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OPTIMASI STRATEGI PENJUALAN MELALUI INTEGRASI METODE K-NEAREST NEIGHBORS (KNN) DAN REGRESI LINIER UNTUK MENGIDENTIFIKASI PRODUK TERLARIS

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Penilaian

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In today's competitive digital era, optimizing sales strategies is crucial for sustaining online business growth. This study aims to identify best-selling products by integrating the K-Nearest Neighbors (KNN) algorithm and linear regression. The research utilizes sales data from the fashion brand "Zaskia Sungkar Jakarta" on the Shopee e-commerce platform. The KNN method is applied to classify products into best-selling or non-best-selling categories based on attribute similarities, while linear regression is employed to predict the relationship between sales quantity and variables such as rating, reviews, discounts, and favorites. Evaluation results show that the KNN model achieved a classification accuracy of 80%, while the linear regression model produced an RMSE value of 33.09. The study concludes that the integration of KNN and linear regression effectively supports sales strategy decisions by providing predictive insights on potentially best-selling products. These findings are expected to aid in stock management, promotional planning, and customer loyalty enhancement.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507004713	T180669	T1806692025	Central Library (REFERENS)	Available but not for loan - Not for Loan

Detail Information

Series Title

09012682327022

Call Number

T1806692025

Publisher

Palembang : Program Magister Ilmu Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvii, 64 hlm.; ilus.; tab.; 29 cm.

Language

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Ilmu Komputer

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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