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Nuansa Informatika
Published by Universitas Kuningan
ISSN : 18583911     EISSN : 26145405     DOI : https://doi.org/10.25134/nuansa
Core Subject : Science,
Computer Science & IT
NUANSA INFORMATIKA adalah jurnal peer-review tentang Informasi dan Teknologi yang mencakup semua cabang IT dan sub-disiplin termasuk Algoritma, desain sistem, jaringan, game, IoT, rekayasa Perangkat Lunak, aplikasi Seluler, dan lainnya
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 87 Documents
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IoT and Water Consumption Forecasting: A Green Accounting Study at a Coffee Shop in Cimahi: IoT dan Peramalan Konsumsi Air: Studi Akuntansi Hijau di Kedai Kopi Cimahi Fauzan, Mohamad Nurkamal; Tanjung, Riani
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.366

Abstract

Uncontrolled water consumption is a serious challenge, especially in small businesses like coffee shops. Excessive water use can lead to waste and financial losses. To address this issue, IoT (Internet of Things) technology and data analysis are applied to monitor and predict water consumption. In this study, predictive models such as Random Forest, XGBoost, and LSTM are used to analyze water consumption data. The results show that Random Forest has the best performance with the lowest prediction error and the highest R-squared value, indicating this model’s capability to explain nearly all the variance in water consumption data. Random Forest and XGBoost perform well as they can handle data with non linear features and complex interactions, while LSTM's lower performance is likely due to limited data and suboptimal hyperparameter tuning. The implementation of green accounting in this system enables effective tracking of water consumption costs. Suggested improvements include further exploration of LSTM hyperparameters, the use of ensemble techniques, and cost sensitivity analysis for water-saving policy decisions. This model is expected to provide an effective water saving solution for coffee shop owners.
Web-Based Assignment Management System Application Design to Increase Personnel Productivity and Effectiveness in Product Documentation Division: Rancang Bangun Aplikasi Sistem Manajemen Penugasan Berbasis Web Guna Meningkatkan Produktifitas dan Efektifitas Personel Bagproddok Dispenad Seftian Candra Pratama; Ahmad Firdaus, Eryan; Idul Adha, Rochedi
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.368

Abstract

An effective task management is essential for enhancing productivity and operational efficiency within organizations. Currently, the Production Documentation Division of the Information Service of the Indonesian Army (Dispend) uses WhatsApp for task coordination, which results in fragmented communication, limited tracking, and reduced transparency. To overcome these issues, this study develops a web-based assignment management system  to improve task distribution, monitoring, and reporting. The system is built using the Rapid Application Development (RAD) model, which emphasizes iterative prototyping and users’ feedback. Key features include task creation, progress tracking, file submission, approval workflows, and reporting tools, supported by role-based access control for both administrators and users. The implementation of this system shows significant improvements in workflow efficiency, transparency, and accountability compared to the previous WhatsApp-based method. In conclusion, the system contributes to better documentation, timely task completion, and enhanced collaboration, thereby increasing overall productivity. Future enhancements may include mobile integration and real-time notifications to further improved accessibility and operational effectiveness.
Feature Extraction Using Markov Random Field (MRF) On Improving CNN Classification Results For Alzheimer's Disease Diagnosis: Ekstraksi Fitur Menggunakan Markov Random Field (MRF) untuk Meningkatkan Hasil Klasifikasi CNN pada Diagnosis Penyakit Alzheimer Bahri, Saeful; Adiwisastra, Miftah Farid; Hidayatulloh, Taufik
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.369

Abstract

Alzheimer’s disease is a degenerative neurological disorder that significantly affects patients’ cognitive functions and social lives. It is a leading form of dementia, characterized by the progressive death of brain cells. One widely adopted diagnostic approach involves magnetic resonance imaging (MRI) to evaluate brain structures. Recent advances in machine learning have enabled automated image analysis, with Convolutional Neural Networks (CNNs) commonly used for image feature extraction and classification. However, CNNs face a major limitation in maintaining consistency during image segmentation, which results in reduced classification accuracy. This issue arises from CNNs’ limited ability to preserve local pixel-level consistency during feature extraction. To address this, we propose integrating a Markov Random Field (MRF)-based layer into the CNN architecture, which has been shown to enhance segmentation consistency. This study utilizes publicly available MRI datasets of Alzheimer’s patients and employs a k-fold cross-validation scheme for evaluation. The results show that the CNN-MRF model improves classification accuracy to 63%, compared to 61% with the standard CNN. Furthermore, the loss value is reduced from 0.80 to 0.74. Although the improvement in accuracy is incremental, a paired t-test confirms that the difference is statistically significant (p < 0.05). This method has proven effective in enhancing the reliability of image-based diagnostic systems for early detection of Alzheimer’s disease.
Design and Implementation of a Performance Dashboard for Public Relations at Telkom University: Perancangan dan Implementasi Dashboard Kinerja Bidang Humas Universitas Telkom Dea Reskyadita, Feddy; Nurrahmi, Hani; Maulana , Daris
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.377

Abstract

The Public Relations and Analytics (PRA) division at Telkom University faces challenges in managing manual processes and integrating data from diverse sources, hindering efficient reputation management. This study developed PANDA (Public Relations and Analytics Dashboard Application), a web-based system with an interactive performance dashboard to optimize PRA operations. Using the Waterfall methodology, the research encompassed requirements analysis, system design, implementation, and initial evaluation. PANDA integrates real-time key performance indicators (KPIs) such as media coverage, social media engagement, website analytics, and enabling data-driven decision-making. The System Usability Scale (SUS) evaluation resulted in a high score of 82 (categorized as 'Good to Excellent'), demonstrating PANDA's effectiveness in enhancing usability and streamlining operational workflows. The system enhances PR performance monitoring and offers a scalable model for educational institutions.
The Implementation of User Satisfaction Based Shortest Job First Algorithm Efficiency in Queuing System : Penerapan Efisiensi Algoritma Shortest Job First Berbasis Kepuasan Pengguna pada Sistem Antrian Darsanto
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.378

Abstract

Efficient and structured queue management is crucial to ensure the smooth operation of various services in both the public and private sectors. A web-based queue system has now become a good solution due to their ease of access and ability to manage queues in real-time. In this study, a web-based queue system is developed that implements the Shortest Job First (SJF) algorithm to optimize service sequences. The SJF algorithm prioritizes services with the shortest processing duration, which is expected to reduce user waiting time and to increase overall system effectiveness. This research is conducted in the university's Bureau of General Administration and Finance queue system as the research object. The software development method uses Agile with the Extreme Programming (XP) framework. The results of system testing using the Black Box testing method to evaluate application functionality show that all test cases are valid, indicating that the system operates according to the desired requirements. System performance analysis is conducted by 40 students using the User Experience Questionnaire (UEQ), resulting in benchmark scores in which 5 variables are above average, and 1 variable is below average. These results indicate that the queue system built using the SJF algorithm is feasible and effective for users.
Assessing the Role of E-Govqual in Improving Public Satisfaction with the MyPertamina Application in Setiabudi District: Mengkaji Peran E-Govqual dalam Meningkatkan Kepuasan Masyarakat terhadap Aplikasi MyPertamina di Kecamatan Setiabudi Yulian Surya Saputra; Sucitra Sahara; Agung Permana, Rizqi
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.379

Abstract

This research aims to analyze the influence of Customer Satisfaction on the quality of e-government services (E-Govqual) on the use of the My Pertamina application in Setiabudi District. The research method used was quantitative with a survey approach by distributing questionnaires to 150 respondents. The data collected was analyzed using validity tests, reliability tests, and hypothesis testing through linear regression analysis. The research results show that there is no significant influence between Customer Satisfaction and E-Govqual. This is proven by a correlation value of 0.160, which indicates a very weak relationship, as well as a coefficient of determination (R²) value of 2.56%, which indicates that variations in E-Govqual are only slightly influenced by Customer Satisfaction. The results of the hypothesis test show a significance value of 0.050 > 0.05 and Fcount (3.891) < Ftable (3.905), so that the null hypothesis (H₀) is accepted and the alternative hypothesis (H₁) is rejected. Satisfaction (X) on E-Govqual (Y) is 0.050 > 0.05, and the calculated F-value (F-count) is less than the F-table value, namely 3.891 < 3.905. These findings suggest that other factors beyond Customer Satisfaction may have a greater influence on e-government service quality. Based on the results, it is recommended that the development of the My Pertamina application be more focused on improving system quality, ease of use, and other technical aspects to improve overall service quality.
Predicting Basic Shipping Tariff Using Machine Learning: Prediksi Tarif Dasar Pengiriman Menggunakan Machine Learning Harani, Nisa Hanum; Setyawan, M. Yusril Helmi; Ferdinan, Dani
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.388

Abstract

This study explores the application of machine learning algorithms in predicting the Basic Shipping Tariff for logistics, focusing on variables such as Item Price, Shipment Weight, and Distance (KM). Random Forest Regressor and Linear Regression models were used as comparison methods. Experimental results show that the Random Forest Regressor outperforms Linear Regression, achieving an R² value of 0.915 and RMSE of 0.154, while Linear Regression reached an R² value of 0.706 and RMSE of 0.113. Additionally, the Random Forest model achieved lower error values with MSE of 0.000 and MAE of 0.003, compared to Linear Regression with MSE of 0.001 and MAE of 0.007. These error metrics further highlight the superiority of the Random Forest model. In-depth analysis reveals significant relationships between these variables and the Basic Shipping Tariff, showcasing the model's potential application in dynamic pricing strategies within the Indonesian logistics industry. This study aims to contribute to operational efficiency and improve pricing accuracy in the logistics business in Indonesia.
Emoji-Based Sentiment Classification Using Ensemble Learning with Cross-Validation: A Lightweight Approach for Social Media Analysis: Klasifikasi Sentimen Berbasis Emoji Menggunakan Ensemble Learning dengan Validasi Silang: Pendekatan Ringan untuk Analisis Media Sosial Alamsyah, Nur; Bayu Wibisono, Gunthur; Parama Yoga, Titan; Budiman; Hendra, Acep
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.396

Abstract

The increasing use of emojis in online communication reflects emotional expression that is often more immediate and intuitive than text. This study proposes a lightweight sentiment classification approach that utilizes only emoji features extracted from social media posts, without relying on textual content. The importance of this research lies in its relevance to short-form digital content, where textual sentiment cues are minimal or absent. To address the classification problem, we implement and compare multiple machine learning models including Random Forest (RF), Support Vector Machine, and an ensemble Voting Classifier combining both. Emoji tokens were vectorized using character-level count vectorization, and performance was evaluated using 5-fold cross-validation to ensure robustness and generalizability. Results show that the ensemble model achieved the highest average accuracy of 93.6%, outperforming the individual classifiers. These findings confirm that emojis alone can serve as reliable indicators of sentiment and support the deployment of fast, interpretable, and scalable models for social media sentiment analysis.
Design And Development of The Cakrawala Project Web Application: Case Study of The Information Technology Division: Perancangan dan Pengembangan Aplikasi Web Proyek Cakrawala: Studi Kasus Divisi Teknologi Informasi Subagja, Tirta; Syani, Mamay
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.397

Abstract

This research examines the design and development process of the Cakrawala Project web application using the CodeIgniter framework at the Information Technology Division. The research objectives are to analyze the stages of application development, identify the advantages of using the CodeIgniter framework, and measure the effectiveness of the web application implementation. The research method used is a case study with a Research and Development (R&D) approach through a waterfall development model. The results showed that the use of the CodeIgniter framework in the development of the Cakrawala Project web application provided convenience in the design process through the MVC (Model-View-Controller) architecture, increased development efficiency, and produced responsive web applications. The implementation of the Cakrawala Project web application has succeeded in increasing the effectiveness of information management and collaboration between divisions in the organization. This research contributes practical recommendations in the development of CodeIgniter-based web applications for similar organizational needs.
Development Of Online Attendance Application With Time And Location Validation At Satpol Pp South Tangerang: Pengembangan Aplikasi Absensi Online Dengan Validasi Waktu Dan Lokasi Di Satpol PP Tangerang Selatan Hidayat, Syamsu; Rifki Ramadhan, Muhamad; Susilo, Joko
NUANSA INFORMATIKA Vol. 19 No. 2 (2025): Nuansa Informatika 19.2 Juli 2025
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/ilkom.v19i2.398

Abstract

In order to solve the inefficiencies and errors in manual attendance at the Satpol PP office in South Tangerang, this study creates a web-based attendance system.  The Laravel framework is used to construct the system, and GPS and reverse geocoding are incorporated to verify the locations of check-in and check-out.  The system design is supported by UML diagrams, and structured attendance data is handled using a MySQL database.  The Black Box Testing technique verifies that the system's essential features operate as planned.  The outcomes demonstrate enhanced precision, real-time tracking, and simplified reporting.  To improve system usability and dependability, future suggestions call for including mobile apps, facial recognition, and predictive attendance analytics. In order to increase productivity, precision, and openness at the Satpol PP office in South Tangerang.

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