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Muhazir, Ahmad
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Social Sciences

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Analisis Penjualan Sepeda Motor Di Cv. Honda Karya Utama Berbasis Algoritma Regresi Linier Rhindi, Lira; Fauziah, Rizky; Muhazir, Ahmad
J-Com (Journal of Computer) Vol. 5 No. 2 (2025): JULI 2025
Publisher : STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/j-com.v5i2.4164

Abstract

Abstract: Motorcycle sales are one of the key indicators of growth in Indonesia’s automotive industry. CV. Honda Karya Utama, as an authorized Honda motorcycle dealer, faces challenges due to unstable monthly sales fluctuations. This uncertainty complicates stock planning, marketing strategy formulation, and may lead to potential losses caused by overstocking or understocking. To address these issues, this study aims to analyze the relationship between time and sales volume and to develop a predictive model that can assist management in making more effective business decisions. The research was conducted using a quantitative method and a machine learning approach by applying a linear regression algorithm, implemented through the Python programming language and a MySQL database. The dataset used consists of monthly sales data over one year, analyzed to predict future sales trends. The results show that the linear regression algorithm can predict sales trends with a good level of accuracy, achieving evaluation values of MAPE 1.72%, MSE 1.76%, and RMSE 0.57. The developed model assists management in formulating marketing strategies, optimizing inventory planning, and minimizing financial risks. Therefore, linear regression can serve as an effective analytical tool to support strategic business decision-making at CV. Honda Karya Utama. Keywords: motorcycle sales; linear regression; prediction; sales analysis Abstrak: Penjualan sepeda motor merupakan salah satu indikator penting dalam pertumbuhan industri otomotif di Indonesia. CV. Honda Karya Utama sebagai dealer resmi sepeda motor Honda menghadapi tantangan berupa fluktuasi penjualan yang tidak stabil setiap bulannya. Ketidakpastian ini menyebabkan kesulitan dalam perencanaan stok, penentuan strategi pemasaran, serta berpotensi menimbulkan kerugian akibat kelebihan atau kekurangan persediaan. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan untuk menganalisis hubungan antara waktu dan jumlah penjualan serta membangun model prediksi yang dapat membantu manajemen dalam pengambilan keputusan bisnis yang lebih efektif. Penelitian dilakukan dengan metode kuantitatif dan pendekatan machine learning menggunakan algoritma regresi linier, dengan implementasi berbasis bahasa pemrograman Python dan basis data MySQL. Data yang digunakan berupa data penjualan bulanan selama satu tahun, yang kemudian dianalisis untuk memprediksi tren penjualan pada periode berikutnya. Hasil penelitian menunjukkan bahwa regresi linier mampu memprediksi tren penjualan dengan tingkat akurasi yang baik, dengan nilai evaluasi MAPE sebesar 1,72%, MSE 1,76%, dan RMSE 0,57. Model ini membantu manajemen dalam menyusun strategi pemasaran, mengoptimalkan perencanaan stok, serta meminimalkan risiko kerugian. Dengan demikian, regresi linier dapat menjadi alat bantu yang efektif dalam mendukung keputusan bisnis di CV. Honda Karya Utama. Kata kunci: penjualan sepeda motor; regresi linier; prediksi; analisis penjualan
Co-Authors Anggi Mela Ariska Arridha Zikra Syah Chaniago, Audiya Ananda Fauziah, Rizky Guntur Maha Putra Irawati, Novica Jeperson Hutahaean Khairul Saleh Nofriadi Nofriadi Novica Irawati Pratiwi, Radila Rainah Rainah, Rainah Rhindi, Lira Rianda, Kiki Rizki Rizaldi, Rizaldi Siddik, Mohd Syukri Syukri Utami, Lola Citra Yessica Siagian Yustria Handika Siregar