Document Type : Articles
Authors
1 National Research and Innovation Agency
2 IPB University
Abstract
R&D is one of the key drivers of technological progress and contributes to increased productivity and profit growth. Indonesian percentage of Gross Domestic Expenditure on R & R&D (GERD) to GDP in 2018 is one of the Global Competitiveness Index indicators, only reaches 0.28% and is dominated by the government sector, while the industrial sector is only 7.34%. One of the reasons for this small value is that the data collection of R&D on the business sector in Indonesia has not been carried out optimally. A classification model is needed to determine the data collection target so that the results are more optimal. The main objective of this study is to classify R&D industries actors in Indonesia using XGBoost and then analyze the features for R&D industries actors using SHAP. XGBoost is one of the black-box models that is difficult to interpret, and SHAP is one of the interpretation methods. The classification results using XGBoost obtained the accuracy, AUC, and F1-Score values of 79.61%, 0.7646, and 84.44%, respectively. Based on the Shapley value of the SHAP method, it was found that the average growth in R&D expenditure had the highest contribution. The feature's contribution to the estimation will be even higher if the mean of R&D expenditure growth is higher (more than 0). The other one is the ratio of researchers to R&D human resources. If the ratio is more than 75%, it will negatively contribute. Finally, exports and State-Owned Enterprise (BUMN) feature with the smallest contribution.https://dorl.net/dor/20.1001.1.20088302.2022.20.2.4.9
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