Penerapan Metode Trend Moment Dalam Sistem Forecasting Untuk Memprediksi Jumlah Penjualan Smartphone dan Aksesoris


  • Kevin Louis Universitas Prima Indonesia, Medan, Indonesia
  • Christina Julia Sinaga Universitas Prima Indonesia, Medan, Indonesia
  • Putra Edi Mujahid * Mail Universitas Prima Indonesia, Medan, Indonesia
  • (*) Corresponding Author
Keywords: Prediction; Trend Moment Method; Accessories Product; Smartphone Sales

Abstract

Trend Moment and Forecasting are data retrieval methods that have accurate and effective suitability to handle problems such as large amounts of data. The Trend Moment method is an approach that uses special statistical and mathematical calculation techniques to replace broken lines formed from the company's historical data with a straight line function. The Star Communicator store is one of the stores in the city of Medan that is engaged in selling various brands of smartphones and their accessories. Currently, the Star Communicator store still uses a conventional system to record its sales data. The admin staff will record product sales data. Then, at the end of the month, a sales recapitulation will be made to the store owner. The implementation of this system has a weakness where the company owner cannot know which products are more in demand by customers in a certain period. This information is needed so that the company owner can control smartphone stock in the company. Therefore, it is necessary to apply a smartphone prediction system. The result of this research is a desktop application that can be used to predict the number of smartphone sales in a certain period. From the results of the tests carried out, information was obtained that the average level of accuracy of the Trend Moment method was 70.22%. This means that the level of accuracy of the prediction results from the Trend Moment method is still not good. To improve the accuracy of the prediction results, the Trend Moment method can be combined with other methods, such as the Linear Regression method. In addition, other supporting factors for predictions can also be added, such as holiday factors or certain holidays which are often known as the holiday effect.

Downloads

Download data is not yet available.

References

A. Prasetia, “Faktor-Faktor Yang Mempengaruhi Persaingan Dan Pertumbuhan Pasar: Budaya, Sosial, Personal (Suatu Literature Review),” Jurnal Ilmu Manajemen Terapan, vol. 2, no. 4, pp. 442–462, 2021, doi: 10.31933/jimt.v2i4.457.

E. A. N. Putro, E. Rimawati, and R. T. Vulandari, “Prediksi Penjualan Kertas Menggunakan Metode Double Exponential Smoothing,” Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN), vol. 9, no. 1, p. 60, 2021, doi: 10.30646/tikomsin.v9i1.548.

M. Leonardi, R. Emilda, I. Katrin, and A. Yulianto, “Prediksi Penjualan Produk Rokok Pada PT. Indomarco Prismatama Menggunakan Algoritma C4.5,” Paradigma - Jurnal Komputer dan Informatika, vol. 23, no. 2, pp. 182–190, 2021, doi: 10.31294/p.v23i2.11151.

P. A. Duran, A. V. Vitianingsih, Moch. S. Riza, A. L. Maukar, and S. F. A. Wati, “Data Mining Untuk Prediksi Penjualan Menggunakan Metode Simple Linear Regression,” Teknika, vol. 13, no. 1, pp. 27–34, 2024, doi: 10.34148/teknika.v13i1.712.

A. Nurlifa and S. Kusumadewi, “Sistem Peramalan Jumlah Penjualan Menggunakan Metode Moving Average Pada Rumah Jilbab Zaky,” INOVTEK Polbeng - Seri Informatika, vol. 2, no. 1, p. 18, 2017, doi: 10.35314/isi.v2i1.112.

S. R. Tangahu and Moh. H. Koniyo, “Penerapan Metode DESB dan EOQ untuk Prediksi Penjualan dan Persediaan Mobil,” Jambura Journal of Informatics, vol. 3, no. 1, pp. 29–43, 2021, doi: 10.37905/jji.v3i1.10384.

I. Yulian, D. S. Anggraeni, and Q. Aini, “Penerapan Metode Trend Moment Dalam Forecasting Penjualan Produk CV. Rabbani Asyisa,” Jurnal Teknologi dan Sistem Informasi, vol. 6, no. 2, pp. 193–200, 2020.

R. Prayoga, J. Silaban, and S. Parsaoran Tamba, “Analisis Metode Trend Moment Dalam Forecasting Untuk Memprediksi Jumlah Penjualan Pada Restoran Ayam Geprek Gokil,” Jurnal TEKINKOM, vol. 6, no. 1, pp. 127–134, 2023, doi: 10.37600/tekinkom.v6i1.892.

A. Fauziyyah, “Implementasi Metode Trend Moment Untuk Prediksi Penjualan (Studi Kasus Di Toko Zacozi Pancing Kabupaten Solok),” Jurnal Teknoif Teknik Informatika Institut Teknologi Padang, vol. 12, no. 1, pp. 10–17, 2024, doi: 10.21063/jtif.2024.v12.1.10-17.

A. A. F. D. Izz, M. Sholihin, and M. Masruroh, “Trend Moment Method for predicting Multimedia Equipment Rental Needs,” Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi, vol. 5, no. 1, pp. 20–24, 2020, doi: 10.25139/inform.v5i1.2203.

F. M. Putri, “Tingkat Peramalan Penjualan Produk Bordir dan Sulaman Menggunakan Metode Trend Moment,” Jurnal Informatika Ekonomi Bisnis, vol. 4, pp. 34–38, 2022, doi: 10.37034/infeb.v4i2.122.

C. J. M. Sianturi, E. Ardini, and N. S. B. Sembiring, “Sales Forecasting Information System Using the Least Square Method in Windi Mebel,” Jurnal Inovasi Penelitian, vol. 1, no. 2, pp. 75–82, 2020, doi: 10.47492/jip.v1i2.52.

Wahyu Hadi Sutiyono and Widya Setiafindari, “Analisis Penerapan Forecasting Penjualan Untuk Menentukan Jumlah Tenaga Kerja Efektif Produksi Tepung Mocaf Pada UMKM XYZ,” Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika, vol. 2, no. 4, pp. 181–194, 2024, doi: 10.61132/jupiter.v2i4.423.

A. K. Azis and K. Kustanto, “Penerapan Moving Average Pada Prediksi Penjualan Accu,” Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN), vol. 11, no. 1, p. 25, 2023, doi: 10.30646/tikomsin.v11i1.722.

P. E. Mujahid, M. P. Gultom, H. G. Lahagu, and I. Sinaga, “Penerapan Metode Trend Moment Dalam Memprediksi Harga Minyak Mentah Pada PT Asian Agri,” Teknik Informasi dan Komputer, vol. 6, pp. 627–632, 2023, doi: 10.37600/tekinkom.v6i2.930.

T. Fakhta Tri Nasution and A. Ridho Lubis, “Analisis Metode Trend Moment Sebagai Peramalan (Forecast) Penjualan UMKM Dimsum,” Januari, vol. 2023, no. 2, pp. 117–126, 2022.

M. U. Riyal et al., “Analisa Perbandingan Metode Trend Moment dan Regresi Linear dalam Prediksi Kurs Mata Uang Rupiah terhadap Mata Uang Riyal,” Journal of Computer System and Informatics (JoSYC), vol. 6, no. 3, pp. 563–571, 2025, doi: 10.47065/josyc.v6i3.7400.

F. M. Putri, “Tingkat Peramalan Penjualan Produk Bordir dan Sulaman Menggunakan Metode Trend Moment,” Jurnal Informatika Ekonomi Bisnis, vol. 4, pp. 34–38, 2022, doi: 10.37034/infeb.v4i2.122.

Ines Saraswati Machfiroh and Cahaya Ayu Ramadhan, “Peramalan Penjualan Produk Cup 220 Ml Menggunakan Metode Least Square Pada PT. Panen Embun Kemakmuran Tahun 2022,” Jurnal MSA ( Matematika dan Statistika serta Aplikasinya), vol. 10, no. 2, pp. 17–24, 2022, doi: 10.24252/msa.v10i2.27870.

U. Habibah, R. R. Robby, and M. N. Qomaruddin, “Comparison of the Trend Moment and Naive Methods in Forecasting Gross Regional Domestic Product in Blitar Regency,” Eigen Mathematics Journal, vol. 5, no. 1, pp. 31–36, 2022, doi: 10.29303/emj.v5i1.121.

L. R. Amalia, W. Ramdhan, and W. M. Kifti, “Penerapan Metode Trend Moment Untuk Memprediksi Jumlah Pertumbuhan Penduduk,” Building of Informatics, Technology and Science (BITS), vol. 3, no. 4, pp. 566–573, 2022, doi: 10.47065/bits.v3i4.1396.

C. Oliviasandrea and M. Sukur, “Implementasi Metode Trend Moment Pada Sistem Pendukung Keputusan Peramalan Penjualan Truk,” Klik-Kumpulan Jurnal Ilmu Komputer, vol. 09, no. 03, pp. 402–415, 2022.

L. R. Amalia, W. Ramdhan, and W. M. Kifti, “Penerapan Metode Trend Moment Untuk Memprediksi Jumlah Pertumbuhan Penduduk,” Building of Informatics, Technology and Science (BITS), vol. 3, no. 4, pp. 566–573, 2022, doi: 10.47065/bits.v3i4.1396.


Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Penerapan Metode Trend Moment Dalam Sistem Forecasting Untuk Memprediksi Jumlah Penjualan Smartphone dan Aksesoris

Dimensions Badge
Article History
Submitted: 2025-06-20
Published: 2025-07-11
Abstract View: 583 times
PDF Download: 345 times
How to Cite
Louis, K., Sinaga, C., & Mujahid, P. (2025). Penerapan Metode Trend Moment Dalam Sistem Forecasting Untuk Memprediksi Jumlah Penjualan Smartphone dan Aksesoris. Journal of Information System Research (JOSH), 6(4), 1826-1836. https://doi.org/10.47065/josh.v6i4.7666
Issue
Section
Articles

Most read articles by the same author(s)