The Sukuk (shariah bond) market is developing in Indonesia and potentially will capture the global market in the future. It is an attractive investment product and a hot current issue in the capital market. Especially, the problem of predicting an accurate and trustworthy rating. As the Sukuk market developed, the issue of Sukuk rating emerged. As ordinary investors will have difficulty predicting their ratings going forward, this research will provide solutions to the problems above. The objective of this study is to determine the Indonesian Sukuk rating determinants and comparing the Sukuk rating predictive model. This research uses Artificial Neural Network (ANN) and Multinomial Logistic Regression (MLR) as the predictive analysis model. Data in this study are collected by purposive sampling and employing Sukuk rated by PEFINDO, an Indonesian rating agency. Findings in this study are debt, profitability and firm size significantly affecting Sukuk rating category and the ANN performs better predictive accuracy than MLR. The implications of the results of the research for the issuer and bondholder are a higher level of credit enhancement, a higher level of profitability, and the bigger size of firm rewarding higher Sukuk rating.

中文翻译：

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多项逻辑回归和人工神经网络在预测伊斯兰债券评级中的有效性：来自印度尼西亚证券交易所的证据

回教债券（回教债券）市场正在印度尼西亚发展，未来可能会占领全球市场。它是一种极具吸引力的投资产品，也是当前资本市场的热门话题。特别是预测准确和可信评级的问题。随着 Sukuk 市场的发展，Sukuk 评级问题应运而生。由于普通投资者将难以预测他们未来的评级，本研究将为上述问题提供解决方案。本研究的目的是确定印度尼西亚 Sukuk 评级的决定因素并比较 Sukuk 评级预测模型。本研究使用人工神经网络 (ANN) 和多项逻辑回归 (MLR) 作为预测分析模型。本研究中的数据是通过有目的的抽样和采用 PEFINDO 评级的 Sukuk 收集的，印尼评级机构。本研究的结果是债务、盈利能力和公司规模显着影响 Sukuk 评级类别，并且 ANN 比 MLR 具有更好的预测准确性。研究结果对发行人和债券持有人的影响是更高水平的信用增强，更高的盈利水平，以及奖励更高伊斯兰债券评级的公司规模更大。