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All Journal Teknika J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jusikom: Jurnal Sistem Informasi Ilmu Komputer Journal of Computer System and Informatics (JoSYC) Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) MEANS (Media Informasi Analisa dan Sistem) Journal of Computer Networks, Architecture and High Performance Computing Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) JINAV: Journal of Information and Visualization Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Pendidikan dan Teknologi Indonesia Journal La Multiapp Instal : Jurnal Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Sistem Informasi Bisnis (JUNSIBI) Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) Journal Of Informatics And Busisnes Jurnal Pengabdian Masyarakat
Yusuf Ramadhan Nasution, Yusuf Ramadhan
Universitas Islam Negeri Sumatera Utara Medan
Religion Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mathematics Social Sciences

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Journal : Journal of Computer System and Informatics (JoSYC)

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Prediksi Penjualan Produk Pepsodent Unilever dengan Algoritma K-Nearest Neighbor Maulida, Dzikra; Nasution, Yusuf Ramadhan
Journal of Computer System and Informatics (JoSYC) Vol 5 No 4 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i4.5718

Abstract

In the era of globalisation and increasingly fierce market competition, companies are striving to improve their operational efficiency and marketing strategies to maintain market share and increase revenue. PT Unilever Tbk, as one of the multinational companies that operates various types of consumer products, including dental care products such as Pepsodent, requires reliable sales prediction to maximise its product performance in the market. The main objectives of this research are to apply the K-Nearest Neighbor method to Unilever pepsodent products in a prediction model that can preprocess pepsodent product data for the last 1 year using Rapid Miner and to measure the accuracy of Pepsodent product sales predictions. The data used is the number of stocks, types of pepsodent, sales, seasonal factors. From the results of analysis and evaluation, it can be concluded that the prediction accuracy in the K-NN algorithm is able to provide fairly accurate sales predictions for Pepsodent Whitening products with a value of 161, 186, 165 equally 114. Pepsodent Economy with a value of 982 predictions 1021, a value of 638 and 774 predictions are both 927. Pepsodent Herbal with a value of 173 predicted 193 and a value of 129 and 118 predicted values are both 207. Accurate sales predictions are helpful in production planning and marketing strategies, which in turn can improve operational efficiency and customer satisfaction. The K-NN algorithm proved to be effective in this case, although proper selection of the K parameter is essential to obtain the best results.
Co-Authors Akbar, Muhammad Zidan Al Farizi, Alif Ayu Siregar, Silviana Budiarti, Dinda Fadillah, Rini Fani, Try Fikri, Muhammad Ihsanul Harahap, Ahdi Alfein Hasibuan, Maria Hikmah Heri Santoso Hutabarat, Fatur Padilla Idris Siregar, Idris Ilka Zufria Lbs, Rahma Tania Mawaddah Maulida, Dzikra Mhd Furqan Muhamad Alda Muhammad Siddik Hasibuan Pasaribu, Defri Ananda Prananda, Dimas Raka Prayoga, Dio Putri, Ajeng Kiana Rahim, Fitra Raissa Amanda Putri Ramadhan, Gema Rangkuti, M. Naufal Riyadi, Bagas Yowan Rizqi Hanafi Parapat Sari, Shella Fahdila Sibarani, Fathiya Hasyifa Sinaga, Meri Suhardi Supiyandi Supiyandi Wahyu Arli Wahyu Ramadhan Wiranti, Yuke