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All Journal Jurnal Teknik Informatika (JUTIF) J-EDu : Journal - Erfolgreicher Deutschunterricht Koli Journal: English Language Education German für Gesellschaft (J-Gefüge) Gaba-Gaba
Maruanaya, Rita Fransina
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Journal : Jurnal Teknik Informatika (JUTIF)

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DEVELOPMENT OF A STOCK PURCHASE RECOMMENDATION SYSTEM APPLICATION Maruanaya, Greghar Juan Tjether; Triyono, Gandung; Maruanaya, Rita Fransina
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2322

Abstract

Investing in stocks has become a significant source of passive income through indirect earnings with minimal activity. Choosing stocks for investment requires careful analysis. The Indonesia Stock Exchange has 866 listed stocks, divided into several indices, including IDXBUMN20, which includes 20 stocks from state-owned enterprises (BUMN), regional-owned enterprises (BUMD), and their affiliates. This index helps traders monitor the performance of BUMN stocks. The list of IDXBUMN20 stocks includes ADHI, ANTM, BBNI, AGRO, BBRI, BRIS, BBTN, BJBR, BMRI, MTEL, ELSA, JSMR, PGAS, PTBA, PTPP, SMGR, TINS, TLKM, WIKA, and WSKT. Traders need recommendations to select stocks with positive trends. Forecast analysis becomes a potential solution to provide references for stocks with positive trends. This study applies the Simple Moving Average (SMA) method to forecast the prices of IDXBUMN20 stocks. The SMA will be measured using 30, 40, 50, and 60-day periods as indicators. This method is chosen for its ability to identify stock price trends by calculating the average closing price over a specific period. Therefore, forecasting results using SMA will provide a more accurate picture of stock price movements and aid in making better investment decisions. From the forecasting results using the SMA method, recommendations for the top five stocks showing positive trends will be obtained. Subsequently, to determine which stock is most recommended, a stock recommendation model will be developed using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. TOPSIS will consider various criteria such as average frequency, Price Earning Ratio (PER), Price Book Value (PBV), Return on Assets (ROA), and Return on Equity (ROE). The results showed that the most recommendable stocks based on the positive trend of price movements are SMGR for indicator 30 and TLKM for indicators 40, 50 and 60. Therefore, it can be concluded that the most recommended stock is TLKM (PT Telkom Indonesia (Persero) Tbk).This recommendation model is expected to help traders select the stocks with the best investment potential, maximizing profits and minimizing investment risks in the capital market.
Co-Authors Apituley, Patresia Silvana Haryanto, Didik Jamlean, Alexander Delvan Karuna, Kalvin Khammounty, Bounseng Lewier, Christian Albert Maruanaya, Greghar Juan Tjether Meunmany, Santiphap Pattikawa, Meytty Jeanly Piet Soumokil Sitaniapessy, Marcelina Soyem, Abraham Titaley, Febrio Triyono, Gandung Tuhumena, Wilhemina Ascaria Warandy, Sundary Wilma Akihary