PREDIKSI JUMLAH PRODUKSI KERTAS A3 MENGGUNAKAN ALGORITMA PROPHET

TIVANO, M ALDRIN FARRELL and Arsalan, Osvari and Miraswan, Kanda Januar (2024) PREDIKSI JUMLAH PRODUKSI KERTAS A3 MENGGUNAKAN ALGORITMA PROPHET. Undergraduate thesis, Sriwijaya University.

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Abstract

The era of globalization has driven intense competition among businesses, forcing them to become smarter in fulfilling customer demand. One strategy adopted by companies is using machine learning to predict customer demand. This study focuses on the use of the Prophet algorithm developed by Meta or Facebook and published in 2017. The Prophet algorithm is resilient to missing data, changes over time, and data limitations, requiring minimal data modifications. The object of study in this research is a printing company in Palembang, Indonesia, called F18 Digital Printing, through the analysis of A3 paper production data with external factors such as the COVID-19 period and holidays. The data range used starts from 1July 2019 to 31 December 2022, for training data, and from 1 January 2023 to 30 June 2023. This study aims to compare the RMSE values of prediction results between two different time ranges. The Prophet algorithm has proven capable of predicting A3 paper production to anticipate warehouse needs and meet customer demands by providing low RMSE value at 197,17 for art paper 210. This research is expected to provide further insights into the effectiveness of the Prophet algorithm in the context of the printing industry

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Industri Percetakan
Subjects:	T Technology > T Technology (General) > T173.2-174.5 Technological change > T174 Technological forecasting T Technology > T Technology (General) > T57-57.97 Applied mathematics. Quantitative methods > T57.5 Data processing Cf. HF5548.125+ Business data processing Operations research. Systems analysis
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	M Aldrin Farrell Tivano
Date Deposited:	01 Apr 2024 03:37
Last Modified:	01 Apr 2024 03:37
URI:	http://repository.unsri.ac.id/id/eprint/143027

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