ANALISIS DAN PENERAPAN METODE REGRESI LINEAR DAN DECISION TREE UNTUK MEMPREDIKSI PENJUALAN PADA RAYYAN BAKERY SIMPANG MARBAU =================================================================================================== ANALYSIS AND IMPLEMENTATION OF LINEAR REGRESSION AND DECISION TREE METHODS TO PREDICT SALES AT RAYYAN BAKERY, SIMPANG MARBAU

NATARI DIA ALIKA HIDAYAH, NPM 2209100087 (2026) ANALISIS DAN PENERAPAN METODE REGRESI LINEAR DAN DECISION TREE UNTUK MEMPREDIKSI PENJUALAN PADA RAYYAN BAKERY SIMPANG MARBAU =================================================================================================== ANALYSIS AND IMPLEMENTATION OF LINEAR REGRESSION AND DECISION TREE METHODS TO PREDICT SALES AT RAYYAN BAKERY, SIMPANG MARBAU. Tugas_Akhir(Artikel) : Jurnal Sistem Informasi (SISTEMASI) Sinta 3, 15 (2). pp. 758-772. ISSN 2302-8149 (p-ISSN) / 2540-9719 (e-ISSN)

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Abstract

Perkembangan teknologi informasi dan analitik data mendorong pelaku usaha untuk memanfaatkan data historis sebagai dasar pengambilan keputusan bisnis. Pada sektor usaha kecil dan menengah (UKM), khususnya di bidang kuliner, kemampuan memprediksi penjualan menjadi aspek penting dalam perencanaan produksi dan pengelolaan stok agar operasional usaha dapat berjalan secara efisien. Rayyan Bakery Simpang Marbau sebagai UKM bakery menghadapi permasalahan fluktuasi penjualan yang selama ini masih dikelola berdasarkan pengalaman tanpa analisis data yang sistematis. Permasalahan utama dalam penelitian ini adalah belum adanya penerapan metode prediksi penjualan berbasis data mining yang dapat membantu pemilik usaha dalam memperkirakan jumlah penjualan secara akurat. Oleh karena itu, diperlukan pendekatan prediksi yang mampu memanfaatkan data historis penjualan untuk mendukung pengambilan keputusan manajerial. Metode yang digunakan dalam penelitian ini adalah regresi linear dan decision tree. Data yang dianalisis berupa data penjualan Rayyan Bakery Simpang Marbau dalam periode tertentu. Regresi linear digunakan untuk memodelkan hubungan linier antara variabel penjualan, sedangkan decision tree digunakan untuk menangkap pola non-linier serta menghasilkan aturan keputusan yang mudah diinterpretasikan. Kinerja kedua metode kemudian dianalisis dan dibandingkan berdasarkan hasil prediksi yang dihasilkan. Hasil penelitian menunjukkan bahwa baik metode regresi linear maupun decision tree mampu digunakan untuk memprediksi penjualan, namun decision tree memberikan hasil yang lebih fleksibel dalam menangkap pola penjualan yang berfluktuasi. Temuan ini diharapkan dapat membantu Rayyan Bakery dalam perencanaan produksi dan pengelolaan stok, serta menjadi referensi penerapan metode prediksi penjualan pada UKM sejenis. Kata kunci : Analisis, Regresi Linier, Decision Tree, Prediksi, Penjualan, Bakery ================================================================================================= The development of information technology and data analytics has encouraged business actors to leverage historical data as a basis for decision-making. In the small and medium enterprise (SME) sector, particularly in the culinary field, the ability to predict sales is a crucial aspect of production planning and stock management to ensure operational efficiency. Rayyan Bakery Simpang Marbau, as a bakery SME, faces challenges due to fluctuating sales that have traditionally been managed based on experience rather than systematic data analysis. The main problem addressed in this study is the absence of a data-driven sales prediction method that can assist the business owner in estimating sales accurately. Therefore, a predictive approach that utilizes historical sales data is required to support managerial decision-making. This study employs linear regression and decision tree methods. The analyzed data consist of historical sales records of Rayyan Bakery Simpang Marbau over a specific period. Linear regression is used to model the linear relationship between sales variables, while the decision tree captures non-linear patterns and produces easily interpretable decision rules. The performance of both methods is analyzed and compared based on the accuracy of the predictions they generate. The results indicate that both linear regression and decision tree methods can be effectively used to predict sales; however, the decision tree provides greater flexibility in capturing fluctuating sales patterns. These findings are expected to assist Rayyan Bakery in production planning and stock management, as well as serve as a reference for applying sales prediction methods in similar SMEs. Keywords : Analysis, Linear Regression, Decision Tree, Prediction, Sales, Bakery

Item Type:	Article
Uncontrolled Keywords:	Analisis, Regresi Linier, Decision Tree, Prediksi, Penjualan, Bakery ==================================== Analysis, Linear Regression, Decision Tree, Prediction, Sales, Bakery
Subjects:	H Social Sciences > HF Commerce Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Divisions:	Fakultas Sains Dan Teknologi > Sistem Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	05 May 2026 03:56
Last Modified:	07 May 2026 03:16
URI:	http://repository.ulb.ac.id/id/eprint/2212

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