MAULANA, DWI WAHYU (2025) ANALISIS PREDIKSI KETEPATAN WAKTU PENGIRIMAN PAKET PADA PT.XYZ MENGGUNAKAN ALGORITMA DECISION TREE C4.5. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Transportation and logistics are important elements in supporting efficient distribution of goods, especially in the increasingly developing digital era. Public demand for fast and timely delivery services encourages companies to improve their delivery management. This study aims to predict the punctuality of delivery at PT. XYZ using the Decision Tree C4.5 algorithm. The research method used is a quantitative approach with numerical data covering 10,000 regular delivery transactions during September 2024. The main variables used include weather conditions, destination city, date received, and last status. The results of the study show that the Decision Tree C4.5 algorithm is effective in projecting delivery times, with parameters such as weather and destination city playing an important role in predicting delays. The model that produces good performance based on the evaluation of accuracy, precision, and F1-score metrics, so it can help PT. XYZ in improving the efficiency of their shipping operations and minimizing delays. This study is expected to be a reference for other logistics companies to implement similar predictive models in shipping management. Kata kunci: Logistics, On Time Delivery, Decision Tree C4.5 Algorithm, Prediction Transportasi dan logistik merupakan elemen penting dalam mendukung distribusi barang yang efisien, terutama di era digital yang semakin berkembang. Permintaan masyarakat akan layanan pengiriman barang yang cepat dan tepat waktu mendorong perusahaan untuk meningkatkan manajemen pengiriman mereka. Penelitian ini bertujuan untuk memprediksi ketepatan waktu pengiriman di PT. XYZ menggunakan algoritma Decision Tree C4.5. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan data numerik yang mencakup 10.000 transaksi pengiriman reguler selama bulan September 2024. Variabel utama yang digunakan meliputi kondisi cuaca, kota tujuan, tanggal diterima, dan status terakhir. Hasil penelitian menunjukkan bahwa algoritma Decision Tree C4.5 efektif dalam memproyeksikan waktu pengiriman, dengan parameter seperti cuaca dan kota tujuan berperan penting dalam memprediksi keterlambatan. Model yang dibangun menghasilkan performa yang baik berdasarkan evaluasi metrik akurasi, presisi, dan F1-score, sehingga dapat membantu PT. XYZ dalam meningkatkan efisiensi operasional pengiriman mereka dan meminimalkan keterlambatan. Penelitian ini diharapkan dapat menjadi acuan bagi perusahaan logistik lain untuk mengimplementasikan model prediktif serupa dalam manajemen pengiriman. Kata kunci: Logistik, Ketepatan Waktu Pengiriman, Algoritma Decision Tree C4.5, Prediksi
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