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All Journal Jurnal Proaksi Enrichment : Journal of Management International Journal Software Engineering and Computer Science (IJSECS)
Fitriya Sari
Universitas Muhammadiyah Cirebon
Computer Science & IT Economics, Econometrics & Finance Education

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PENGARUH RETURN ON ASSET DAN ARUS KAS UNTUK MEMPREDIKSI KONDISI FINANCIAL DISTRESS Fatahillah Fatahillah; Fitriya Sari
Jurnal Proaksi Vol 4 No 1 (2017): Januari-Juni
Publisher : Fakultas Ekonomi, Universitas Muhammadiyah Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32534/jpk.v4i1.577

Abstract

This study aimed to examine the effect of the Return On Asset (ROA) and the cash flow for prediction of financial distress in the company go public manufacturing basic chemical industry sector. This study was a descriptive study with a quantitative approach. Samples are six publicly traded companies included in the basic chemical industry sub-sector with the study period 2009-2013. The six companies are PT. Asahimas Flat Glass Tbk, PT. Arwana Citra Mulia Tbk, PT. Ceramic core Alamasri Industry Tbk, PT. Assosiasi Keramika Indonesia Tbk, PT. Industrindo Mulia Tbk and PT. Surya Toto Indonesia Tbk. This study uses secondary data obtained from the annual financial statements published by the company on the Indonesian Stock Exchange website. Data analysis technique used by logistic regression. The results of this study prove that the ROA and cash flow have a significant effect in predicting the company'sfinancial distress. The information value of profit after tax (EAT) has the ability to predict financial distress in a company. This is demonstrated by the significant values are under 0.05. The information value of cash flow (CF) has no significant effect. It is seen from the logistic regression test value of 0.938 which means that cash flow information does not have the ability to predict financial distress of a company.
Financial performance analysis at PT. Japfa Comfeed Indonesia Tbk, 2017-2019 : Surono Surono; Mohamad Djadjuli; Itat Tatmimah; Fitriya Sari; Muzayyanah Muzayyanah
Enrichment : Journal of Management Vol. 12 No. 6 (2023): February: Management Science And Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/enrichment.v12i6.1051

Abstract

Financial performance is a description of the company's financial condition in a certain period, both regarding the aspects of raising funds and channeling funds which are usually measured by indicators of capital adequacy. Therefore, to be able to measure financial performance in companies usually use financial ratio. Financial ratios commonly used in companies such as liquidity ratio, solvency ratio, profitability ratio, activity ratio and investment ratio. However, this study only uses three financial ratio, namely liquidity ratio, solvency ratio and profitability ratio. Based on the research results, the results of the analysis of the liquidity ratio, solvency ratio and profitability ratio in the company have fluctuated or are still unstable in each period because they have increased and decreased in each period.
Personalized Marketing Strategy in Digital Business Using Data Mining Approach Yusnidar Yusnidar; Dudi Yudhakusuma; Fitriya Sari
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 2 (2023): AUGUST 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i2.1515

Abstract

The integration of personalized marketing strategies and data mining techniques in the realm of digital business has garnered significant attention in recent years. This study employs a mixed-methods approach to explore the dynamics between personalized marketing and data mining, specifically investigating customer perceptions and behavior in the Lhokseumawe and Cirebon regions. Through in-depth interviews, 80 respondents' views on personalized marketing were analyzed, highlighting both positive sentiments regarding tailored campaigns and concerns over data privacy. Furthermore, quantitative analysis was conducted using data from platforms such as WhatsApp, Instagram, TikTok, and Shopee Ecommerce. This revealed distinct customer segments, yielded improved product recommendations, and uncovered interesting purchasing patterns. The results emphasize the importance of striking a balance between personalization benefits and privacy protection. By harnessing the insights provided by data mining, businesses can enhance customer engagement and satisfaction, ultimately navigating the dynamic digital landscape more effectively. This study contributes practical implications and strategic insights for businesses seeking to optimize their digital marketing strategies.
Co-Authors Dudi Yudhakusuma Fatahillah Fatahillah Itat Tatmimah Mohamad Djadjuli Muzayyanah Muzayyanah Surono Surono Yusnidar Yusnidar