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Desain dan Implementasi Web Pemesanan Makanan untuk Mempercepat Proses Antrean Pelanggan Rifqi Putra Winanda; Nazwa Salsyabilla Ramadhani; Repi Meilani Putri; Nuriana Sipahutar
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 3 No. 6 (2025): November : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v3i6.781

Abstract

Lengthy, disorganized physical queues in conventional food ordering systems, particularly within canteens, significantly compromise customer convenience and operational efficiency. This direct-ordering model often results in crowd congestion, unpredictably long waiting times, and potential friction among patrons. To address these operational issues and substantially enhance user satisfaction, this research proposes the development and implementation of an innovative Web-Based Food Ordering System. This digital platform allows customers to place orders entirely online, effectively eliminating the need for physical queuing. The system's core functionality is the realtime monitoring of order status and queue position, providing transparent information directly to the customer's device. For canteen management, the application offers a crucial tool for integrated and structured order handling, ensuring staff can prepare meals more accurately and promptly. By transforming the ordering process into a streamlined digital workflow, the system is expected to accelerate the service cycle, minimize unnecessary crowding, and substantially improve customer satisfaction through a modernized, well-organized, and highly efficient experience. This initiative represents a significant step toward smarter and more responsive food service operations.
Implementasi Algoritma Shortest Path untuk Optimasi Rute pada Sistem Navigasi Lokasi Sirlia Sahid; Maissy Angelica Pakpahan; Rifqi Putra Winanda; Muhammad Raihansyah Lubis; Adidtya Perdana
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 4 No. 2 (2026): Mei : Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Profesi Telekomunikasi Dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v4i2.841

Abstract

The increasing complexity of urban road networks demands intelligent navigation systems capable of determining optimal routes efficiently. This research implements the Dijkstra Shortest Path algorithm to optimize route search on a location navigation system in Medan City. The system models a road network as a weighted graph comprising 57 strategic locations and over 90 road connections, represented using adjacency list data structures. The Dijkstra algorithm, implemented in Python using the heapq module for priority queue management, achieves an optimal time complexity of O((V+E) log V). The system features five main functions: shortest route search, popular routes, location listing, dynamic location addition, and dynamic road connection addition. System testing using a case study from Kualanamu Airport to the University of North Sumatra (USU) yielded an optimal route of 16.5 km through 4 road segments. Results demonstrate that the system successfully determines the most efficient route, provides accurate distance and travel time information for multiple transport modes (motorcycle, car, walking), and presents step-by-step journey guidance. This research contributes as a practical reference for applying shortest path algorithms in urban areas and serves as a foundation for developing more complex navigation applications in the future.
PEMANFAATAN ARTIFICIAL INTELLIGENCE DALAM PENULISAN TEKS PROPOSAL BAHASA INDONESIA: ANALISIS KOMPARATIF ERA PRA-AI DAN PASCA-AI Rifqi Putra Winanda; Naufal Aqiilah Asra; Muhammad Raihansyah Lubis; Mohd. Rafiif Albani
LANGUAGE : Jurnal Inovasi Pendidikan Bahasa dan Sastra Vol. 6 No. 3 (2026)
Publisher : Pusat Pengembangan Pendidikan dan Penelitian Indonesia (P4I)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51878/language.v6i3.11901

Abstract

ABSTRACT The rapid development of generative Artificial Intelligence (AI) in academic writing has created a need to examine its impact on the quality of Indonesian-language proposal texts. This study investigates the use of AI in proposal writing through a discourse analysis and comparative text approach. A descriptive qualitative method was employed by comparing four proposal drafts: two manually written proposals from the pre-AI era (2018–2019) and two proposals produced in the generative AI era (2024). The analysis focused on lexical-syntactic structure, orthography, contextual relevance of ideas, and operational validity. The findings indicate that AI-generated texts exhibit more systematic language structures and greater adherence to linguistic conventions but tend to present more generalized and less contextualized ideas. Manual editing of AI-generated texts gave rise to a hybrid error phenomenon, characterized by inconsistencies in writing that reflect weaknesses in the text integration and revision process. In contrast, proposals written entirely by humans demonstrated stronger performance in presenting technical details, timelines, and contextually relevant operational information. The study concludes that AI is most effective as a linguistic support tool, whereas technical planning, budget formulation, and the development of contextualized ideas still require human judgment and control. ABSTRAK Perkembangan Artificial Intelligence (AI) generatif dalam penulisan akademik mendorong perlunya kajian terhadap pengaruhnya pada kualitas teks proposal Bahasa Indonesia. Penelitian ini menganalisis pemanfaatan AI dalam penulisan proposal melalui pendekatan analisis wacana dan komparatif teks. Metode yang digunakan adalah kualitatif deskriptif dengan membandingkan empat draf proposal, terdiri atas dua proposal yang ditulis secara manual pada era pra-AI (2018–2019) dan dua proposal yang disusun pada era AI generatif (2024). Analisis dilakukan berdasarkan aspek leksikal-sintaksis, ortografi, kontekstualitas gagasan, dan validitas operasional. Hasil penelitian menunjukkan bahwa penggunaan AI menghasilkan struktur bahasa yang lebih sistematis dan sesuai kaidah, tetapi cenderung menghadirkan gagasan yang lebih umum dan kurang kontekstual. Penyuntingan manual terhadap teks AI memunculkan fenomena hybrid error, yaitu ketidakkonsistenan penulisan yang menunjukkan kelemahan dalam proses integrasi naskah. Sebaliknya, proposal yang ditulis sepenuhnya oleh manusia lebih unggul dalam menyajikan rincian teknis, linimasa, dan informasi operasional yang relevan. Penelitian ini menyimpulkan bahwa AI efektif sebagai pendukung aspek kebahasaan, sedangkan perencanaan teknis, penyusunan anggaran, dan pengembangan gagasan kontekstual tetap memerlukan kendali manusia.