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All Journal INFORMATIKA
Purwati Purwati
Universitas Sains dan Teknologi Komputer
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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PERANCANGAN MODEL HYBRID EXPLAINABLE ARTIFICIAL INTELLIGENCE BERBASIS IOT DAN MACHINE LEARNING UNTUK OTOMATISASI SISTEM INVENTORY DAN DETEKSI RISIKO KECURANGAN PADA PERUSAHAAN Sumaryanto Sumaryanto; Purwati Purwati; Setiyo Prihatmoko
Informatika: Jurnal Teknik Informatika dan Multimedia Vol. 6 No. 2 (2026): Oktober : JURNAL TEKNIK INFORMATIKA DAN MULTIMEDIA
Publisher : LPPM Politeknik Pratama Kendal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/informatika.v6i2.1964

Abstract

Inventory management in companies faces several challenges, including inaccurate stock records, delayed information, overstocking or stock shortages, and the risk of fraud. This study aims to design a Hybrid Explainable Artificial Intelligence model based on the Internet of Things (IoT) and Machine Learning to automate inventory management systems and detect fraud risks. The proposed model integrates IoT sensor data, inventory transactions, supplier data, and incoming and outgoing goods data. Machine Learning is used to predict stock requirements and detect abnormal transaction patterns, while Explainable Artificial Intelligence (XAI) is employed to provide explanations of the prediction results and risk levels generated by the model. The proposed model is expected to improve inventory monitoring accuracy, detect potential fraud, and support faster, more transparent, and data-driven decision-making.  
Co-Authors Setiyo Prihatmoko Sumaryanto