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All Journal JURIKOM (Jurnal Riset Komputer) Jurnal Computer Science and Information Technology (CoSciTech)
Muhammad Shodiq
Universitas Muhammadiyah, Lamongan
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Grey Forecasting Model Untuk Peramalan Harga Ikan Budidaya Muhammad Shodiq; Bagus Dwi Saputra
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5120

Abstract

Price is an important factor to consider because it determines the profit or loss from selling a product. The difficulty of controlling the volatility of fish prices is related to many factors, including stock availability, natural factors, and the level of demand. One way to solve the problem of fish price volatility is to predict fish prices in the future. The purpose of this study is to apply the gray forecasting method to forecasting fish prices, especially in the aquaculture industry. Gray forecasting is a method for creating forecasting models with a small amount of data that provides accurate forecasts. This study uses daily data on prices of Tilapia fish for the period of June 2022 for analysis of gray forecasting calculations. The results show that gray forecasting provides very accurate predictions with aa mafe value of 2.39% of the price of Tilapia fish
Smart Technology of CO2 Monitoring as Prevention of Acute Respiratory Infection Disease Using Artificial Intelligence Algorithm Muhammad Shodiq; Agus Priyono; M. Cahyo Kriswantoro3
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.7709

Abstract

Air pollution is a serious environmental problem that can affect human health because it contains toxic gases, one of which is carbon dioxide (CO2). This toxic gas can cause Acute Respiratory Infection (ARI). ARI is an acute infection of the respiratory tract that can cause death. One effort to prevent ARI is to monitor CO2 gas as a trigger for ARI. This study develops intelligent technology for monitoring CO2 concentration using a rule-based artificial intelligence algorithm by utilizing Internet of Things technology integrated with telegrams to provide warnings. Rule-based systems are part of artificial intelligence that have advantages and limitations that need to be considered before deciding whether it is the right technique to use in solving existing problems. This study uses daily data taken by CO2 gas sensors from 07.00 - 16.15 WIB with a data collection range of 15 minutes with a total of 38 data samples taken. The results of the study show that this rule-based algorithm is able to classify CO2 concentrations according to the rules that have been made. In addition, from the data taken, 42% are in the safe category, 50% are in the alert category and 8% are in the danger category, each of which has an effect on health. The system that was built can also send danger notifications via telegram
Co-Authors Agus Priyono Bagus Dwi Saputra M. Cahyo Kriswantoro