Peramalan Penjualan Pupuk GoldenSoil Menggunakan Metode SARIMAX dengan Pendekatan Analisis Intervensi pada PT Sumber Alam Unggul

Suwardana, Farhan Adika (2026) Peramalan Penjualan Pupuk GoldenSoil Menggunakan Metode SARIMAX dengan Pendekatan Analisis Intervensi pada PT Sumber Alam Unggul. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

PT. Sumber Alam Unggul, distributor pupuk organik cair “GoldenSoil”, menghadapi tantangan perencanaan stok akibat pandemi COVID-19 yang menyebabkan kekosongan penjualan (zero sales) pada akhir 2020 hingga pertengahan 2023. Kondisi ini menciptakan patahan struktural (structural break) yang membuat metode peramalan konvensional tidak dapat diterapkan secara langsung. Tugas Akhir ini bertujuan meramalkan penjualan GoldenSoil menggunakan metode SARIMAX dengan pendekatan Analisis Intervensi, di mana variabel dummy berbentuk fungsi step digunakan untuk memodelkan dampak pandemi, dan kinerjanya dievaluasi dengan RMSE dan sMAPE. Model terbaik yang diperoleh adalah SARIMAX(2,1,2)(0,1,1) dengan periode musiman 48. Variabel intervensi terbukti signifikan (koefisien −1.623,86 liter; p = 0,026), yang mengonfirmasi penurunan penjualan selama pandemi. Pada data uji, model menghasilkan RMSE 1.964,06 liter dan sMAPE 79,35%, menunjukkan akurasi peramalan yang masih rendah akibat data yang bersifat intermiten dan lonjakan musiman yang tidak konsisten antar tahun. Tugas Akhir ini menyimpulkan bahwa pendekatan SARIMAX dengan analisis intervensi dapat diterapkan untuk menangani patahan struktural akibat pandemi, sekaligus memberikan gambaran awal pola penjualan sebagai masukan bagi perusahaan dalam perencanaan pengadaan barang pasca disrupsi. Serangkaian pengujian robustness tambahan — deteksi outlier, uji differencing, serta variasi indeks musiman — turut mengonfirmasi ketepatan konfigurasi model tersebut.
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PT. Sumber Alam Unggul, a distributor of “GoldenSoil” liquid organic fertilizer, faces stock planning challenges caused by the COVID-19 pandemic, which led to zero sales from late 2020 to mid 2023. This created a structural break that rendered conventional forecasting methods inapplicable. This study aims to forecast GoldenSoil sales using the SARIMAX method with an Intervention Analysis approach, in which a step-function dummy variable is used to model the pandemic impact, with performance evaluated using RMSE and sMAPE. The best model obtained is SARIMAX(2,1,2)(0,1,1) with a seasonal period of 48. The intervention variable is statistically significant (coefficient −1,623.86 liters; p = 0.026), confirming the decline in sales during the pandemic. On the test data, the model produces an RMSE of 1,964.06 liters and an sMAPE of 79.35%, indicating relatively low forecasting accuracy due to the intermittent nature of the data and inconsistent seasonal peaks across years. This study concludes that the SARIMAX approach with intervention analysis can be applied to handle the pandemic-induced structural break, while providing an initial overview of the sales pattern as an input for the company in post-disruption procurement planning. A series of additional robustness checks — outlier detection, differencing tests, and seasonal-index variation — further confirm the adequacy of the selected model configuration

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Peramalan Penjualan, SARIMAX, Analisis Intervensi, Patahan Struktural, Interrupted Time Series, Pupuk Organik, Sales Forecasting, SARIMAX, Intervention Analysis, Structural Break, Interrupted Time Series, Organic Fertilizer
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD30.27 Business forecasting T Technology > T Technology (General) > T174 Technological forecasting
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis
Depositing User:	Farhan Adika Suwardana
Date Deposited:	29 Jul 2026 03:28
Last Modified:	29 Jul 2026 03:28
URI:	http://repository.its.ac.id/id/eprint/138949

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