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Implementasi Sistem ERP Modul Pos Dan Manajemen Karyawan di KB/TK Alfath Malang Apriyani, Meyti Eka; Hamdana, Elok Nur; Pamenang, M. Unggul; Pramudhita, Agung Nugroho; Aji, Deddy Kusbianto Purwoko; Zuraida, Vit
SWAGATI : Journal of Community Service Vol. 2 No. 3 (2024): November
Publisher : Universitas AMIKOM Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/swagati.2024v2i3.1673

Abstract

Pengabdian masyarakat ini dilaksanakan untuk mengatasi berbagai permasalahan yang dihadapi oleh TK Alfath, khususnya dalam hal kebutuhan akan sistem Point of Sale (POS) dan modul employee untuk manajemen administrasi yang lebih baik. Melalui program ini, dilakukan pendampingan kepada guru KB/TK Alfath selaku pemegang proses kegiatan. Selain itu, program ini juga mengembangkan dan implementasi sistem POS serta modul employee. Integrasi antara  POS dan Employee memiliki potensi besar untuk memudahkan pengelolaan persediaan, pemesanan barang, dan manajemen sumber daya manusia. Integrasi antara POS dan Employee akan menciptakan sistem yang terpadu, memungkinkan pemantauan yang lebih akurat terhadap pemesanan produk yang dibutuhkan dan manajemen karyawan yang lebih efisien. Tujuan dari program ini adalah untuk meningkatkan kualitas manajemen serta meningkatkan efisiensi operasional sekolah. Hasil dari program ini diharapkan dapat memberikan kontribusi positif terhadap peningkatan kualitas pendidikan di TK Alfath serta membantu dalam mengatasi berbagai permasalahan yang dihadapi.
Bahasa Inggris Usman Nurhasan; Dian Hanifudin Subhi; Anugrah Nur Rahmanto; Endah Septa Sintiya; Deddy Kusbianto Purwoko Aji
MULTITEK INDONESIA Vol 20 No 1 (2026): July (On Progress)
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/mtkind.v20i1.13681

Abstract

Automated evaluation of flowchart representations is essential for the facilitation of the acquisition of basic programming concepts. Nevertheless, traditional evaluation systems that rely exclusively on structural matching demonstrate some of their most fundamental limitations. The false negative misclassification rates of such systems are frequently high when students create visually distinct structures for algorithmic logic that are semantically equivalent. A hybrid assessment framework is introduced in this study to improve the reliability and efficacy of code evaluation in order to address this challenge. The model that has been proposed combines the probabilistic feature extraction capabilities of Graph Convolutional Networks (GCNs) with mathematical logic verification through symbolic execution of an SMT Solver. While the SMT Solver deterministically establishes functional equivalence, the GCN module adaptively manages graph topological variations. Use of a real-world dataset consisting of 3.600 flowcharts generated by novice students was implemented to assess the hybrid system's functionality. According to quantitative experimental results, the proposed framework obtained a peak F1 Score of 0.88, which is a substantial improvement over conventional Abstract Syntax Tree (AST) methods (F1 Score 0.75). Additionally, the 77.4% reduction in false negative rates was achieved by incorporating the SMT Solver in comparison to a pure GCN configuration. Finally, the semantic equivalence and structural divergence issues that arise during algorithm assessment are effectively resolved by this dual architectural integration. By implementing the proposed system, higher education institutions are equipped with a more dependable mechanism for reducing human error, thereby improving the impartiality, accuracy, and efficiency of the evaluation process.