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All Journal Journal of Software Engineering, Information and Communication Technology Informatics and Computer Engineering Journal
Sunaryo, Gregorius Christian
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Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Fastest Route for Public Health Center in Bandung with Dijkstra Algorithm and FP-Growth Recommendation in C++ Programming Language Kurnia, Andika Eka; Sunaryo, Gregorius Christian; Zamzami, Muhammad Rafi; Melany, Naila; Nugraha, Rafi Nazhmi; Ariyanti, Rahma Dina
Journal of Software Engineering, Information and Communication Technology (SEICT) Vol 5, No 1: June 2024
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/seict.v5i1.71212

Abstract

This research addresses the need for efficient public health center access in Bandung. In this case study, the solution to that specific problem is implemented using the C++ programming language. Consequently, extreme programming is chosen as the research methodology. We implemented Dijkstra's algorithm to find the shortest routes and the FP-Growth algorithm to recommend frequently visited health centers based on previous history. By leveraging C++ for its performance advantages, the system maps urban villages and calculates optimal paths. Additional features manage village data, create routes, and display health center information. The combined use of these algorithms enhances navigation and healthcare access in urban settings, though future work should consider real-time traffic conditions.
Implementasi Prediksi Stok Barang Menggunakan Algoritma Support Vector Regression (SVR) pada Marketplace UMKM Berbasis Microservices Sunaryo, Gregorius Christian; Rafi Nazhmi Nugraha; Muhammad Shandy Winata; Muhammad Rafi Zamzami; Maryam Silva Rahayu; Rahma Dina Ariyanti; Nidda Adzkya Nurfitria
Informatics and Computer Engineering Journal Vol 6 No 1 (2026): Periode Februari 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/icej.v6i1.11508

Abstract

Penelitian ini menangani tantangan kritis manajemen inventaris pada Usaha Mikro, Kecil, dan Menengah (UMKM) dengan mengimplementasikan modul prediksi stok menggunakan algoritma Support Vector Regression (SVR) dalam arsitektur Microservices. Menggunakan kerangka kerja CRISP-DM, penelitian ini memproses data historis penjualan melalui rekayasa fitur sliding window dan transformasi logaritma untuk menangani pola permintaan non-linear. Sistem dirancang dengan memisahkan fungsi operasional berbasis Node.js dan mesin komputasi AI berbasis Python. Pemisahan ini bertujuan untuk meningkatkan skalabilitas dan performa aplikasi. Hasil evaluasi menunjukkan bahwa model SVR dengan kernel Radial Basis Function (RBF) mencapai Root Mean Square Error (RMSE) sebesar 3.57 dan koefisien determinasi ($R^2$) sebesar 0.64, membuktikan kemampuannya dalam memberikan rekomendasi stok yang akurat dan berbasis data. Solusi yang diusulkan mampu memitigasi risiko overstock dan stockout serta mendorong perubahan manajemen inventaris dari proses manual yang bersifat reaktif menuju sistem otomatis yang lebih proaktif., serta meningkatkan efisiensi operasional dan keberlanjutan finansial bagi UMKM.
Co-Authors Ariyanti, Rahma Dina Kurnia, Andika Eka Maryam Silva Rahayu Melany, Naila Muhammad Rafi Zamzami Muhammad Shandy Winata Nidda Adzkya Nurfitria Nugraha, Rafi Nazhmi Rafi Nazhmi Nugraha Rahma Dina Ariyanti Zamzami, Muhammad Rafi