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J-HyTEL welcomes original and rigorous scholarship advancing education, media technology, and computer science applications.
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Abstrak
Pencatatan persediaan secara manual dan praktik pemesanan heuristik masih umum dilakukan di kalangan Usaha Mikro, Kecil, dan Menengah (UMKM), yang sering kali menyebabkan perkiraan permintaan yang tidak akurat, biaya penyimpanan yang berlebihan, dan kehabisan stok. Penelitian ini mengembangkan dan mengevaluasi sistem informasi persediaan berbasis web yang mengintegrasikan peramalan Autoregressive Integrated Moving Average (ARIMA) dengan model Economic Order Quantity (EOQ) untuk meningkatkan akurasi pengambilan keputusan dan efisiensi biaya. Sistem ini menggunakan CodeIgniter 3 dan MySQL serta mengintegrasikan mesin peramalan deret waktu berbasis Python. Data penjualan historis dimodelkan menggunakan ARIMA, dan spesifikasi optimal dipilih berdasarkan Kriteria Informasi Akaike (AIC) dan Kriteria Informasi Bayesian (BIC). Model ARIMA(1,1,1) mencapai Mean Absolute Percentage Error (MAPE) sebesar 8,47%, yang menunjukkan akurasi peramalan yang tinggi untuk perencanaan operasional. Permintaan tahunan yang diproyeksikan diintegrasikan ke dalam kerangka kerja EOQ untuk menentukan jumlah pesanan optimal, Titik Pemesanan Ulang (ROP), dan Persediaan Pengaman probabilistik. Simulasi biaya selama satu tahun menunjukkan bahwa kebijakan berbasis EOQ mengurangi total biaya persediaan sebesar 22,73% dibandingkan dengan pendekatan yang ada. Validasi fungsional melalui pengujian Black-Box memastikan kepatuhan penuh terhadap persyaratan yang ditentukan. Temuan ini menunjukkan bahwa mengintegrasikan analitik prediktif dengan optimisasi persediaan klasik meningkatkan efisiensi operasional dan mengurangi total biaya persediaan. Sistem ini menyediakan kerangka kerja manajemen persediaan yang praktis dan didorong oleh data bagi UMKM yang sedang menjalani transformasi digital.
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Referensi
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