IMPLEMENTSI ALGORITMA FREQUENT PATTERN GROWTH DAN SIMPLE ADDITIVE WEIGHTING PADA APLIKASI SUPPLY CHAIN MANAGEMENT

HERMAWAN, DICKY SAPUTRA (2024) IMPLEMENTSI ALGORITMA FREQUENT PATTERN GROWTH DAN SIMPLE ADDITIVE WEIGHTING PADA APLIKASI SUPPLY CHAIN MANAGEMENT. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

The rapid development of technology in the current era has triggered a transformation in inventory management within companies. Many businesses still rely on manual record-keeping using Microsoft Excel, which is often inefficient and less accurate. This research proposes a solution by developing an inventory control application using the Frequent Pattern Growth (FP Growth) and Simple Additive Weighting (SAW) algorithms. The research aims to improve efficiency, reduce calculation errors, and enhance customer satisfaction through better decision-making in inventory management. Several previous studies have demonstrated the successful implementation of the SAW algorithm in other contexts, such as supplier selection, business location determination, and raw material inventory control. These findings provide support for the continued use of intelligent algorithms in various business aspects. In this study, the SAW algorithm is applied to improve understanding of consumer purchasing patterns and optimize sales, while FP Growth is used for sales transaction analysis to identify relationships between products. The application of the SAW and FP Growth algorithms is expected to contribute positively to operational efficiency, improve inventory management, and optimize sales strategies. The results of this research can serve as a useful reference for other companies looking to enhance their inventory management through the utilization of technology and algorithmic intelligence. Kata Kunci : Prediksi, Metode, FP-Growth, SAW, SCM Perkembangan teknologi yang pesat di era saat ini memicu transformasi dalam manajemen persediaan barang di perusahaan. Banyak perusahaan masih mengandalkan pencatatan manual dengan Microsoft Excel, yang seringkali tidak efisien dan kurang akurat. Penelitian ini mengusulkan solusi dengan mengembangkan aplikasi pengendalian persediaan menggunakan algoritma Frequent Pattern Growth (FP Growth) dan Simple Additive Weighting (SAW). Tujuan penelitian adalah meningkatkan efisiensi, mengurangi kesalahan perhitungan, dan memperbaiki kepuasan konsumen melalui pengambilan keputusan yang lebih baik terkait manajemen stok barang. Beberapa penelitian sebelumnya telah menunjukkan keberhasilan implementasi algoritma SAW dalam konteks lain, seperti pemilihan supplier, penentuan lokasi usaha, dan pengendalian persediaan bahan baku. Hasil-hasil tersebut memberikan dukungan terhadap keberlanjutan penggunaan algoritma cerdas dalam berbagai aspek bisnis. Dalam penelitian ini, algoritma SAW diterapkan untuk meningkatkan pemahaman pola pembelian konsumen dan mengoptimalkan penjualan, sementara FP Growth digunakan untuk analisis transaksi penjualan guna mengidentifikasi hubungan antar produk. Penerapan algoritma SAW dan FP Growth diharapkan dapat memberikan kontribusi positif terhadap efisiensi operasional perusahaan, meningkatkan pengelolaan persediaan, dan mengoptimalkan strategi penjualan. Hasil penelitian ini dapat menjadi acuan bermanfaat bagi perusahaan lain yang ingin meningkatkan manajemen persediaan mereka melalui pemanfaatan teknologi dan kecerdasan algoritma. Kata Kunci : Prediksi, Metode, FP-Growth, SAW, SCM

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 24 032
Call Number:	SIK/15/24/023
NIM/NIDN Creators:	41519120108
Uncontrolled Keywords:	Prediksi, Metode, FP-Growth, SAW, SCM
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 006 Special Computer Methods/Metode Komputer Tertentu > 006.4 Computer Pattern Recognition/Pola Pengenalan Komputer 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma 600 Technology/Teknologi > 640 Home Economic and Family Living Management/Kesejahteraan Rumah Tangga dan Manajemen Kehidupan Keluarga > 644 Household Utilities/Keperluan Rumah Tangga > 644.6 Household Water Supply/Persediaan Air untuk Rumah Tangga 600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 658 General Management/Manajemen Umum > 658.7 Management of Supplies/Manajemen Persediaan
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	12 Feb 2024 03:20
Last Modified:	12 Feb 2024 03:20
URI:	http://repository.mercubuana.ac.id/id/eprint/85959

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