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Ircham Ali
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Nusantara Journal of Artificial Intelligence and Information Systems
Published by Universitas Nahdlatul Ulama Indonesia
ISSN : 30908876     EISSN : 30908302     DOI : https://doi.org/10.47776/nuai
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Nusantara Journal of Artificial Intelligence and Information Systems (NUAI) publishes high-quality research and review articles that advance the theory and application of Artificial Intelligence (AI) and Information Systems (IS) across industry, government, academia, and research institutions. The journal focuses on innovative approaches in human–AI interaction, machine learning, intelligent systems, data engineering, computer vision, natural language processing, data analytics, blockchain-based systems, and other emerging AI technologies, as well as on the design, development, implementation, and evaluation of information systems including software engineering, software quality assurance, decision support systems, health and accounting information systems, IT governance and audits, spatial and geographic information systems, smart city information systems, socio-technical perspectives, enterprise systems, and the role of information systems in developing countries. NUAI welcomes contributions that provide theoretical insights, practical solutions, and interdisciplinary perspectives that strengthen the integration and advancement of AI and information systems.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 15 Documents
 1   2 
Web-Based Gym Membership System with Semi-Automated QRIS Verification Developed Through Agile-Scrum Ragel Trisudarmo; Anisa Ramdhani; Dila Mardiyanti; Nabila Anggi Permatasari
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 2 No. 1 (2026): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v2i1.1904

Abstract

Gym membership administration that depends on manual processes is correlated with elevated rates of recording inaccuracies, protracted payment verification periods of membership status. This study presents the development and evaluation of a web-based gym membership information system at TGW Gym, Indonesia, integrating semi-automated QRIS payment verification through the Agile-Scrum framework. The system was built using Laravel and MySQL across five iterative sprints, encompassing member registration, package selection, QRIS payment proof upload, administrator verification, and membership renewal modules. Functional validation used black-box testing across all modules with eight test scenarios spanning the package selection, payment, and renewal pages. Performance metrics were obtained through structured pre and post-implementation observation over 15 transaction cycles. Black-box testing confirmed that all functional requirements were satisfied. Following implementation, the task success rate reached 92%, error rates decreased from 15-20% to 3-5%, and verification time fell from 10-15 minutes to 2-5 minutes per transaction. The system usability scale score of 78 (Grade B, Good) confirmed acceptable usability. The novelty lies in combining admin payment verification, an expiry-aware renewal workflow, and a semi-automated QRIS flow within a single architecture, a combination not present in prior gym management systems.
Development and Quality Evaluation of a Web-Based Drug Inventory System for Pharmacy Management Heru Budianto; Leni Nur Angraeni; Nanda Haipah Nabila; Muhamad Fikri
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 2 No. 1 (2026): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v2i1.1933

Abstract

Manual drug inventory management in pharmacies that rely on spreadsheets is prone to stock recording errors, unmonitored expiration dates, and reporting delays, and these problems compound as the drug variety and transaction volume grow. This study developed a web-based drug inventory system for pharmacy operations using the Waterfall model and evaluated its quality through Black Box Testing and User Acceptance Testing (UAT). Black Box Testing across thirteen test scenarios confirmed that every feature functioned according to its specification. UAT involved two pharmacy users, a pharmacy manager and an administrative staff member, who evaluated the system across nine criteria after operating its core functions in the actual work environment. The total UAT score was 71 out of 72, an overall average of 98.61%, classified as Very Good. One criterion, the stock depletion and expiry alert feature, scored 87.50% and was the only result below the maximum, pointing to notification responsiveness as the main area for further work. The system is functionally sound and well-received in this operational context, with the caveat that the two-respondent sample limits broader generalizability. Unlike prior pharmacy IS studies that handle stock recording, sales, or expiry management separately, this system combines batch-level tracking, automated expiry alerts, and integrated reporting in one platform designed for small pharmacy operations.
Mapping Generative AI Ethics in Higher Education: A Systematic Review and Multidimensional Boundary Framework Nio Awandha Nehru; Nik Haryanti
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 2 No. 1 (2026): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v2i1.1993

Abstract

The rapid integration of generative artificial intelligence in higher education has generated a fundamental dilemma: does it function as a learning aid or as an academic shortcut? This study employs a qualitative systematic literature review guided by PRISMA procedures to map the ethical spectrum of generative AI use between cognitive augmentation and academic substitution. Thirty-eight core journal articles published between 2021 and 2026 were thematically synthesized. The findings indicate that generative AI can enhance learning when it supports metacognitive reflection, scaffolding, and self-regulated learning while preserving human evaluative control. Conversely, risks emerge when AI contribution replaces core cognitive labor, leading to authorship ambiguity, integrity violations, and superficial engagement. To reconcile these tensions, this study proposes a multidimensional ethical boundary framework structured along two dimensions: human cognitive engagement and level of AI contribution. This framework offers a conceptual basis for policy development, assessment redesign, and responsible pedagogical integration, positioning ethical AI use as a continuum grounded in sustained human intellectual accountability.
Sentiment Analysis of Emotional Intensity as a Continuous Driver of Engagement and Algorithmic Visibility Zia Ul Rehman Zafar; Dedi Gunawan; Muhammad Saif
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 2 No. 1 (2026): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v2i1.2006

Abstract

This study investigates how emotional intensity, rather than sentiment direction, shapes engagement and algorithmic visibility in digital political discourse. Using sentiment analysis, a dataset of about 15,000 posts from Twitter (X) and YouTube was collected over a 30-day period and scored with a hybrid TextBlob, VADER, and BERT pipeline. Emotional strength (the absolute sentiment value) correlated moderately with engagement (r = 0.58, p < 0.05), whereas the directional sentiment score did not (r ≈ 0.05). Emotionally intense posts attracted about 2.4 times more engagement than neutral posts, and positive posts were the most frequent (41%) while neutral posts drew the lowest mean engagement. These results indicate that engagement-based ranking amplifies emotional magnitude over neutral or analytical content, which can narrow the diversity of visible expression. The findings give platform designers and policymakers a reproducible basis for assessing how affective dynamics shape visibility in algorithmically mediated public discourse.
A Fuzzy Multi-Criteria Decision-Making Framework for Soil-Based Cultivation Block Selection in Citrus Orchards Adi Yusuf Arrasyid; Oka Ardiana Banaty; Adrinoviarini Adrinoviarini; Niken Ayu Widya Ningrum
Nusantara Journal of Artificial Intelligence and Information Systems Vol. 2 No. 1 (2026): June
Publisher : Faculty of Engineering and Computer Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47776/nuai.v2i1.2065

Abstract

Selecting the optimal cultivation block in a multi-plot citrus orchard is a hard multi-criteria problem when the soil criteria mix categorical and numerical measurements. Descriptors like Munsell color, soil structure, and consistency sit alongside numerical pH, and conventional agronomic assessment offers no systematic way to weigh them against each other. This study builds a decision support system (DSS) that pairs the fuzzy analytic hierarchy process (FAHP) with two ranking methods, TOPSIS and Simple Additive Weighting (SAW). A rule-based triangular fuzzy number (TFN) protocol first converts the categorical descriptors into numerical inputs through documented rules. Field data came from seven plots across five citrus variety blocks at IP2SIP Tlekung, BRMP Jestro, Batu, East Java, covering texture, structure, color, consistency, and pH. FAHP weights gave a consistency ratio (CR) of 0.0446. Both TOPSIS and SAW ranked plot A1 (Keprok Batu 55 II, 4-year stand) first and A2 (Keprok Batu 55 I, 15-year stand) last, with Spearman ρ = 0.8929 (p = 0.0068). The top and bottom ranks were held across all 10 sensitivity scenarios. The framework gives orchard managers a reproducible way to prioritize block-level soil intervention, marking A1 as the benchmark block and A2 as the priority for pH correction.

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