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Analisis Kinerja Keuangan Perusahaan dengan Menggunakan Economic Value Added (EVA) dan Market Value Added (MVA) Studi pada Perusahaan Telekomunikasi yang Terdaftar di Bursa Efek Indonesia (BEI) Periode 2007-2011 Rosihana, Athiy Dina; lendro, Har
Jurnal Ilmiah Mahasiswa FEB Vol. 1 No. 2
Publisher : Fakultas Ekonomi dan Bisnis Universitas Brawijaya

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Abstract

Competition in the business world so that more and more stringent assessment of the company's performance be measured by the success of a company. Assessment of the company's performance is measured by using the method of (Economic Value Added) and EVA (Market Value Added) MVA using data from income statements and balance sheets,  stock market returns, stock prices, stock index, the number of shares outstanding, and SBI. Telecommunications sector to attract the object of research for the development of this sector is very rapid. In addition, people are now very dependent to telecommunications companies because of the convenience offered by them. EVA two companies generated positive (+) indicates that the company has managed to create wealth for shareholders and the company. MVA both companies is positive (+) means that the management  has been able to increase the wealth of the company and its shareholders and the financial performance of the company is in good condition. Keyword : Financial Performance, Economic Value Added, Market Value Added
Implementation of Expert System Applications using Forward Chaining to Detect Dental Health Zahra , Zahra; Melyani, Melyani; Yusuf, Faif; Herawati, Metty Titin; Royanti, Suci; Rosihana, Athiy Dina
Journal of Management and Informatics Vol. 4 No. 3 (2025): December Season | JMI: Journal of Management and Informatics
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jmi.v4i3.212

Abstract

Dental diseases remain one of the most common health issues globally, often resulting from a lack of early detection and limited access to dental specialists. This research presents the implementation of an expert system that uses forward chaining to diagnose dental health conditions based on user-reported symptoms. The system integrates a knowledge base modeled from expert consultation with dentists, consisting of symptom sets and rule-based logic. Findings indicate that the Forward Chaining approach is effective for step-by-step rule evaluation and generates accurate diagnoses of diseases such as caries, gingivitis, periodontitis, halitosis, and pulpitis. The study demonstrates that expert systems can support preliminary dental screening and improve public awareness of dental health.