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          "name": {
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            "given": "Ellok Sintha",
            "family": "Maydiana",
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      "contact_email": "digilib@unpkdr.ac.id",
      "department": "KODEPRODI55201#Teknik Informatika",
      "date": "2026-07-21",
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      "abstract": "Penelitian ini bertujuan untuk mengembangkan Sistem Manajemen Penjualan Gula Merah pada Distributor Gula Express yang mendigitalisasi seluruh proses operasional bisnis secara terintegrasi. Sistem ini memfasilitasi pengelolaan master data, pencatatan transaksi penjualan secara real-time, pemantauan keluar-masuk persediaan (stok) barang, rekam jejak pengiriman logistik, hingga manajemen piutang atau hutang pelanggan.Untuk mengoptimalkan pengambilan keputusan dan efisiensi rantai pasok, sistem ini mengintegrasikan metode analitik prediktif berbasis kecerdasan buatan. Metode Autoregressive Integrated Moving Average (ARIMA) digunakan untuk melakukan peramalan kebutuhan stok barang di masa mendatang berdasarkan data historis penjualan dan persediaan. Sementara itu, algoritma Extreme Gradient Boosting (XGBoost) diterapkan untuk memprediksi estimasi biaya distribusi logistik berdasarkan variabel jarak pengiriman, berat muatan, dan jenis kendaraan. Sistem dikembangkan menggunakan arsitektur modern berbasis framework Laravel, React.js dengan TypeScript, serta layanan kecerdasan buatan berbasis Python.Hasil pengujian model ARIMA menggunakan skema pembagian data 80:20 menunjukkan nilai Mean Absolute Percentage Error (MAPE) sebesar 61,52% untuk Gula Tebu, 32,86% untuk Gula Kelapa, 32,29% untuk Gula Ceplik, dan 48,57% untuk Gula Tanggung. Sementara itu, model XGBoost memperoleh tingkat akurasi yang sangat tinggi dengan nilai koefisien determinasi (R²) sebesar 95,50% dan Mean Absolute Error (MAE) sebesar Rp12.053,21 pada simulasi distribusi menggunakan armada truk sedang dengan jarak tempuh 150 km dan muatan 4.000 kg.",
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