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All Journal Jurnal Samudra Ekonomi dan Bisnis Jurnal Tekinkom (Teknik Informasi dan Komputer)
Andreas Andreas
Universitas Prima Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Peran Return on Equity, Debt to Equity Ratio dan Cash Ratio dalam Mempengaruhi Dividend Payout Ratio pada Perusahaan Go-Publik Sektor Barang Konsumsi Tahun 2014-2018 Meliana Meliana; Wirda Lilia; Siska Siska; Andreas Andreas
Jurnal Samudra Ekonomi dan Bisnis Vol 11 No 2 (2020)
Publisher : Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (555.79 KB) | DOI: 10.33059/jseb.v11i2.2117

Abstract

The study aims to analyze the role of Return on Equity, Debt to Equity Ratio and Cash Ratio in influencing Dividend Payout Ratio on go-public companies of consumer goods sector in the year of 2014-2018. This quantitative-desciptive research sourced from financial data on the Indonesia Stock Exchange website. 18 companies were selected as a sample purposively from 47 companies in the consumer goods sector that were members of the population. The results showed that partially, Return on Equity and Debt to Equity Ratio were proven to have a significant role in influencing Dividend Payout Ratio; while Cash Ratio is proven to have no significant effect on Dividend Payout Ratio. Simultaneously, Return on Equity, Debt to Equity Ratio and Cash Ratio were proven to have a significant role in influencing Dividend Payout Ratio.
PENERAPAN DATA MINING UNTUK PEMBUATAN PAKET PROMOSI PENJUALAN MENGGUNAKAN KOMBINASI FP-TREE DAN TID-LIST Saut Parsaoran Tamba; Albert William Tan; Yudi Gunawan; Andreas Andreas
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 4 No 2 (2021)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v4i2.309

Abstract

The manual preparation strategy of a promosi package can encounter difficulties in determining the right product to be promosited caused of no sales data analysis and the large size of sales database.The solution to this problem is to apply data mining science to find buying patterns that consumers often make in a collection of sales transactions, so that company can create the right promosi packages to encourage increased sales turnover. The study scanned the sales database obtained from the UCI maching learning repository and intelligent system dataset with 12,224 sales transaction records and 126,898 record of goods sold. Furthermore, the data mining process carries out the process of constructing an FP-Tree tree structure, constructing a conditional FP-Tree and TID List, then extracting a combination of items and calculating support (S), confidence (C) and sorting association rules based on the value of S x C descending, from the highest to the lowest value. The combination of FP-Tree and TID-List algorithms can be used to help formulate promosi package strategies, by analyzing the sales database and finding the most frequently sold combinations of items.
Co-Authors Albert William Tan Meliana Meliana Saut Parsaoran Tamba Siska Siska Wirda Lilia Yudi Gunawan