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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Ecotrophic, Journal of Environmental Science KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 Journal of Computer Networks, Architecture and High Performance Computing J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan Resi: Jurnal Riset Sistem Informasi
Ida Ayu Utari Dewi
Universitas Hindu Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Environmental Science Health Professions Public Health

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Pemetaan Sebaran Nasabah Kredit di Lembaga Perkreditan Desa Adat Mengwitani Berbasis Sistem Informasi Geografis (SIG) Menggunakan Python Yajmana, Dewa Gede Indra; I kadek Andy Asmarajaya; Ida Ayu Utari Dewi
RESI : Jurnal Riset Sistem Informasi Vol. 4 No. 1 (2025): Resi Juli 2025
Publisher : Program Studi Sistem Informasi, Fakultas Teknologi Informasi dan Sains, Universitas Hindu Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32795/6mp4mc07

Abstract

Lembaga Perkreditan Desa (LPD) is a microfinance institution owned by traditional villages in Bali, which provides savings and loan services to the community. This study aims to design and develop a Geographic Information System (GIS) to map the distribution of credit customers at LPD Desa Adat Mengwitani. The system was developed using the Waterfall model, which includes the stages of analysis, design, implementation, and testing. The technology used includes the Python programming language with the Flask framework and the Folium library for interactive map visualization. Customer data is stored in a MySQL database and connected using SQLAlchemy. System testing was carried out using the black box testing method, and the results showed that the system performed well without any bugs. The final product is a web-based application that displays an interactive map with customer location markers and customer information in popups. This system helps LPD monitor customer distribution visually and supports decision-making related to credit service and management. 
Transformasi Bisnis di Era Digital: Peran Strategis Kecerdasan Buatan dalam Inovasi dan Keunggulan Bersaing I Putu Putra Astawa; Ida Ayu Utari Dewi
RESI : Jurnal Riset Sistem Informasi Vol. 4 No. 1 (2025): Resi Juli 2025
Publisher : Program Studi Sistem Informasi, Fakultas Teknologi Informasi dan Sains, Universitas Hindu Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32795/n78xst47

Abstract

Digital transformation has become a major driving force in the changing landscape of modern business. This study aims to examine the strategic role of artificial intelligence (AI) in supporting innovation and achieving competitive advantage in the digital era. Using a qualitative descriptive approach based on a literature review, this study analyzes various empirical and theoretical findings related to the implementation of AI in a business context. The results indicate that AI plays a crucial role in process automation, big data analysis, and improving the quality of consumer-oriented decision-making. In addition to driving operational efficiency, AI also opens up opportunities for product innovation and new, more adaptive, customer-driven business models. However, the implementation of AI is not without challenges such as digital infrastructure readiness, human resource competency gaps, and issues of data ethics and regulation. Therefore, integrating AI into business strategy requires a holistic, collaborative approach based on responsible governance. This research provides conceptual and practical contributions in designing AI-based digital transformation strategies, while also serving as a reference for policymakers and business actors to strengthen sustainable competitiveness.
Rancang Bangun Sistem Informasi Manajemen Bimbingan Skripsi Mahasiswa (SIMBISA) Berbasis Web Menggunakan Framework CodeIgniter 4 (Studi Kasus: Prodi Sistem Informasi UNHI) Putri Pertiwi, Ni Kadek Sri Ayu; Noppi Adi Jaya, I Kadek; Utari Dewi, Ida Ayu
RESI : Jurnal Riset Sistem Informasi Vol. 4 No. 2 (2026): Resi Januari 2026
Publisher : Program Studi Sistem Informasi, Fakultas Teknologi Informasi dan Sains, Universitas Hindu Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32795/8bqej783

Abstract

The utilization of information technology in academic management continues to evolve to support the efficiency and quality of higher education services. In the Information Systems Study Program at UNHI, the thesis supervision process is still conducted through several separate platforms, such as Google Forms and messaging applications, which leaves room for improvement in terms of effectiveness through a unified system that integrates the entire process. This study aims to design and develop a web-based Thesis Supervision Management Information System (SIMBISA) to facilitate a more structured and efficient supervision process. The system was developed using the waterfall method and the CodeIgniter 4 framework, while system testing was conducted using the blackbox testing method. The development results show that SIMBISA is capable of facilitating the submission of research topics, supervision scheduling, revision uploads, and the submission of proposal and thesis documents in an organized and well-documented manner. In addition, the system provides easy access to information for students and supervisors to monitor supervision progress. Blackbox testing results indicate that all features function according to user needs, making the system effective in supporting a comprehensive and integrated thesis supervision process. With the implementation of SIMBISA, thesis supervision management is expected to become more systematic, accountable, and accessible at any time throughout the process.
Prediksi Stunting Berbasis Machine Learning melalui CERDIS: Cepat Resposif Deteksi Dini Stunting Indriana, Ni Putu Riza Kurnia; Dewi, Ida Ayu Utari; Darmayanti, Putu Ayu Ratna
J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan Vol 7 No 1 (2025): December
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/j-remi.v7i1.6486

Abstract

Stunting is a condition with long-term impacts on cognitive function and productivity, thus requiring accurate early detection to support effective interventions. This study aims to develop a machine learning–based stunting prediction application using the Support Vector Machine (SVM) algorithm, integrated into mobile and web-based systems. The development method follows the CRISP-DM framework to ensure a structured data mining process and incorporates the Behaviour Change Wheel (BCW) to encourage positive user behaviour change. A dataset of approximately 121,000 records obtained from Kaggle was used for model training. Evaluation using black-box testing demonstrated that the application achieved excellent system, information, and service quality, with a benefit score of 98%. The application was shown to improve diagnostic efficiency, enhance the accuracy of stunting risk identification, and support the acceleration of early intervention efforts in primary healthcare centres (Puskesmas). Its implementation is expected to contribute to reducing stunting prevalence and advancing the digital transformation of primary healthcare services. It is recommended that future development focus on optimising healthcare worker training, improving the user interface, and expanding system integration and service coverage to maximise application effectiveness.
Co-Authors A A Ayu Wulan Agustini Anak Agung Putu Ngurah Andika Adnyana Gede Surya Mahendra I Dewa Kadek Laksana Digita I Kadek Andy Asmarajaya I Kadek Noppi Adi Jaya I Made Sukayana I Putu Putra Astawa I Wayan Arthana I Wayan Brata Mertha, I Made Buana Ni Putu Riza Kurnia Indriana Noppi Adi Jaya, I Kadek Oky Sanjaya, Kadek Putri Pertiwi, Ni Kadek Sri Ayu Putu Ayu Ratna Darmayanti Takahiro Osawa Trisnawati, Ni Komang Adi Wardana, I Putu Mahendra Adi Yajmana, Dewa Gede Indra