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All Journal Morfologi : Jurnal Ilmu Pendidikan, Bahasa, Sastra dan Budaya Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika
Repi Meilani Putri
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Arts Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media

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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.
Optimasi Alokasi Sumber Daya Bantuan Sosial : Pendekatan Algoritma Greedy dan Analisis Komputasi Maulana Al Nouri; Tia Risky Yasmin Saketang; Repi Meilani Putri; Paskal Arienda Epidonta Ginting; Adidtya Perdana
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 4 No. 3 (2026): Mei: Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v4i3.1556

Abstract

The distribution of social assistance in Indonesia faces challenges such as inaccurate recipient data, overlapping programs, and limitations of traditional data management systems that lead to inaccurate targeting of aid. This study proposes a social assistance distribution optimization system using the Greedy algorithm that assesses recipient priorities based on economic conditions, number of family members, location, and urgency of needs with certain weights to produce objective rankings. This system is implemented in a JavaScript-based web application without external frameworks, making it lightweight and easily accessible. Simulations with 20 prospective recipients and a quota of 10 slots and validation with a dataset of 10,000 entries show that the Greedy algorithm produces identical results to Dynamic Programming but is much faster (669 times faster). In terms of complexity, this algorithm has O(n log n) time and O(n) space, and meets the requirements of the Greedy Choice Property and Optimal Substructure, making it a practical and efficient solution for managing large-scale social assistance distribution in Indonesia.
Ragam Bahasa Indonesia dalam Prompt AI: Studi Komparatif Gaya Respons ChatGPT Sirlia Sahid; Maissy Angelica Pakpahan; Mika Monika Fransiska Simanullang; Repi Meilani Putri
Morfologi : Jurnal Ilmu Pendidikan, Bahasa, Sastra dan Budaya Vol. 4 No. 3 (2026): June: Morfologi : Jurnal Ilmu Pendidikan, Bahasa, Sastra dan Budaya
Publisher : Asosiasi Periset Bahasa Sastra Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/morfologi.v4i3.2699

Abstract

This study examines the influence of standard (baku) and non-standard (informal) Indonesian language in prompt construction on the response style and structure generated by ChatGPT. The proliferation of generative AI in Indonesia presents a gap: most users interact with AI using everyday informal language, while the effect on AI response characteristics remains understudied. Using a comparative qualitative approach, two prompt variants formal standard language and informal non-standard language were tested on an identical object: an internet service package (HOME ODS, 100 Mbps, Rp150,000/month). Responses were evaluated across five dimensions: structure, completeness, analytical depth, register alignment, and practical utility. Findings show that formal-language prompts yield more hierarchically organized and elaborated responses, while informal prompts elicit concise, conversational responses marked by emoji and colloquial tone. Both prompt types produced substantively comparable information, indicating that language variety primarily shapes response style rather than content depth. These findings suggest ChatGPT adapts its register to match user input, a behavior consistent with statistical pattern prediction inherent to large language models (LLMs). Implications for Indonesian language education and AI literacy are discussed.
Co-Authors Adidtya Perdana, Adidtya Maissy Angelica Pakpahan Maulana Al Nouri Mika Monika Fransiska Simanullang Nazwa Salsyabilla Ramadhani Nuriana Sipahutar Paskal Arienda Epidonta Ginting Rifqi Putra Winanda Sirlia Sahid Tia Risky Yasmin Saketang