A novel naïve Bayes approach to identifying grooming behaviors in the force-plate actometric platform

Anderson, Collin J.; Cadeddu, Roberto; Anderson, Daria Nesterovich; Huxford, Job A.; VanLuik, Easton R.; Odeh, Karen; Pittenger, Christopher; Pulst, Stefan M.; Bortolato, Marco

doi:10.1016/j.jneumeth.2023.110026

Cited by 1 publication

(2 citation statements)

References 34 publications

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“…Penelitian ini dilakukan di lapangan, yaitu di JNE Kopma UNY, untuk mengamati data numerik untuk mengukur dan menganalisis variabel-variabel yang terkait dengan prediksi permintaan [39], [41]- [43].…”

Section: Metode Penelitian 21 Desain Penelitianunclassified

“…Oleh sebab itu, kontribusi tingkat kesalahan berperan penting MAD, MSE dan MAPE[36]-[38].Studi yang ada, belum melakukan perspektif metrik akurasi, pertimbangan dinamika data. Metrik akurasi tepat, salah satunya adalah Mean Percentage Error (MPE) dan model asumsi permintaan tiap periode dapat menggunakan Naïve Approach[39],[40]. Keduanya akan digunakan sebagai model dalam peramalan permintaan paket pengiriman pada JNE Penelitian ini akan menentukan metode peramalan yang paling optimal untuk memprediksi penjualan JNE Kopma UNY dengan membandingkan tingkat akurasi berdasarkan Mean Percentage Error (MPE) dari tiga metode peramalan, yaitu Naive Approach, Simple Moving Average (SMA) 3 bulan, dan Weighted Moving Average (WMA)…”

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Perbandingan Pendekatan Metode Peramalan Naive Approach, Simple Moving Average dan Weighted Moving Average dalam Upaya Meningkatkan Prediksi Penjualan JNE Kopma UNY

Cahya Wulan,

Pasca Riani

2024

jatiunik. jurnal. ilm. teknik. manaj. industri.

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JNE Kopma UNY's logistics demand increases 2% per week, the manual courier allocation system is unable to keep up, predictions are accurate and real-time is needed. However, there is no exact accuracy for this case. The study was conducted to determine the accuracy of the smallest Mean Percentage Error (MPE) at JNE Kopma UNY by observing sales data for 2022 to predict demand. The data was analyzed using the Naive Approach, SMA and WMA methods, then measured using the MPE to determine the best forecasting method. The software used is Microsoft Excel 2016. The 3 Month (SMA) produces the highest sales prediction (Rp. 38,668,850) for January 2023 compared to Naive Approach (Rp. 35,086,330) and 3 Month WMA (Rp. 37,993,380). 3 Month SMA is proven to be superior with the lowest MPE (12.07%) and consistent performance. Naive Approach is inaccurate (MPE 20.26%) and 3 Month WMA performance is unstable (MPE 14.27%). This research recommends 3 Month SMA for JNE Kopma UNY to increase the accuracy of sales predictions and optimize stock. Opportunities for further research are open regarding the application of 3 Month SMA in various contexts.

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Section: Metode Penelitian 21 Desain Penelitianunclassified

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