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All Journal Dinamik Proceeding SENDI_U JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Technologia: Jurnal Ilmiah JINAV: Journal of Information and Visualization Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal Ilmiah Ekonomika & Sains Tematik
Taufiq Dwi Cahyono
Jurusan Teknik Elektro, Fakultas Teknik, Universitas Semarang
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Library & Information Science Mathematics Social Sciences Other

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Journal : JINAV: Journal of Information and Visualization

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Forecasting Analysis of Fishermen’s Productivity Data Using Single Exponential Smoothing Taufiq Dwi Cahyono; Heri Purwanto; Iwan Adhicandra; Kraugusteeliana Kraugusteeliana; Edy Winarno
JINAV: Journal of Information and Visualization Vol. 3 No. 2 (2022)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav1487

Abstract

One of the reasons why it is vital to forecast fisher production data in coastal regions is to increase fish resource management efficiency. By calculating the number of fishing boats, the amount of fish that must be caught, and the amount of raw materials required for fish processing based on the anticipated amount of fishermen's production in the following period, decision-makers can determine the amount of fish that must be caught and the amount of raw materials required for fish processing. So that the objective of the research is to forecast fishermen's production data using the Single Exponential Smoothing method, this method is effectively used to perform forecasting of time series data with short period data intervals to produce forecasts for the next period, and it can measure the rate of change of fishermen's production data each period. The results of forecasting data on fishermen's production utilizing time series data intervals from October 2022 to January 2023 to make forecasts for February 2023, namely a MAPE error rate of 2.85%, indicate that the forecasting results are within the "good" category.
Co-Authors Arief Jananto Edy Winarno Elfira Nureza Ardina Erlinasari Erlinasari Ery Sadewa Heri Purwanto Imam Husni Al Amin Ivannofick Adha Nugraha Iwan Adhicandra Kraugusteeliana Kraugusteeliana Muliandhi, Puri Puri Muliandhi Puri Muliandhi Rofi'atun Nihayah Roni Kartika Pramuyanti, Roni Kartika Rudi Hariyanto, Rudi Setyawan Wibisono Setyawan Wibisono Setyawan Wibisono Wiwien Hadikurniawati Zakaria, Franky Zuly Budiarso