PENGUJIAN METODE NEURAL NETWORK BACKPROPAGATION DAN LINEAR REGRESSION DALAM MEMPREDIKSI TARGET PENJUALAN PUPUK UREA PSO (STUDI KASUS : PT. PUPUK SRIWIDJAJA PALEMBANG)

SALSHABILA, RENITA and Jambak, Muhammad Ihsan (2021) PENGUJIAN METODE NEURAL NETWORK BACKPROPAGATION DAN LINEAR REGRESSION DALAM MEMPREDIKSI TARGET PENJUALAN PUPUK UREA PSO (STUDI KASUS : PT. PUPUK SRIWIDJAJA PALEMBANG). Undergraduate thesis, Sriwijaya University.

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Abstract

PT. PUSRI (Pupuk Sriwidjaja) has the responsibility and obligation to carry out the distribution and marketing of subsidized fertilizers to farmers to implement the Public Service Obligation (PSO) to support the national food program by prioritizing the production and distribution of fertilizers for farmers throughout Indonesia. In this case, it is essential for PT. PUSRI (Pupuk Sriwidjaja) makes predictions to consider the ideal amount of fertilizer to be provided in the future so that the company does not experience a shortage of inventory or excess inventory, which will result in losses to the company. For this reason, data mining is a supporting methodology in making structured predictions implemented by comparing the Neural Network Backpropagation algorithm with the Linear Regression algorithm to find a prediction tool that has the highest accuracy result. The data used is the sales data of urea fertilizer PSO in 2019. The learning and training data were carried out through the rapidMiner software application using the cross-validation technique. The results obtained respectively show MSE error values of 0.767 and 5.130, indicating that the Neural Network Backpropagation has a higher level of accuracy than the Linear Regression. Keywords: Neural Network Backpropagation, Linear Regression, Prediction, Rapidminer.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Neural Network Backpropagation, Linear Regression, Prediksi, Cross Validation, Rapidminer
Subjects:	H Social Sciences > HF Commerce > HF5410-5417.5 Marketing. Distribution of products > HF5415.126.R38 Database marketing--Statistical methods. Data mining--Statistical methods. Big data--Statistical methods. Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.D343 Data mining. Database searching. Big data. Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.Z55 Apache Hadoop (Computer file) Electronic data processing--Distributed processing. File organization (Computer science) Data mining. Streaming technology (Telecommunications)
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Users 11200 not found.
Date Deposited:	07 May 2021 04:19
Last Modified:	07 May 2021 04:19
URI:	http://repository.unsri.ac.id/id/eprint/46334

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