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Submitted by: Alviyanur, Alviyanur
On: May 13, 2022 @ 5:42 PM
IP: 36.85.0.117

• 1. Title [Judul]: ANALISIS PERENCANAAN PRODUKSI MENGGUNAKAN METODE FORECASTING
• 2. Creator [Pengarang/ penulis]: ALVIYANUR
• 3. Subject [Subjek dan kata kunci]: Seasonal Method; Forecasting; Moving Averages; Exponential Smoothing
• 4. Description [Abstrak] : Production activities require precise forecasting and overall planning to address the problem of forecasting demand that sales may decline or increase over time in the future. This study aims to maximize the level of customer service, minimize inventory investment and operating efficiency. This research uses a forecasting method using past data using 2 calculation methods, namely using the Moving Average and Exponential Smoothing methods to forecast the production of sawn timber produced by CV. Diki Putra in Kec. Sebulu Kutai Kartanegara. This business unit has been established since 2008 until now, in production planning which has been using the seasonal calculation method, namely, the dry season and the rainy season so that there is a shortage of raw materials duringcertain seasons even though the amount of wood stock in East Kalimantan is still adequate for the production of processed wood. Therefore, forecasting is carried out using the 6-month Moving Average and Exponential Smoothing = 0.9 with 3 data accuracy measurement tools, namely Mean Absolute Deviation, Mean Square Error, and Mean Absolute Percentage Error. After analyzing the results, it was found that Exponential Smoothing is more appropriate because it is close to the real value of the amount of production so far with Exponential Smoothing results with a total of 114.176M^3 per month with a MAD value of 1.480, MSE 3.232.175, and a MAPE value of 1.35%.
• 5. Publisher [Nama Lembaga Kontributor]: Program Studi Ilmu Administrasi Bisnis
• 6. Contributor [Pembimbing, promotor, ilustrator, produser, dll.] : Dr. Zaini M. Si, Wira Bharata S. Ab, M. Ab
• 7. Date [Tanggal / tahun penciptaan atau penerbitan]: 21 Maret 2022
• 8. Type: Artikel
• 9. Identifier/ permalink [URL menuju konten di lembaga kontributor]: https://jist.publikasiindonesia.id/index.php/jist/article/view/387
• 10. Right [Contoh: CCL, MIT, Open Document, dll.]: eJournal article