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Journal : Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)

Comparison of Exponentially Weighted Moving Average and Triple Exponential Smoothing Methods for Cryptocurrency Price Forecasting sukma rizki; Zarayunizar Zarayunizar; Said Fadlan Anshari
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

Cryptocurrencies have rapidly become a prominent part of today's information landscape. Bitcoin (BTC), one of the first cryptocurrencies, was introduced by Satoshi Nakamoto, a pseudonym whose true identity remains unknown. Nakamoto is credited with creating the blockchain system that underpins Bitcoin. As technology has advanced, cryptocurrencies have evolved into digital currencies that can be used as a medium of exchange. This has garnered significant attention from investors, particularly due to the substantial fluctuations in cryptocurrency values over time. Therefore, choosing the right method for making investment decisions is crucial. This research compares two leading methods for cryptocurrency price forecasting: Exponentially Weighted Moving Average (EWMA) and Triple Exponential Smoothing (TES). Each method has its own strengths and weaknesses in forecasting. In this study, EWMA achieved an average MAPE score of 54% and an MSE of 1818, while TES recorded an average MAPE of 45% and an MSE of 11408. The results indicate that TES outperforms EWMA by a margin of approximately 10%. To assess the methods' effectiveness, evaluation metrics were applied, categorizing performance as excellent, good, feasible, or not feasible.
Contagion Analysis of Plantation Commodity Producing Regions in Aceh Province Using Bayesian Inference Juliawati; Mukti Qamal; Said Fadlan Anshari
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

The commodity-producing region is one of the plantation sectors with significant potential for economic growth in Aceh Province. The spread level between commodities owned by regions within the network is called “contagion,” which means that one commodity will influence a region, leading to a greater focus on that commodity within the network, and a region will influence other regions. With the diversity of commodities across various areas, a comprehensive analysis and visualization of the network formed among commodity producing regions are conducted using a Social Network Analysis (SNA) approach. Thus, Bayesian inference can reveal the network of each region that has relationships among the variables used to form a graph with the desired representation. This network analysis result can provide an overview of Aceh Province's plantation data through the network graph visualization among commodity-producing regions and the network graph of commodity production levels by region. Keywords: Aceh; Contagion Analysis; Social Network Analysis
Full Automation and Control System Based on IoT in a Greenhouse (Case Study: Faculty of Agriculture, Malikussaleh University M Ishlah Buana Angkasa; Rizal Tjut Adek; Said Fadlan Anshari
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This study aims to develop a full automation and control system based on the Internet of Things (IoT), implemented in a greenhouse to support real-time monitoring of temperature, soil moisture, and water levels in the tank. The system is designed using the ESP32-WROOM microcontroller as the core for data communication with various sensors, including the DHT22 sensor for air temperature and humidity, a soil moisture sensor for soil moisture, and a JSN-SR04T sensor for water level. The developed system connects to Firebase as a cloud data platform, enabling remote monitoring via a specially designed mobile application. Testing shows that the system works efficiently in supporting automated plant growth, reducing manual intervention, and increasing productivity. This system allows students and faculty in the Faculty of Agriculture at Malikussaleh University to more easily conduct research and teaching activities related to modern agricultural technology.