A Conceptual Design of an Expert System for Halal Product Verification with Machine Learning-Based Rule Refinement
Keywords:
Expert system, Rule refinement, Machine learning, Decision supportAbstract
Current research methods in halal tourism predominantly rely on conventional surveys, which are prone to bias. This study advances traditional methods by analyzing authentic, real-time user-generated data from 8,943 Google Maps reviews, employing a computational approach that combines Natural Language Processing and data visualization for sentiment categorization. The analysis covers three categories religious tourism, halal culinary, and Muslim-friendly accommodations across three prominent provinces for halal tourism in Indonesia: Aceh, West Nusa Tenggara, and DKI Jakarta. The methodology involved data collection, processing using a lexicon-based method to categorize sentiments as positive, negative, or neutral, and subsequent data visualization. Key findings indicate that tourist sentiment is significantly dominated by positive reviews, with religious tourism consistently receiving the highest satisfaction. Specific positive keywords such as “enak” (delicious) for culinary and “bersih” (clean) for accommodation were identified, alongside universal complaints such as “salah” (wrong). This study confirms that a visualization-based sentiment categorization approach is effective in transforming raw reviews into actionable strategic insights for tourism stakeholders.References
[1] M. Abdel-Basset, R. Mohamed, M. Elhoseny, F. Chiclana, and A. N. H. Zaied, “A hybrid multi-criteria decision-making model for sustainable supplier selection using blockchain and Internet of Things technologies,” J. Clean. Prod., vol. 276, pp. 123–234, 2020.
[2] M. Amin and A. B. A. Hamid, “Halal food certification and business performance: The moderating role of firm reputation,” J.Islam. Mark., vol. 10, no. 4, pp. 1013–1028, 2019.
[3] S. Barakat and M. Al-Emran, “Applications of artificial intelligence in halal industry: A systematic review,” IEEE Access, vol. 9, pp. 125190–125205, 2021.
[4] C. Bernard and K. Cho, “Rule-based expert systems: Concepts, applications, and challenges,” Expert Syst. Appl., vol. 165, p.113918, 2021.
[5] T. Chakraborti, S. Sreedharan, and S. Kambhampati, “Explainable AI: Interpreting black-box machine learning models,”Commun. ACM, vol. 63, no. 11, pp. 68–77, 2020.
[6] N. M. Daud, A. Zainal, and M. Ali, “Trends and challenges in halal logistics: A global review,” J. Islam. Account. Bus. Res.,vol. 11, no. 4, pp. 889–910, 2020.
[7] R. Hassan, N. A. Rahman, and A. A. Samad, “Expert systems for halal verification: A review of existing approaches and limitations,” Int. J. Adv. Comput. Sci. Appl., vol. 10, no. 7, pp. 145–152, 2019.
[8] M. A. Hussain and C. Dawson, “Economic impact of halal certification systems,” World Appl. Sci. J., vol. 21, no. 12, pp.1687–1693, 2013.
[9] I. O. for Standardization, “ISO/IEC 25010: Systems and software engineering — Systems and software quality models,”ISO/IEC, 2018.
[10] M. H. Kamali, Shariah law: An introduction. Oneworld Publications, 2019.
[11] M. U. Indonesia, “HAS 23000: General Guidelines for Halal Assurance System,” MUI, 2020.
[12] S. and M. I. for I. Countries, “OIC/SMIIC 1: General requirements for halal food,” OIC/SMIIC, 2019.
[13] N. A. Rahman, S. Ahmad, and H. Zulkifli, “Halal supply chain standards and regulations in Southeast Asia,” J. Islam. Mark.,vol. 8, no. 4, pp. 683–700, 2017.
[14] M. Roushdy, S. El-Sayed, and D. Ahmed, “An Expert System for Diagnosing Eye Diseases Using CLIPS,” Int. J. Adv.Comput. Sci. Appl., vol. 2, no. 6, pp. 64–70, 2011.
[15] A. A. Samejo, A. Javed, and J. Zain, “Machine learning-based rule extraction and refinement for decision support systems,”Expert Syst., vol. 39, no. 3, p. e12848, 2022.
[16] F. Shahzad and M. I. Malik, “Artificial intelligence in halal industry: Opportunities, challenges, and future directions,” J.Islam. Bus. Manag., vol. 11, no. 1, pp. 1–15, 2021.
[17] S. R. Yahaya, H. Hashim, and M. N. Saad, “Enhancing halal certification through blockchain technology,” J. Halal Ind. Serv.,vol. 2, no. 1, pp. 1–10, 2019.
[18] H. Zainuddin and R. Selamat, “Halal food traceability using IoT: A conceptual framework,” Int. J. Adv. Sci. Eng. Inf. Technol.,vol. 10, no. 2, pp. 520–525, 2020
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