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All Journal Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara)
Kustanto Kustanto
STMIK Sinar Nusantara
Computer Science & IT

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Prediksi Penjualan Produk Promo PT. Unilever, Tbk Menggunakan Metode Fuzzy Time Series Yehoshua Yehoshua; Kustanto Kustanto; Retno Tri Vulandari
Jurnal Informa : Jurnal Penelitian dan Pengabdian Masyarakat Vol 6 No 2 (2020): Desember
Publisher : Politeknik Indonusa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46808/informa.v6i2.184

Abstract

PT. Unilever is a multinational company headquartered in Rotterdam, the Netherlands (under the name Unilever N.V.), London, England (under the name Unilever pic.) And in Indonesia has a subsidiary, PT. Unilever, Tbk was established on December 5, 1933. Unilever produces food, drinks, cleaners, and also body care. Unilever is the third largest producer of household goods in the world, if based on the amount of revenue in 2012, behind P & G and Nestle. In forecasting products, it is often influenced by the sale of these products because there are also changes in sales for each period. Usually there is an increase in sales of these products which, among other things, is caused by price discounts, new products, one free one to buy promo, or a saving package from Unilever or from a rival company. Data collection method used by the author is a method of observation or directly observing the process of transmission, interview methods and literature study methods. While the method for processing data uses fuzzy time series algorithms, context diagrams, data flow diagrams, HIPO, relational diagram entities, data dictionary design, input design, output design, relation diagrams between tables, system implementation and testing. The method for implementation uses vb.net and Mysql. The results of this thesis are a system for calculating the forecasting amount of sales or sales of promo products for the following year. From this system, information on store data, item data, sales year history data, and forecasting data from fuzzy time series data will be displayed.. From rinso goods promotion data which have been calculated using fuzzy time series method which get MAPE value equal to 3,2%, so sales data for category of goods will experience increase based on calculation equal to 3,2%.
PENERAPAN ALGORITMA APRIORI PADA SISTEM REKOMENDASI BARANG DI MINIMARKET BATOX Nur Fitrina; Kustanto Kustanto; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 6, No 2 (2018): Jurnal TIKomSiN
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2700.804 KB) | DOI: 10.30646/tikomsin.v6i2.376

Abstract

Recommendations are application models from previous measurement of data and information. To process data that is quite a lot is used the right method. Association rules are one technique that can be used in associating indirect data from a data. The purpose of this study is to create a system that can be used to provide information on goods in accordance with consumer combinations. The method used is direct interviews with staff to get information in the form of sales data and system requirements. The design model uses the System Development Life Cycle (SDLC), namely Analysis, Design, Construction, Implementation, and Testing. The system design method used is UML (Unified Modeling Language). The system used is an algorithm that is made web-based using the language PHP and MySQL as databases. The results used in this study are to stop at the specified 2-item iteration and two rules that meet minimum 30% support rules and a minimum confidence of 70%, namely Cofemix → Sugar and Sugar → Sugar.
Co-Authors Nur Fitrina Retno Tri Vulandari Yehoshua Yehoshua