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Smart Sustainable Cities: Digital Communication and Information Literacy in Jakarta and Bandung Nurkhalila Fajrini; Irla Yulia; Enggar Mulyajati; Pratiwi Anindita Adji
Jurnal Dakwah dan Komunikasi Vol. 11 No. 2 (2026): In Progress
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/jdk.v11i2.17931

Abstract

Purpose − The development of smart cities in Indonesia has accelerated in an effort to enhance urban sustainability through the integration of information and communication technology (ICT). This study adopts the smart sustainable city framework to examine digital communication transformation and information literacy challenges in Jakarta and Bandung. It aims to explore the implementation of digital communication strategies and identify barriers to information literacy in supporting sustainable urban development. Method − This study employed a qualitative comparative case study approach. Data were collected through semi-structured interviews, direct observations, and document analysis, and were analyzed using thematic analysis to identify patterns in digital communication practices and information literacy challenges. Findings − The findings reveal that Jakarta optimizes digital technology for public service delivery through the JAKI application, while Bandung emphasizes a collaborative and community-based approach through the Bandung Sadayana platform. In addition to these differences in implementation strategies, both cities face similar challenges: a digital literacy gap, uneven public participation, and limitations relating to digital inclusion. The study concluded that the success of smart cities depends not only on the use of technology but also on strengthening information literacy, increasing inclusive citizen participation, and fostering collaboration between the government, the community, and other stakeholders in order to achieve sustainable urban development.
Visualizing Uncertainty in AI-Assisted Canine Acute-Pain Assessment: Dog-Grouped Risk Modeling and Information-Equivalent Interface Prototypes Chole Zhao; Evelyn Liu; Zijian Cao
International Journal of Graphic Design Vol. 3 No. 1 (2025): May | IJGD: International Journal of Graphic Design
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/ijgd.v3i1.4272

Abstract

Canine acute-pain assessment combines behavioral observation, clinical context, and professional judgment, yet a model probability can be mistaken for a clinical pain score when the two lack a clear visual hierarchy. This study linked retrospective prediction-model findings to three information-equivalent interface prototypes. The structured database contained 594 observations from 184 dogs; 114 complete acute-pain observations from 65 dogs formed the primary cohort, with the short-form Glasgow Composite Measure Pain Scale (CMPS-SF) ≥ 6/24 as the reference outcome. A hypothetical pre-score feature set excluded direct score components, although the database did not establish recording order. Four calibrated models were evaluated with five repetitions of four-fold dog-grouped nested cross-validation. Logistic regression achieved an area under the receiver operating characteristic curve (AUROC) of .627 (95% CI [.474, .755]), an area under the precision–recall curve (AUPRC) of .476 [.317, .660], and Brier score .210 [.174, .249]. Sensitivity at 0.50 was .189, missing 30 of 37 threshold-positive observations. Full-development bootstrap fits supplied 90% model-stability ranges, distinct from patient-outcome intervals. Exploratory routing reduced Brier score but also reduced AUROC and changed retained event prevalence. An auxiliary vocabulary analysis identified 169 descriptors in 52 grouped rows. A separate transit-display analysis of 12,331 records from 299 participant identifiers did not establish an average payoff or duration advantage over a no-uncertainty display. The numeric dashboard, visual scale, and progressive evidence card retained identical information while varying hierarchy and disclosure. Their structural audit establishes content equivalence, not clinical effectiveness. The design contribution connects model limitations to visible range definitions, separate clinical-reference labels, missing-context cues, and a persistent structured-assessment action.
Detection of Climate Change and Sustainable Accounting Practices in Environmental Accounting Information Systems: Through International Accounting Standards in South Sumatra Hertati, Lesi; Suharman, Harry; Umar, Haryono; Iskak, Jamaludin; Nopriansyah, Arief
Jati: Jurnal Akuntansi Terapan Indonesia JATI Vol 9, No 2: October 2026
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jati.v9i2.25378

Abstract

This study aims to examine the sustainability disclosure of illegal oil mining practices from the perspective of IFRS S1 and IFRS S2 sustainability accounting related to sustainability risks and climate change through an environmental accounting information system. The novelty of this study lies in the integration of IFRS Sustainability Disclosure Standards with the phenomenon of illegal oil mining, which has so far been limitedly studied in environmental accounting and accounting information systems literature. The study adopted identifying emerging patterns through interviews, observations, focus group discussions (FGDs), and supporting documents related to illegal oil mining practices, and understanding the phenomenon in depth. The research informants consisted of 20 people, including illegal oil miners, communities around mining sites, local government officials, and community leaders, based on their experience and involvement in illegal oil mining activities in Musi Banyuasin, Indonesia. The results of the study disclosed that illegal oil mining activities have been oriented toward short-term economic profits without considering environmental sustainability, climate risk management, and ecological accountability. The main findings revealed that environmental damage increased the risk of ecosystem damage, environmental pollution, public health problems, and climate change. In addition, weak supervision and the absence of an environmental accounting information system made these activities difficult to control. This research provides input for policymakers and stakeholders in strengthening natural resource oversight, enhancing environmental accountability, and developing environmental accounting information systems that support sustainable development goals. Theoretically, this research extends the sustainability accounting literature by linking illegal economic practices, climate risk, and IFRS S1 and IFRS S2 standards in a developing country context.
Measuring the Financial Information Quality for Decision-Making in Regional Fiscal Policy: A Case from Indonesia Suprayitno; Mabrur, Azas; Nanang Nugroho, Muhammad; Azhar
Jati: Jurnal Akuntansi Terapan Indonesia JATI Vol 9, No 2: October 2026
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jati.v9i2.31070

Abstract

The allocation policy of fund transfer from the central government to regional governments requires reliable regional financial information. The Regional Financial Information System produces the required information. The quality of regional fiscal policy depends on the reliability of financial information. This research aims to explore the important characteristics of financial information attributes produced by SIKD and how to measure those attributes to determine the quality of financial information. A qualitative method was adopted, particularly a case study of SIKD implementation in the central government. The results identified several important attributes regarding information quality that the system must ensure, encompassing accuracy, completeness, timeliness, ease of understanding, and up-to-dateness. In addition, the measurement of information quality should utilize the data stored in the database, especially for assessing accuracy, completeness, timeliness, and up-to-dateness. Meanwhile, the understandability attribute should be measured by a user perception survey.
Effect of e-HRM Transformation, HR Quality Development, and Information Technology on Organizational Performance Halimatussaadah halimatussaadah
Greenation International Journal of Tourism and Management Vol. 1 No. 2 (2023): (GIJTM) Greenation International Journal of Tourism and Management (June - Augu
Publisher : Greenation Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/gijtm.v1i2.21

Abstract

A scientific article from a literature study titled "Transformation of e-HRM in Information Technology-Based HR Quality Development on Organizational Performance" aims to develop a research hypothesis on the impact of variables to be used in additional research, within the context of management information systems. This paper was written using the library research approach, with information from online academic databases like Google Scholar, Mendeley, and others. As a consequence of this article, it has been determined that: 1) e-HRM transformation; 2) HR Quality Development; and 3) Information Technology all have an impact on organizational performance.
The Effectiveness of Using Human Resource Information System on the Performance of Employees at Hermina Arcamanik Hospital Sani Fitriyani; Kelvin Herlambang H; Muhammad Prakarsa Al Qadr Saleh; Candra Mecca Sufyana
Greenation International Journal of Tourism and Management Vol. 2 No. 2 (2024): (GIJTM) Greenation International Journal of Tourism and Management (June - Agus
Publisher : Greenation Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/gijtm.v2i2.227

Abstract

To remain competitive in the health industry and streamline performance, an efficient human resource management system is essential. This research employs a qualitative approach with a case study design, gathering data through semi-structured interviews and direct observation. The findings reveal that Human Resource Information System (HRIS XPRESSO), implemented in 2019, offers features such as managing employee personal data, training records, and integrating recruitment and payroll processes. This system has significantly enhanced HR department performance by simplifying data access and reducing manual processes. However, challenges such as large file rejections, server disruptions, and limited access outside the hospital were identified. To enhance effectiveness, feature improvements and access adjustments are necessary. In conclusion, HRIS XPRESSO has proven effective in boosting HR operational efficiency but requires ongoing evaluation and institutional reforms to address existing challenges and fully leverage its benefits for the organization.
Medical Information Release Application Design Using Design Thinking And Heuristic Evaluation At Private Hospital In Bumi Serpong Damai Nerissa Adha Andrania; Anastasia Cyntia Dewi Kurniawati; Hosizah Hosizah; Siswati Siswati
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 5 (2026): JUTIF Volume 7, Number 5, October 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.5.5653

Abstract

Medical information release processes in Indonesian hospitals often suffer from data inconsistency, process delays, and weak coordination, while simultaneously operating under strict regulatory and privacy requirements. This study designs a user interface (UI) for a medical information release application using a Design Thinking methodology encompassing empathize, define, ideate, prototype, and test phases. The resulting high‑fidelity prototype adopts a dual‑pathway architecture that separates navigation flows for patients/third parties and Health Information Management (HIM) personnel, and integrates 13 core features aligned with Indonesian Ministry of Health Regulation No. 24/2022, IFHIMA recommendations, and HIPAA security principles such as minimum necessary disclosure, role‑based access control, audit trail, and informed consent. Gestalt design principles are applied to optimize perception, reduce cognitive load, and support safe handling of sensitive medical data. Usability was evaluated through heuristic assessment with 22 criteria and a 0–4 severity rating scale by three expert evaluators, yielding an average Severity Rating of 1.26, categorized as cosmetic problems without impact on core functionality or user satisfaction. The prototype therefore offers both operational effectiveness and regulation-aligned security, providing a reference framework for health informatics in designing medical information release systems for highly regulated healthcare environments.
Agile-Based Development and System Usability Scale Evaluation of a Web-Based Daycare Information System for Parental Engagement Ni Made Rai Masita Dewi; I Gusti Agung Ayu Sekarini; Ni Made Ayu Juli Astari; I Gede Putra Mas Yusadara
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 5 (2026): JUTIF Volume 7, Number 5, October 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.5.5674

Abstract

The study employed an Agile-based system development approach supported by Unified Modeling Language (UML). Functional validation was conducted using black-box testing to ensure system conformity with user requirements. Usability evaluation was performed using the System Usability Scale (SUS) after the system had been used operationally for three months by 25 respondents representing various user roles. Parental engagement was measured using an adapted instrument contextualized to the use of a daycare information system. The results showed that the system achieved a SUS score of 82, which falls into the Good and acceptable category, while the mean parental engagement score reached 4.37, indicating a high level of engagement. These findings suggest that the system provides a good level of usability and is capable of supporting active parental participation in monitoring children’s development. The scientific contribution of this study lies in providing an integrated evaluation framework that combines Agile-based development, standardized usability measurement, and user engagement analysis within a real operational context. This study extends usability research beyond technical interface evaluation toward understanding user engagement within digital information service systems.
Retrieval-Augmented Generation Chatbot Using Gemini AI for Public Internship Information Services Ihda Nur Maulidia Hanum; Ajib Susanto; Miftakhul Ashfania
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 5 (2026): JUTIF Volume 7, Number 5, October 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.5.5788

Abstract

Chatbot is a technology designed to assist humans by simulating text or voice based conversations to provide efficient information services powered by Artificial Intelligence. This study addresses the difficulties prospective interns face in finding internship information at the Central Java Regional Police and the lack of prompt responses from office staff, which often results in delays in information delivery due to manual processing. Many prospective applicants also feel confused about how to inquire regarding the registration process, required qualifications, and other important details. To address these issues, this research was conducted to develop a web-based internship system equipped with an advanced chatbot implementing the Retrieval Augmented Generation (RAG) method and integrated with a vector database for semantic retrieval. This platform ensures that all information provided is relevant and accurate by providing real-time responses based on the agency’s official documents. Based on functional testing, the system achieves an accuracy rate of 93.3% with and average response latency of 1.8 seconds. This research significantly improves access to information and demonstrates how the RAG framework effectively mitigates LLM hallucinations, ensuring data integrity within highly regulated public service.
Optimizing Diabetes Complication Prediction Using Adaptive Boosting With Naive Bayes, Synthetic Minority Oversampling Technique, And Information Gain Feature Selection Farid Fitriyadi; Erna Indriastiningsih; Indriyati Indriyati
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 5 (2026): JUTIF Volume 7, Number 5, October 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.5.5812

Abstract

Primary healthcare facilities often face significant technical challenges in the early detection of diabetes complications due to their heavy reliance on micro-datasets characterized by extreme class imbalances. Such data constraints typically make standard single-prediction models prone to overfitting and low sensitivity, which are critical issues in clinical decision-making. This study proposes a multi-level optimization framework to overcome these limitations by integrating Information Gain for dimensionality reduction, Synthetic Minority Over-sampling Technique (SMOTE) to handle class imbalance, and Adaptive Boosting (AdaBoost) with Categorical Naive Bayes as the base learner. To address the critical aspect of model validity on a highly limited dataset (n=20), this methodology employs a stratified cross-validation scheme to ensure reliable performance estimation and minimize prediction bias. The integration of Information Gain effectively optimized the model by reducing the predictor variables from seven to four optimal features, thereby decreasing computational complexity. Based on rigorous testing, the proposed ensemble architecture achieved a robust average accuracy of 87.00% and, more importantly, a high Recall (Sensitivity) of 90% in identifying positive complication cases. This research provides a significant scientific contribution to machine learning development by demonstrating that the systematic integration of SMOTE and AdaBoost offers a stable, precise, and computationally efficient solution for predictive modeling in data-constrained clinical environments. These findings suggest that the proposed model can serve as a reliable early warning system to improve patient outcomes in primary care settings.

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