Pengembangan Multimodal Artificial Intelligence Financial Assistant dalam Rekomendasi Pembelian Otomatis pada UMKM Kopi Menceng
Abstract
Coffee micro, small, and medium enterprises (MSMEs) require integrated inventory and financial management to ensure that raw-material purchasing decisions align with operational demand and budget constraints. Manual recordkeeping may result in delayed purchases, excess inventory, or stockouts. This article presents the design of a Multimodal Artificial Intelligence Financial Assistant to support automated purchasing recommendations for Kopi Menceng MSME. The proposed system is designed to accept text-based inputs and, as an optional feature, transaction data extracted from receipt images or documents. Validated data are processed alongside inventory levels, material requirements, prices, and budget limits to generate recommended purchase quantities and estimated costs. The development follows a prototyping approach comprising requirements identification, design, prototype construction, evaluation, and refinement. Proposed evaluation methods include black-box testing, recommendation-error measurement, and user assessment. Since actual implementation data have not been included, numerical examples in this article serve as simulations rather than field-test results. This design is intended to provide a foundation for developing a more structured purchasing decision-support system for MSMEs.
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Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
Program Studi Teknik Informatika, Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
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