya Cryptocurrency atau mata uang Kripto. Salah satu jenis Cryptocurrency adalah Bitcoin. Karena beberapa faktor, Bitcoin menjadi terkenal di seluruh dunia, sehingga sering diperdagangkan layaknya perdagangan mata uang pada umumya. Namun karena belum adanya regulasi dari pemerintah, membuat harga bitcoin menjadi tidak terkendali sehingga sering terjadi fluktuasi besar besaran. Metode Double Exponential Smoothing adalah sebuah metode yang sering diguakan dalam kebutuhan Forecastng. Metode ini memanfaatka  data historis pada priode tertentu dalam proses prediksi. Untuk metode ini akan diuji dalam sebuah rancangan dan pengembangan system berbasis web, dimana sampel data akan di kalkulasikan dengan Metode Double Exponential Smoothing. Penelitian ini menguji sekitar 5 data setiap harinya selama 10 hari, dengan parameter a (alpha) 0.4035. menghasilkan tingkat akurasi senilai 70%. Hasil peramalan itu akan di sajikan dalam bentuk tabel dan grafik. Key Words : Bitcoin, Forecasting, Double Exponential Smoothing, Kurs, Cryptocurrency
IMPLEMENTATION OF DOUBLE EXPONENTIAL SMOOTHING METHOD IN WORLD GOLD PRICE PREDICTION APPLICATION Hizamrul Jaen; Cindy Rahayu
Bulletin of Engineering Science, Technology and Industry Vol. 1 No. 1 (2023): March
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v1i1.1

Abstract

The constantly changing price of gold in the world can worry gold investors, so accurate and fast data is needed to respond to these changes. The role of technology and appropriate procedures is crucial in addressing these challenges. This research will discuss the Prediction of World Gold Prices as a Support for Gold Stock Investment Decisions Utilizing Time-Varying Prediction Algorithms such as Double Exponential Smoothing, which utilizes historical data as a reference in the prediction calculation. The historical data sample used in this study ranges from the beginning of September 2019 to the end of October 2019. From this research, it is expected to test the Double Exponential Smoothing method in predicting future world gold prices.
INFORMATION SYSTEM FOR DISASTER MANAGEMENT DATA PROCESSING AT THE REGIONAL DISASTER MANAGEMENT AGENCY (BPBD) OF NORTH ACEH REGENCY Hizamrul Jaen; Irham Fatriyandas Rufdo; Muhammad Irsyad Thoyib
Bulletin of Engineering Science, Technology and Industry Vol. 1 No. 2 (2023): June
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v1i2.7

Abstract

This research aims to address the pressing need for an efficient and comprehensive information system application for disaster management. Natural disasters can have devastating impacts on communities, and effective disaster management is crucial to minimize losses and ensure a swift and well-coordinated response. To meet this objective, the study develops a website-based application that manages critical disaster-related data, such as information on disaster victims, aid distribution, handling processes, and visual documentation (photos and videos) of the disaster. The design of the application incorporates three essential methodologies: Data Flow Diagrams (DFD), Entity-Relationship Diagrams (ERD), and Context Diagram. These methodologies ensure a clear and systematic representation of data flow, database structures, and system boundaries. By utilizing these tools, the researchers ensure the application's efficiency, effectiveness, and user-friendliness in managing disaster-related information. The research employs a mixed-method approach, combining quantitative and qualitative data collection techniques. Surveys, interviews, and observations are conducted to assess the application's usability, effectiveness, and impact on disaster management. Quantitative data is analyzed using statistical tools, while qualitative data is thematically analyzed to gain deeper insights into user experiences and perceptions.
APPLICATION OF TRIPLE EXPONENTIAL SMOOTHING METHOD FOR PREDICTING THE PRICE MOVEMENT OF CRYPTOCURRENCY ETHEREUM Maurizio Zanardi; Hizamrul Jaen
Bulletin of Engineering Science, Technology and Industry Vol. 1 No. 2 (2023): June
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v1i2.8

Abstract

An innovation that was sparked is an alternative currency to replace conventional currency, namely digital currency that is secured using a Cryptographic method called Cryptocurrency. However, Cryptocurrency prices cannot be controlled, causing massive fluctuations. Cryptocurrency price changes are very stable due to several factors such as speculation from users and the nature of the follow-up from new to one of the causes. The cause of this bandwagon is due to extreme price increases in a short time, even within a day the price of Crypto can experience a difference of millions of rupiah for each increase and decrease. To answer this question, we need a software that can predict the Rupiah exchange rate. The Mean Absolute Percentage Error (MAPE) for the Triple Exponential Smoothing implementation is 3.7249%. This method was utilized to predict the Rupiah exchange rate for Cryptocurrency, addressing the issue of price fluctuations in the Crypto market. Historical data, along with the specified parameters of 0.40 for Xt and S't, and 0.60 for Beta, were employed to generate accurate predictions. The process involved calculating first to third smoothing, determining Constants, Slopes, and Parabolics, and finally producing the Forecasting results. The MAPE value of 3.7249% indicates that the Triple Exponential Smoothing method exhibited relatively accurate predictions with a small margin of error when applied to a dataset of 50 data samples, ranging from May 2022 to June 2022.