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All Journal The IJICS (International Journal of Informatics and Computer Science) Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Tekinkom (Teknik Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) INFOKUM KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Media Teknik Elektro dan Komputer
Mujahid, Putra Edi
Universitas Prima Indonesia, Medan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Penerapan Metode Trend Moment Dalam Sistem Forecasting Untuk Memprediksi Jumlah Penjualan Smartphone dan Aksesoris Kevin Louis; Christina Julia Sinaga; Putra Edi Mujahid
Journal of Information System Research (JOSH) Vol 6 No 4 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i4.7666

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.
Co-Authors Albert Pratama Sembiring Albert Pratama Sembiring Andri Syahputra Tarigan Arthur William Christina Julia Sinaga Erika Girsang Fertomedis, Ridho Lukas Gultom, Maju Parsaoran Hasibuan, Muhammad Fikry Hasrul Jansen Yudistira S Meliala Jansen Yudistira Sembiring Meliala Jodi Daniel Pransisko Manalu Johan Tanaro Kevin Louis Lahagu, Hasrat Gideon Manik, Rosianni Maya Frida Panjaitan Nababan, Marlince Nurzanah, Laila Okta Jaya Harmaja Rendy Christian Riyandi Riyandi Rudi Yanto Ryan Chandra Saut P Tamba Simbolon, Junpri Sardodo Sinaga, Indah Sinaga, Maria Riska Ratna Sari Siti Aisyah Soselisa, Yopie Lahardo Tambunan, Daniel Partogi Verli Vernando S Colia Villa Delfya Sarumaha Willy, Willy