Article Per Year (5 Year)
p-Index From 2021 - 2026
3.096
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Dasar AKSIOMA: Jurnal Program Studi Pendidikan Matematika Jurnal Sains Matematika dan Statistika Jurnal Matematika Sains dan Teknologi Jurnal Aplikasi Statistika & Komputasi Statistik INSIST (International Series on Interdisciplinary Research) Buguh: Jurnal Pengabdian Kepada Masyarakat Jurnal Siger Matematika Sciencestatistics: Journal of Statistics, Probability, and Its Application Advance Sustainable Science, Engineering and Technology (ASSET)
Khoirin Nisa
Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, University Of Lampung
Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

Published : 22 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 22 Documents
Search

 1   2   3 
A Hybrid AI–SEMPLS Model for Digital Visualization Acceptance in Blue Tourism: Evidence from Lampung Province Debby Alita; Khoirin Nisa; Styawati; Dina Amelia
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i2.2909

Abstract

Blue tourism destinations often lack advanced digital tools capable of providing real-time, AI-driven visualization and user-centered information services. This study addresses this gap by developing JELAMBU, an AI-enabled digital visualization platform, and by evaluating user acceptance through a hybrid SEMPLS models. The research aims to: (i) design and implement an AI-based system that combines chatbot interaction, realtime sentiment analytics, and digital visualization; and (ii) examine the determinants of tourists’ intention to adopt AI-enabled e-tourism technologies. A structured questionnaire was administered to 467 visitors of destinations, and 16 hypotheses were tested. The results show that platform design, facilitating conditions, AI technology, perceived ease of use, perceived usefulness, social influence, service quality, trust, and risk perception significantly shape intention to use, whereas information quality, perceived benefits, and performance expectancy do not show significant effects. The model demonstrates substantial predictive power (R² = 0.703), strong effect sizes (f² > 0.225), and acceptable fit (SRMR = 0.084). These findings highlight the pivotal role of design and system conditions in AI-driven tourism platforms and provide practical guidance for developers and policymakers in strengthening digital visualization, personalization features, and sustainable blue tourism management. Future studies may extend this framework to multi-regional settings or longitudinal adoption scenarios.
Modeling Air Quality Index in Indonesia Using Smoothing Splines and Truncated Splines Regression Nadhia Az Zahra; Khoirin Nisa; Misgiyati Misgiyati; Nusyirwan Nusyirwan
Jurnal Matematika Sains dan Teknologi Vol. 26 No. 2 (2025)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v26i2.14574.2025

Abstract

The Air Quality Index (AQI) is a composite indicator that reflects regional air quality conditions and is influenced by multiple determinants with complex and nonlinear relationships. In such circumstances, parametric regression may be restrictive because it requires a predetermined functional form. This study applies spline based nonparametric regression using smoothing splines and truncated splines to model AQI in Indonesia and to compare the performance of both approaches. AQI is treated as the response variable, while population density, land cover area within and outside forest areas, and the number of motor vehicles are considered as predictor variables. For smoothing splines, the optimal smoothing parameter is selected using Generalized Cross Validation, whereas truncated splines are estimated using Ordinary Least Squares under various knot configurations and selected based on the minimum Generalized Cross Validation value. Model performance is evaluated using Generalized Cross Validation, Mean Squared Error, and Adjusted R squared. The study aims to identify the most appropriate model and to determine key factors influencing AQI variation in Indonesia, thereby providing empirical support for environmental policy making. The results show that the smoothing spline model provides better performance than the truncated spline model, with a lower Mean Squared Error (MSE) of 0.0716 and a higher Adjusted R² of 0.794. These results indicate that smoothing splines are more effective in capturing the nonlinear relationships influencing AQI variation in Indonesia.
Co-Authors Aditya Putra Pradana Agus Sutrisno Agus Sutrisno Ahmad Faisol Alita, Debby Deta Erviana Dina Amelia Dorrah Azis Eri Setiawan Eri Setiawan Eri Setiawan Fifi Nurhafifah Hilda Venelia Juanda Juanda Misgiyati Misgiyati Misgiyati Mona Arif Muda Muhammad Luthfi Muslim Ansori Mustofa Usman Nadhia Az Zahra Naflah Faulina Netti Herawat Netti Herawati Netti Herawati Netti Herawati Netti Herawati Netti Herawati Netti Herawati Nusyirwan Nusyirwan Nusyirwan Nusyirwan Nusyirwan Nusyirwan Nusyirwan Pandri Ferdias Putri Apricia Rachma Adji Ramadanti Rizki Agung Wibowo Rizki Agung Wibowo Saidi, Subian Shabrina Novaindah Dwiyamti Siska Diah Ayu Larasati Sofalina Nodra Brilliantya Styawati Styawati subian saidi Tiryono Ruby Wardhani Utami Dewi Warsono Warsono Widiarti