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Yunita -
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Library & Information Science Other

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ANALISIS KOMPARASI KUALITAS LABA SE BELUM DAN SESUDAH PENERAPAN STANDAR PELAPORAN KEUANGAN INTERNASIONAL (IFRS) PADA PERUSAHAAN MANUFAKTUR YANG TERDAFTAR DI BEI Yunita -; Zulbahridar -; Al Azhar Lukman
Jurnal Online Mahasiswa (JOM) Bidang Ilmu Ekonomi Vol 2, No 2 (2015): Wisuda Oktober 2015
Publisher : Jurnal Online Mahasiswa (JOM) Bidang Ilmu Ekonomi

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This research is to give empiris about comparation analyze of earnings quality before and after adoption of the international financial reporting standart. Main variable in this research is International Financial Reporting Standart (IFRS) and Earnings Quality. This research also use some free variable as Earning Management, Earning Persistence, also Profitability Ratio (Net Profit Ratio, Gross Profit Ratio and Operating Profit Ratio). Earnings Management refers to intervention to extern Financial Statement to get own profit. Earnings Persistence refers to expected future earning that implicated by current year earning . Net profit Ratio refers as comparison between net profit and sales. Gross Profit Ratio refers to comparison between gross profit and sales. Operating profit Ratio refers to comparison between operating profit and sales.This research used sample of manufacturing company that listed in BEI for four years (2010-2013). This research used convenience sampling method. Research Tool used secondary .This research data using Paired T-Test by SPSS (Statistic Product and Service Solution) 22. The result of this research showed that comparison analyze from variable- variable Earnings Management, Earnings Persistence, Net Profit Margin Ratio, Gross Profit Margin Ratio and Operating Profit Margin Ratio before and after adoption IFRS has no difference at all.Keywords: IFRS, Earning Quality, Earning Management, Earning Persistence, Profitability Ratio.
Implementasi Metode Fuzzy Simple Additive Weighting (Fuzzy - Saw) Dalam Sistem Pendukung Keputusan Dengan Pendekatan Variabel Benefit Dan Cost Danny Matthew Saputra; Rusdi Efendi; Yunita -
Jurnal Sistem Informasi Vol 10, No 2 (2018)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (383.863 KB) | DOI: 10.36706/jsi.v10i2.8056

Abstract

AbstrakDalam banyak kasus informasi ini kurang memadai untuk membuat sebuah keputusan yang spesifik guna memecahkan permasalahan tertentu. Oleh karena itulah Sistem Pendukung Keputusan dibuat sebagai suatu cara untuk memenuhi kebutuhan ini. Konsep sistem pendukung pengambilan keputusan yang berbasis komputer (computer based decision support system) saat ini sedang berkembang sangat pesat. Didalam proses pengambilan keputusan terdapat benyak kriteria yang digunakan, serta banyak juga metode yang bisa dipakai untuk mendapatkan solusi dari permasalahan tersebut. Metode yang akan dipakai dalam penelitian ini adalah fuzzy simple additive weighting, yang merupakan metode gabungan antara teori fuzzy dan metode penjumlahan bobot dalam system pendukung keputusan. Dalam metode ini terdapat dua bagian utama yang akan dibahas, yaitu proses pembobotan dan proses perengkingan. Dimana didalam proses pembobotannya terdapat proses normalisasi data yang membagi setiap variabel inputnya menjadi variabel benefit dan variabel cost. Adapun data uji yang akan digunakan sebanyak 120 buah data. Hasil perengkingan yang didapatkan dari metode ini nantinya akan dibandingkan dengan mengalikan nilai kepentingan data dengan data itu sendiri. Kata Kunci— Sistem Pendukung Keputusan, Metode Fuzzy SAWAbstractIn many cases this information is insufficient to make a specific decision to solve a particular problem. Therefore, Decision Support Systems are made as a way to meet these needs. The concept of computer-based decision support systems is currently developing very rapidly. In the decision making process there are a number of criteria used, as well as many methods that can be used to obtain solutions to these problems. The method that will be used in this research is fuzzy simple additive weighting, which is a combined method of fuzzy theory and weight sum method in decision support systems. In this method there are two main parts to be discussed, namely the weighting process and the cracking process. Where in the weighting process there is a data normalization process that divides each input variable into benefit variables and cost variables. The test data will be used as many as 120 pieces of data. The results of the cracking obtained from this method will be compared to multiplying the value of the importance of the data with the data itself Keywords- Decision Support System, Fuzzy SAW Method
Co-Authors Al Azhar Lukman Danny Matthew Saputra Rusdi Efendi Zulbahridar -