Analisis Pengaruh Rasio Profitabilitas Terhadap Zakat Pada PT. Bank Muamalat Indonesia
Bibliographic record
Abstract
ABSTRAK Lembaga Keuangan Syariah termasuk PT. Bank Muamalat Indonesia dan laporan keuangan ditentukan besamya zakat perusahaan sebab dalam Islam salah sam tujuan pelaporan keuangan adalah untuk keperluan zakat. Hal ini berarti berorientasi pada zakat yaitu perusahaan berusaha untuk mencapai angka pembayaran zakat yang tinggi, dengan deinikian laba bersih tidak lagi menjadi tolak ukuran kinerja perusahaan. Orientasi pada zakat bukan berarti perusahaan melupakan mencari laba dad sisi ekonoinis, tetapi pencapaian laba yang maksimal adalah sasaran antara dan pencapaian zakat adalah tujuan akhirnya. Penelitian ini dilakukan untuk mengetahui dan meneliti faktor-faktor yang sekiranya berpengarub secara statistik signifikan terhadap zakat. Faktor-faktor tersebut, sebagai variabel independen adalah Return on Assets (ROA), Return on Equity (ROE), Loan Deposit Ratio (LDR), Current Ratio (CR), Debt to Assets Ratio (DtAR) dan Equity Multiplier (EM). Sedangkan sebagai variabel dependen adalah zakat. Teknik pengambilan sample dilakukan dengan metode purposive sampling, dengan data berupa laporan iriwulan perusahaan path 31 Desember 1993 — 31 Desember 2000. Pengolahan dan analisis data menggunakan teknik analisis regresi linier berganda dengan bantuan program SPSS 10,0 for Windows. Hash pengujian regresi linier berganda menunjuickan babwa secara simultan faktor-faktor Return on Assets (ROA), Return on Equity (ROE), Loan Deposit Ratio (LDR), Current Ratio (CR), Debt to Assets Ratio (DtAR) dan Equity Multiplier (EM) berpengarub secara statistik signifikan terhadap zakat, alcan tetapi secara parsial hanya Current Ratio (CR) dan Debt to Assets Ratio (DtAR) saja yang berpengarub secara statistik signifikan terhadap zakat. Variabel kinerja keuangan rnempunyai pengarub yang doininan terhadap zalcat. ini sesuai dengan teori bahwa untuk pencapaian kinerja keuangan yang balk akan membuat zakat baik juga. Kata Kunci : Zakat, ROA, ROE, ROOA ABSTRACT Syariab Financial Intitution include PT. Bank Muamalat Indonesia base on financial statement as their zakat, because in Islam the goal of financial statement is for zakat purpose. It means the company oriented in zakat, so the company tries to reach high zakat payment. Net profit is not to be perfomance evaluation but zakat. It doesn’t mean that the company neglects to find profit econoinically, but the maximal achievement of profit is intermediate goals and zakat is the ultimate goals. This research is to know what factors inight give significant and statistical influence. Those factors, as independent variables are Return on Assets (ROA), Return on Equity (ROE), Loan Deposit Ratio (LDR), Current Ratio (CR), Debt to Assets Ratio (DtAR) and Equity Multiplier (EM). While a dependent variable is zakat. The technique of sampling uses purposive sampling method and data was collected from 3 1-12-1993 till 31-12-2000. The data process and analysis uses the technique of multiple linear regression, using SPSS 10,0 for Windows program. The result of multiple linear regression shows that Return on Assets (ROA), Return on Equity (ROE), Loan Deposit Ratio (LDR), Current Ratio (CR), Debt to Assets Ratio (DtAR) and Equity Multiplier (EM) give significant and statistical influence to zakat simultaneously, but partially only the Current Ratio (CR) and Debt to Assets Ratio (DtAR) give significant and statistical influence to zakat. Financial perfomance variable has the doininant effect to zakat. This is suitable to the theory that to achieve the good financial perfomance makes the good zakat too. Key Words Zakat, Return on Assets, Return on Equity, Return on Operation Assets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".