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Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 471 Documents
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Pengembangan Aplikasi Mobile untuk Penjualan Ikan Hias pada Toko Gudang Jaya Aquarium David Precius Panggabean
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Technological developments in the current digital era have encouraged various business sectors to shift to online platforms, including in the trade sector. Gudang Jaya Aquarium, as one such business, still relies on a conventional sales system. This research aims to develop a mobile-based sales application to facilitate the store in managing transactions and providing information about ornamental fish care to customers. Meanwhile, the system development method applies the Scrum approach, which allows for an iterative and flexible development process according to user needs. Data were collected through observation, interviews, and literature studies. By implementing a mobile-based sales system, Gudang Jaya Aquarium is expected to assist in transaction management and increase customer satisfaction through the convenience of more modern and integrated transactions.
Penerapan Non-negative Matrix Factorization untuk Pemodelan Topik pada Opini Kegiatan Dakwah Rahmad Kurniawan; Aidha Tita Irani; Sukamto; Ilyas Husti; Fatayat; Elfizar
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The Indonesian Ulema Council (MUI) of Riau Province faces challenges in objectively evaluating dakwah (Islamic preaching) as its existing Peta Dakwah Cerdas (PDC) system lacks a feature to analyze congregant feedback. This study aims to design and implement a topic modeling model to identify the main hidden themes within congregant opinions. The study utilized 2,581 comments collected from the MUI Riau Smart Evaluation System. The methodology involved text preprocessing, Term Frequency-Inverse Document Frequency (TF-IDF) word weighting, and topic modeling using the Non-Negative Matrix Factorization (NMF) algorithm. Toward determine the optimal number of topics (k), the model was evaluated using Coherence Score to measure semantic readability and Silhouette Score to measure the resulting topic separation. The experiment identified two topics (k=2) as the best configuration achieving a high Coherence Score of 0.7023 and a Silhouette Score of 0.0163. The two main topics formed represent (1) Prayers and Greetings for the Preacher, and (2) Congregant Participation and Appreciation for the Dakwah. The application of NMF proved effective in identifying thematic patterns in congregant opinions and can serve as a foundation for MUI Riau to develop a real-time Islamic preaching evaluation system.
Pengaruh Augmentasi Data dan Dropout terhadap Generalisasi Model Deteksi Kerusakan Panel Surya Irfan Ali; Rudi Kurniawan; Dadang Sudrajat; Saeful Anwar; Nining Rahaningsih
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Automatic defect detection in photovoltaic (PV) panels is a crucial challenge for maintaining energy efficiency and reliability in renewable power systems. However, the limited availability of labeled datasets and high environmental variability often lead deep learning models to overfit and lose generalization capability. This study investigates the combined effects of data augmentation and dropout regularization on improving the generalization performance of transfer learning-based models for multi-class PV defect classification. Two pretrained architectures, VGG16 and InceptionV3, were fine-tuned using the Faulty Solar Panel dataset comprising six defect categories. Experiments were conducted under three main configurations: (1) baseline without regularization, (2) augmentation only, and (3) combined augmentation–dropout with dropout rates of 0.2, 0.3, and 0.5. Performance evaluation employed accuracy, precision, recall, macro-F1, and confusion matrix analysis for each defect class. The results demonstrate that the combination of data augmentation and moderate dropout (0.3) significantly enhances generalization, achieving 92.10% accuracy and 0.90 macro-F1 with the InceptionV3 architecture. Higher dropout values (0.5) caused slower convergence and decreased accuracy. These findings confirm that balanced integration of augmentation and dropout effectively mitigates overfitting and strengthens model robustness under limited and imbalanced data conditions. The proposed approach provides practical implications for implementing reliable, lightweight, and deployable deep learning-based inspection systems in real-world PV monitoring using edge computing devices.
Pemanfaatan Teknologi IoT untuk Optimalisasi Energi dan Manajemen Fasilitas Berkelanjutan Menggunakan Fuzzy Logic Ceorido Ghalib Wibowo; Jumanto Unjung; Dwika Ananda Agustina Pertiwi; Much. Aziz Muslim
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The development of the smart airport concept requires the integration of digital technologies to enhance operational efficiency, environmental sustainability, and passenger comfort. One of the key technologies driving this transformation is the Internet of Things (IoT), which enables real-time data collection and analysis from interconnected devices and sensors. This study explores the utilization of IoT for energy optimization and sustainable facility management in smart airports, focusing on systems such as energy consumption monitoring, automated lighting control, sensor-based temperature regulation, and efficient equipment management. The research employs a literature review and data-driven system analysis within the operational context of modern airports. The results indicate that IoT-based implementations can reduce energy consumption by up to 25–30% through dynamic and predictive control of resource usage. Furthermore, IoT contributes to sustainability by reducing carbon emissions and extending infrastructure lifespan. Therefore, IoT technology serves as a fundamental component in realizing airports that are efficient, environmentally friendly, and future-oriented.
Implementasi Algoritma Deep Learning YOLO dan OpenCV untuk Mendeteksi Perbedaan Buah Ery Muchyar Hasiri; Fahmi; Mohamad Arif Suryawan; Nurfida Ain
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The development of computer vision technology and artificial intelligence has driven innovation in automation in various fields, including the agricultural sector and fruit trading. The process of identifying fruit quality, which is generally done manually, is still vulnerable to human error and inconsistencies. Based on these problems, this study aims to develop an automated system to detect the difference between fresh and rotten fruit using a deep learning-based You Only Look Once (YOLO) algorithm integrated with the OpenCV library. The system is designed in the form of a web application that is easy for fruit sellers to use. The dataset used consists of images of apples, mangoes, and bananas labeled through Roboflow into two categories, namely fresh and rotten. The model was trained using YOLOv11, then tested with new data that had never been used before. The test results showed high performance with an accuracy of 99.01%, mAP@50 of 0.925, precision of 0.93, recall of 0.90, and F1-score of 0.91. Based on these results, the system is able to detect the condition of the fruit automatically and in real-time with an excellent level of accuracy. This implementation proves that the integration between YOLO and OpenCV is effective in improving the efficiency, accuracy, and consistency of the fruit quality identification process.
Integrasi Sistem Informasi Manajemen Dan Teknologi GIS Untuk Pengelolaan Data Di Rumah Tahfidz Al-Ma’arif Banjarmasin Mariatul Kiftiah; Arifin Noor Asyikin; Fuad Sholihin; Subandi
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Effective data management plays a crucial role in improving administrative efficiency in educational institutions, including Rumah Tahfidz. Rumah Tahfidz Al-Ma’arif Banjarmasin, as a non-formal educational institution, requires a system capable of systematically recording, monitoring, and visualizing data. This study aims to develop a web-based management information system integrated with Geographic Information System (GIS) technology to support data management in the institution. The system development follows the Waterfall method, which consists of sequential stages: planning, requirements analysis, design, implementation, testing, and maintenance. This approach was chosen because it provides a structured workflow, ensuring that the system is developed according to user needs. The system is built using the Laravel framework and Filament for the admin interface, and is equipped with an interactive GIS-based map to display the distribution locations of donation boxes. It also implements a role and permission management system with four user levels: admin, teacher, volunteer, and owner, to ensure secure and efficient access. Black-box testing shows that all features function as expected. An evaluation using the System Usability Scale (SUS) with 33 respondents resulted in a score of 74.55, indicating good usability. The results show that this system effectively supports data management, information transparency, and administrative decision-making.
Pemanfaatan Generative Artificial Intelligence (GenAI) untuk Prediksi dan Analisis Bencana Alam Arief Wibowo; Asep Surahmat
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

Disaster prediction and analysis are crucial components in mitigating the impacts of natural hazards such as floods, earthquakes, and landslides. Conventional systems often rely on deterministic models and limited historical data, which restrict their accuracy and adaptability to dynamic environmental changes. The emergence of Generative Artificial Intelligence (GenAI), particularly models based on deep learning and generative architectures such as Generative Adversarial Networks (GANs) and Diffusion Models, introduces new opportunities for synthetic data generation and predictive simulation. This study aims to explore the implementation of GenAI in disaster prediction and analysis by reviewing recent literature and practical applications in Indonesia. The proposed framework integrates multimodal data—including meteorological, seismic, and remote sensing data—into generative models to simulate disaster scenarios and improve early warning systems. The results indicate that GenAI can enhance data diversity, reduce bias in model training, and support real-time decision-making in disaster management. The study concludes that GenAI has strong potential to revolutionize disaster analytics and strengthen climate resilience through adaptive, data-driven insights. Thus, the output of this research is conceptual and focuses on designing a framework, while empirical testing forms the basis for further research development.
Performance Evaluation of Flask-Based Telegram Chatbot with Local LLaMA3 Language Model Gusti Muhamad Sardana; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The rapid advancement of digital technology has increased the demand for information delivery systems that are accurate and contextually relevant. This study aims to design and evaluate the performance of a LLaMA3-based chatbot integrated with the Telegram platform using the Flask framework. The development is driven by the need for digital information services capable of providing fast, relevant, and context-aware responses in the Indonesian language. The research methodology includes system configuration, API integration, and performance testing through measurements of Average Response Time (ART) and response quality assessment based on relevance, clarity, and completeness. Experimental results show that the chatbot achieves an average response time of 49.15 seconds and an average response quality score of 14.10 out of 15, indicating strong contextual understanding and high response relevance. These findings suggest that the chatbot system is feasible for use as an automated Indonesian-language information service. However, further optimization is necessary to improve processing speed for broader and more dynamic implementation scenarios.
Perancangan Aplikasi E-Arsip Untuk Efisiensi Pengelolaan Dokumen Di PT XYZ (Showroom dan Bengkel Mobil) Prianto Roito Siregar; Binastya Anggara Sekti
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The rapid development of information technology has encouraged companies to transform toward digitalization, including in document management. PT XYZ, a company engaged in car showroom and workshop services, still relies on conventional archiving systems that lead to several issues, such as difficulties in retrieving documents, risks of losing physical archives, and lack of integration across departments. This study aims to design a web-based e-Archive application to support the document digitalization process, enabling more structured, faster, and efficient archive management. The research method adopts the waterfall model, which includes requirements analysis, system design, prototype implementation using the Next.js framework and MySQL database, and system evaluation. Data were collected through observations of the archiving process at PT XYZ and questionnaires distributed to employees as potential users of the system. The results show that the e-Archive application provides essential features such as digital archive management, fast document retrieval, categorization, and automatic report generation. Based on the questionnaire analysis, most respondents indicated that the application is user-friendly, improves the speed of document retrieval, and enhances work efficiency. In conclusion, the designed e-Archive prototype has proven to minimize the risk of document loss, improve document management, and support data-driven decision-making. The implementation of this application is expected to serve as a strategic step toward sustainable digital archive management at PT XYZ.
Aplikasi Edukatif dan Hiburan Cross-Platform untuk Meningkatkan Literasi Digital Abdulloh Fairuzabadi; Arya Iswahyudia; Barnadi; Muslik
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

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Abstract

The Cross-Platform Educational and Entertainment Application was developed to address the issue of low digital literacy, particularly among young people who actively use digital media but have not fully understood its healthy, productive, and safe utilization. This study aims to design a cross-platform application that integrates education and entertainment to enhance engagement while providing an enjoyable learning experience. The research method employed the Agile Scrum approach, an iterative and collaborative framework that divides the development process into several sprints. Data were collected through observation, interviews, and literature studies to accurately map user needs. The development stages included preparing the product backlog, sprint planning, feature development in short cycles, as well as evaluation through sprint reviews and retrospectives. The results indicate that the application provides interactive learning media, educational entertainment, and user-friendly cross-platform access. User satisfaction reached 86%, demonstrating the application’s effectiveness in improving digital literacy and encouraging positive technology utilization. Thus, this study contributes to the development of technology-based solutions that support the enhancement of digital skills among younger generations.

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