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All Journal Journal of Computer System and Informatics (JoSYC) Jurnal Pengabdian Masyarakat
Maulida, Dzikra
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Religion Computer Science & IT Decision Sciences, Operations Research & Management Education Industrial & Manufacturing Engineering Library & Information Science Social Sciences

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The Incoming Mail Management System Design and Exit at the General Bureau of the Web Based Governor's Office Maulida, Dzikra; Siregar, Nora Arianti; Hasugian, Abdul Halim
Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2023): Desember 2023
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v2i2.83

Abstract

Incoming mail archiving is still stored in a general ledger sorted by date and the incoming mail filing process only stores mail files in the general ledger so that if the mail file is lost and if the file is needed again, the mail will be difficult to find. The method used to design the Correspondence Management Information System is the waterfall method. The result is a data processing system that can be run properly. Thus it can be known whether this software can produce information system applications that are in accordance with the expected goals. With the design of this application, it is expected to facilitate the company in the process of collecting correspondence starting from the identity of the letter, the time of receipt of the letter to the destination of the letter.
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 Abdul Halim Hasugian Siregar, Nora Arianti Yusuf Ramadhan Nasution, Yusuf Ramadhan