Implementasi Algoritma Single Moving Average Untuk Prediksi Stok Barang Pada Sistem Pos Berbasis Web Di My Perfume
Kata Kunci:
Kata kunci: Point of Sale, Single Moving Average, Prediksi Stok, MAPE, Next.js.Abstrak
Dalam industri ritel yang kompetitif, pengelolaan persediaan barang menjadi faktor penentu keberlanjutan bisnis. Permasalahan utama yang dihadapi oleh toko ritel "My Perfume" adalah ketidakpastian manajemen stok akibat ketergantungan pada metode pencatatan manual dan intuisi pemilik usaha. Kondisi ini sering kali bermuara pada inefisiensi operasional berupa penumpukan barang (overstock) yang membebani modal kerja, serta kekosongan stok (stockout) pada produk terlaris yang menyebabkan hilangnya potensi pendapatan (lost sales). Penelitian ini bertujuan untuk mengatasi permasalahan tersebut dengan merancang dan mengimplementasikan algoritma peramalan Single Moving Average (SMA) ke dalam sebuah Sistem Point of Sale (POS) berbasis web. Sistem dikembangkan menggunakan model Waterfall yang sistematis, dengan memanfaatkan teknologi Modern Web Architecture yang terdiri dari Next.js untuk antarmuka pengguna (frontend) yang responsif dan Express.js untuk pengelolaan logika server (backend). Algoritma SMA dipilih karena kemampuannya meredam fluktuasi data penjualan yang bersifat stasioner untuk menghasilkan tren prediksi yang stabil. Kinerja sistem dievaluasi melalui pengujian akurasi menggunakan metode Mean Absolute Percentage Error (MAPE) terhadap data transaksi penjualan historis. Hasil pengujian menunjukkan bahwa sistem mampu memprediksi kebutuhan stok dengan tingkat presisi yang tinggi, menghasilkan rata-rata nilai error hanya sebesar 3,33%. Mengacu pada standar evaluasi kemampuan peramalan, nilai ini diklasifikasikan sebagai tingkat akurasi yang Sangat Baik (Highly Accurate). Temuan ini membuktikan bahwa integrasi metode peramalan ke dalam sistem POS efektif membantu pemilik usaha dalam mengambil keputusan pengadaan barang secara presisi, meminimalkan risiko kerugian, serta mendukung transformasi manajemen bisnis menuju pendekatan berbasis data (data-driven).
Unduhan
Referensi
REFERENSI
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