Seasonal Pattern Analysis In Bolu House Sales Using Seasonal Adjustment Method

Stefhany Andrean; Muhammad Ardiansyah Sembiring; Maulana Dwi Sena

doi:10.30865/jurikom.v12i4.8937

Authors

Stefhany Andrean Universitas Royal Asahan Sumatera Utara
Muhammad Ardiansyah Sembiring Universitas Royal Asahan Sumatera Utara
Maulana Dwi Sena Universitas Royal Asahan Sumatera Utara

DOI:

https://doi.org/10.30865/jurikom.v12i4.8937

Keywords:

Seasonal Adjustment, Rumah Bolu, Sponge Cake Sale

Abstract

Rumah Bolu is a business engaged in the sale of sponge cakes located on Jalan Perumahan Duta Mas 9, Sei Kamah II, Kec. Sei Dadap, Asahan Regency, North Sumatra 21263. The problems faced by Rumah Bolu include if the stock decreases, Rumah Bolu risks losing sales and customer trust, while if the stock is excessive but sales are low it can cause wasteful costs, decreased product quality and financial losses that hinder maximum profits. During certain seasons such as weekends or big celebrations, the demand for sponge cakes can increase drastically which risks causing shortages of raw material stock and delays in marketing. Conversely, on Monday to Friday, sales tend to decrease which can result in stock piling up and increase the risk of loss. With the need for a forecasting system, Rumah Bolu can adjust sales based on seasonal demand patterns so as to avoid the risk of shortages or excess stock, optimize operational costs and increase profits to the maximum. To predict the sale of sponge cake, a forecasting method is applied, namely the Seasonal Adjustment method, which is used when the time series data pattern obtained has a seasonal pattern. The seasonal pattern is a fairly unique sales pattern because it can be seen when there is a certain increase in a certain season. The purpose of this study is to design a sponge cake stock forecasting application with the Seasonal Adjustment method and to apply a forecasting method to predict the stock of sponge cakes at Rumah Bolu using PHP and its MySQL database. The research method used in this study is a quantitative research method. The results of the Seasonal Adjustment calculation prediction on banana sponge cakes for the January 2025 period were 424 with a MAPE of 5.53%. Then the results of the Seasonal Adjustment calculation prediction on pandan sponge cakes for the January 2025 period were 73.67 with a MAPE of 3.84% and the results of the Seasonal Adjustment calculation prediction on birthday sponge cakes for the January 2025 period were 142.67 with a MAPE of 3.03%.

References

N. H. Setiawan and Z. Zulkarnain, “Forecasting Palm Oil Production Using Long Short-Term Memory (LSTM) With Time Series Cross Validation (TSCV),” Int. J. Soc. Serv. Res., vol. 4, no. 05, pp. 1237–1251, 2024, doi: 10.46799/ijssr.v4i05.780.

N. Khaerani, D. Anggraeni, and D. Moeis, “Analysis Of The Simple Moving Average Method For Estimation Of Revenue For Nanishop Cosmetic Shops354,” Nusant. Hasana J., vol. 1, no. 7, pp. 33–37, 2021.

M. W. Putri and F. N. Azizah, “Comparison of Moving Average, Single Exponential Smoothing, and Trend Analysis Forecasting Methods on Art Board Production Demand (Case Study of PT Pindo Deli Pulp and Paper Mills 1),” J. Rekayasa Sist. dan Ind., vol. 8, no. 2, pp. 104–109, 2021.

A. Dzulfikar, M. Orisa, and F. Santi Wahyuni, “Aplikasi Peramalan Untuk Prediksi Stok Di Perusahaan Percetakaan Berbasis Web Dengan Metode Trend Moment,” JATI (Jurnal Mhs. Tek. Inform., vol. 7, no. 5, pp. 3182–3190, 2024, doi: 10.36040/jati.v7i5.7645.

Noviadry Nur Tamtama and Rahmawati Riantisari, “Analisis Peramalan Permintaan Melalui Metode Moving Average, Weighted Moving Average dan Exponential Smoothing (Studi Kasus Pada Exist Auto Detailing),” Primanomics J. Ekon. Bisnis, vol. 22, no. 1, pp. 109–120, 2024, doi: 10.31253/pe.v22i1.2685.

S. Sahara, R. A. Permana, M. Marlina, and J. Jamaludin, “Prediksi Persediaan Barang Menggunakan Indikator Moving Average Studi Kasus Department Store,” J. Teknol. Sist. Inf., vol. 5, no. 1, pp. 171–180, 2024, doi: 10.35957/jtsi.v5i1.7811.

N. Hidayat, Muhammad Ammar Rizki, and Ageng Priyo Wijaya, “Analisis Peramalan dalam Menentukan Perencanaan Persediaan pada Toko Seragam Sekolah Hermul Jaya,” El-Mal J. Kaji. Ekon. Bisnis Islam, vol. 5, no. 5, pp. 3267–3273, 2024, doi: 10.47467/elmal.v5i5.1256.

W. I. Butarbutar et al., “Peramalan Harga Taksiran Emas Dan Uang Pinjaman Pada Pt. Pegadaian Cabang Passo Dengan Menggunakan Metode Double Moving Average,” Var. J. Stat. Its Appl., vol. 5, no. 1, pp. 1–12, 2023, doi: 10.30598/variancevol5iss1page1-12.

K. Hanapi and S. Harlina, “Systematic Review Peramalan Penjualan Produk dalam Sistem Sales Force Automation,” Pros. Semin. Ilm. Sist. Inf. dan Teknol. Inf., vol. 14, no. 1, pp. 98–103, 2025.

W. W. Alfarisi, Z. Haura, D. A. Pratiwi, F. A. Putri, E. Sadewo, and G. Darmawan, “Comparative Analysis of Fourier Series Analysis and Holtwinters Methods on Forecasting Additive Seasonal Data,” Innov. J. Soc. Sci. Res., vol. 4, no. 1, pp. 1310–1325, 2024, [Online]. Available: http://j-innovative.org/index.php/Innovative/article/view/7570

D. Widyaningrum, “Analisis Peramalan Permintaan Refill Gas dengan Exponential Smoothing,” Matrik J. Manaj. dan Tek. Ind. Produksi, vol. 23, no. 2, p. 131, 2023, doi: 10.30587/matrik.v23i2.5260.

E. Lawby and J. Rahardjo, “Trendline with Seasonal Adjustment Forecast for CF150 in Sport Mid Segment Product,” J. Titra, vol. 8, no. 2, pp. 313–320, 2020.

S. Antar, B. Vol, X. I. V No, K. Ulum, and K. Hati, “Sistem Informasi Pemesanan dan Pemasangan Alumunium dan Kaca Berbasis Web Pada Ical Karya Kaca Alumunium,” J. Sist. Inf. STMIK Antar Bangsa, vol. 14, no. 1, pp. 45–50, 2025.

D. Kurniasari, A. D. Salsabila, and M. Usman, “Enhancing Weather Forecasting in Bandar Lampung?: A Hybrid SARIMA-LSTM Approach,” JTAM (Jurnal Teor. dan Apl. Mat., vol. 9, no. 1, pp. 206–220, 2025.

J. Sutanto and P. Adi, “Analisis Pengelolaan Container Kosong Pada PT . Mentari Mas Multimoda,” J. Titra, vol. 11, no. 2, pp. 281–288, 2023.

M. Riyan Dirgantara, S. Syahputri, and A. Hasibuan, “Pengenalan Database Management System (DBMS),” J. Ilm. Multidisipline, vol. 1, no. 6, pp. 300–301, 2023, [Online]. Available: https://doi.org/10.5281/zenodo.8123019

S. M. Pulungan, R. Febrianti, T. Lestari, N. Gurning, and N. Fitriana, “Analisis Teknik Entity-Relationship Diagram Dalam Perancangan Database,” J. Ekon. Manaj. dan Bisnis, vol. 1, no. 2, pp. 98–102, 2023, doi: 10.47233/jemb.v1i2.533.

H. A. Madjid, A. Ambarwati, and L. Latipah, “Decision Support System Peramalan Permintaan Layanan Kecantikan dengan Single Exponential Smoothing dan Simple Moving Average,” J. Sist. dan Teknol. Inf., vol. 9, no. 3, p. 372, 2021, doi: 10.26418/justin.v9i3.45796.

R. S. Nasution, D. Abdullah, and A. Razi, “Implementasi Sistem Monitoring dan Menentukan UKM Terbaik Menggunakan Metode Topsis,” RABIT J. Teknol. dan Sist. Inf. Univrab, vol. 10, no. 2, pp. 1253–1264, 2025.

E. Siswanto, E. Satria Wibawa, and M. Zaenal, “Implementasi Aplikasi Sistem Peramalan Persedian Barang Menggunakan Metode Single Moving Average Berbasis Web,” Elkom J. Elektron. dan Komput., vol. 14, no. 2, pp. 224–233, 2021, doi: 10.51903/elkom.v14i2.515.