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TIN: TERAPAN INFORMATIKA NUSANTARA
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Jurnal TIN: TERAPAN INFORMATIKA NUSANTARA memuat tentang Kajian Bunga Rampai dari berbagai ide dan hasil penelitian para peneliti, mahasiswa, dan dosen yang berkompeten di bidangnya dari berbagai disiplin ilmu seperti: Komputer, Informatika, Industri, Elektro, Telekomunikasi, Kesehatan, Agama, Pertanian, Pembelajaran, Pendidikan, Teknologi Pendidikan, Ekonomi dan Bisnis, Manajemen, Akuntansi, dan Hukum
Arjuna Subject : Umum - Umum
Articles 582 Documents
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User Experience Analysis of a Multimodal Digital Application Integrating Multiple Intelligences for Young Learner Sipahutar, Rini Juliana; Silalahi, Natalia; Damayanti, Nina Afria
TIN: Terapan Informatika Nusantara Vol 6 No 9 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i9.8643

Abstract

Despite the increasing adoption of multimodal educational applications for young learners, empirical research that explicitly examines young learner’s user experience from the perspective of cognitive diversity remains limited. Many existing studies emphasize learning outcomes or technical usability, while insufficient attention is given to affective engagement, interaction behavior, and experiential quality during young learner’s interaction with multimodal systems. This gap highlights the need for a structured analysis of how multimodal interaction grounded in the Multiple Intelligences (MI) framework shapes young learner’s user experience. This study examines young learner’s user experience while interacting with an existing multimodal educational application that incorporates the MI framework as a foundation for its interaction structure. The research explores how visual, auditory, and kinesthetic elements influence children’s engagement, affective responses, and interaction behaviors. A qualitative descriptive design was employed through systematic observation and semi-structured interviews involving five young learners aged 5–6 years (N = 5), along with accompanying educators. The study introduces an adapted user experience analysis framework tailored for young learner’s multimodal interaction contexts. Thematic analysis was conducted to identify interaction patterns and usability factors shaping the overall experience. The findings indicate that multimodal interaction enhances engagement, motivation, and accessibility, particularly for children with diverse intelligence profiles. Integrating Multiple Intelligences principles supports adaptive interaction pathways that improve satisfaction and sustained attention. This study contributes to the field of Human Computer Interaction (HCI) by providing empirical evidence on how cognitive diversity can inform the evaluation and design of multimodal interfaces for young learners.
Sistem Face Recognition Berbasis Web menggunakan OpenCV Serta Evaluasi dengan Metode System Usability Scale Putri, Vanessa Shinta; Wibowo, Gentur Wahyu Nyipto; Zen, Ahmad Khanif
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.8924

Abstract

The attendance system is one of the important aspects for Tabebuya Resort and Restaurant for systematic human resource processing, the attendance system needed to be the basis for calculating salaries, evaluating discipline, and assessing the work of each employee. Therefore, an accurate, efficient, and transparent abscess system is needed so that the company’s productivity can be properly maintained. This research aims to develop the attendance system used by Tabebuya into a web-based face recognition system to make it easier for every employee to access the attendance system used by Tabebuya which originally had a problem in attendance recapitulation which had an effect on salary dan the failure of finger detection which had an effect in operational speed and long queues to become a web-based face recognition atttandance system to make it easier for every employee to access the attendance system with their own device with a certain coordinate point for avoiding operational disruptions and providing roleaccess limits to avoid manipulation of data. In the development of the system the programming, the software development method uses the waterfall method with the python program language implementation by OpenCV library to process facial features using biometric identification to recognize individuals based on facial characteristics and becomes an additional value to avoid the problem of attendance manipulation. The system evaluation is carried out using the system usability scale (SUS) method to ensure that the system created is technically functional. With >80,3 score of SUS indicate the web-based face detection attendance system developed using OpenCv is successful in usability and can help improvement of human resource management in company.
Pengembangan Website E-Commerce untuk Ekspansi Pasar Produk UMKM Menggunakan Model Prototipe Hidayatullah, Rian Hilmi; Haryono, Kholid
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9011

Abstract

The advancement of digital technology provides opportunities for Micro, Small, and Medium Enterprises (MSMEs) to develop marketing strategies through the utilization of electronic commerce platforms. However, the Baraya UMKM Community in Pangandaran, West Java, still experiences obstacles in market expansion due to marketing and sales methods that are still conducted conventionally. This research aims to design an e-commerce website that can facilitate digital marketing and transaction activities for the Baraya UMKM Community while assessing its functionality and ease of operation. The research approach adopts the Prototype method, which facilitates iterative system development by incorporating user feedback. This study involves the participation of 24 respondents comprising community administrators and MSME administrators as primary users of the platform. System verification is conducted through Black Box Testing to validate the conformity of all functions with requirement specifications, as well as usability evaluation using the System Usability Scale (SUS) instrument to analyze the system's practicality level. The usability evaluation results show an average SUS score of 74.58 with a Grade B category, indicating that the platform has an adequate level of practicality and is acceptable to users. Therefore, the developed e-commerce website is declared to meet the feasibility criteria as a medium for digital marketing and transactions in supporting the market expansion of MSME products within the Baraya UMKM Community environment.
Klasifikasi Penyakit Daun Kentang Berbasis CNN MobileNetV2 dengan Optimasi Randomize Search Lie, Jeason; Rahman, Abdul; Udjulawa, Daniel
TIN: Terapan Informatika Nusantara Vol 6 No 9 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i9.9108

Abstract

Potatoes are a vital food commodity in Indonesia, but their productivity often declines significantly due to attacks by various leaf diseases that inhibit growth. This study aims to build an efficient and accurate automatic classification model for potato leaf diseases using Deep Learning technology. The approach used in this study is the MobileNetV2 Convolutional Neural Network (CNN) architecture based on transfer learning, which is known to have high computational efficiency. To obtain the most optimal model performance, this study applies an automatic hyperparameter tuning strategy using the Randomize Search method and performs robust model validation using the K-Fold Cross Validation technique with 5 folds. In addition, the balanced class weight technique is also applied to overcome the problem of data imbalance in the eight disease classes tested. The experimental results show that the best model configuration is achieved at the 15th iteration of the 5th fold using a combination of RMSprop optimizer parameters, 35 epochs, and a learning rate of 0.001. The final evaluation on independent test data produces an accuracy of 78.45%, a precision of 84.24%, and a recall of 72.94%. The very small difference between the validation accuracy of 79.30% and the test accuracy indicates good generalization ability without overfitting. Although the model achieved excellent results in Alternaria classification, challenges remained in identifying the Fungi class, which has high visual similarity to Phytopthora and Pest. This study concludes that the integration of MobileNetV2 with hyperparameter optimization is capable of effectively classifying potato leaf diseases.
Evaluasi Usability Sistem Manajemen Penelitian Dosen Berbasis Prototyping Menggunakan System Usability Scale Andryadi, Aan Ansen; Zulkifli, Ridwan; Faidah, Rika Setiani Nur; Fadillah, Rike Setiani Nur; Fadilah, Umi Lutfiatul; Sophiawati, Nur Kesha; Perdiansyah, Devi; Derismana, Derismana
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9122

Abstract

Lecturer research management in higher education institutions often faces complex administrative challenges that are time-consuming and prone to documentation errors. These problems include difficulties in tracking proposal status, inconsistent progress reporting, and lack of transparency in the review process. The purpose of this study is to evaluate the effectiveness of a throwaway prototyping-based development approach in building a lecturer research management information system that is usable, efficient, and capable of improving administrative productivity. The system is designed to simplify research administration activities, such as proposal submission, reviewer assignment, progress reporting, and integrated research output tracking. The study employs a mixed method design that combines quantitative approaches through usability and time efficiency measurements, as well as qualitative approaches through in-depth interviews. The development process applies a throwaway prototyping cycle through stages: (1) initial requirements identification through stakeholder analysis, (2) rapid prototype creation for concept validation, (3) iterative evaluation and validation with end users, (4) prototype disposal and final system implementation based on feedback. This approach was chosen to accelerate requirements elicitation, validate interface flows before full development, and minimize rework before final implementation. The system was implemented as a web application using PHP (Laravel) and a relational database. Usability evaluation was conducted using the System Usability Scale (SUS), complemented by task-based efficiency measurements and brief interviews with end users. The research results show an SUS score of 85.5, indicating excellent usability and high user acceptance. Task completion time for core administrative activities decreased by 35% compared to manual processes. Qualitative feedback shows improved status transparency, reduced administrative burden, and more consistent documentation. Overall, these findings demonstrate that the prototyping model is effective for developing research management systems in higher education, particularly when user feedback is integrated from the outset and conducted iteratively. This study provides empirical contributions by demonstrating that the application of a throwaway prototyping model with early user involvement can produce a lecturer research management system with excellent usability and significant improvements in administrative work efficiency. These findings enrich the body of knowledge in academic information system development by integrating a system development model, usability evaluation using the System Usability Scale (SUS), and task-based efficiency measurement within a comprehensive evaluation framework.
Analisis SelectKBest pada Klasifikasi Trafik VPN Menggunakan Random Forest dan SVM Nurdiansyah, Andri; R, Dwi Robiul; Sururi, Sururi; Sujana, Nana
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9136

Abstract

The increasing use of Virtual Private Networks (VPNs) in modern networks poses significant challenges for network monitoring and traffic management, particularly in accurately and efficiently distinguishing VPN and non-VPN traffic. This study aims to analyze the effectiveness of the SelectKBest feature selection method in improving VPN traffic classification performance using Random Forest and Support Vector Machine (SVM) algorithms. The dataset used in this study is the CIC VPN-NonVPN Traffic Dataset provided by the Canadian Institute for Cybersecurity (CIC), which is widely recognized as a standard benchmark in network security research. Feature selection was performed using SelectKBest with the ANOVA (f_classif) scoring function, reducing the original feature set to 15 most relevant features. Experimental results show that the Random Forest classifier achieved a test accuracy of 84.94%, along with high F1-score and ROC-AUC values, and an average cross-validation accuracy of 95.18% with low variance. In contrast, the SVM model demonstrated relatively poor performance, with a test accuracy of approximately 62%, indicating its limitation in capturing the complex patterns of network traffic data. Further analysis using ROC curves, Precision–Recall curves, confusion matrices, and learning curves confirms that Random Forest exhibits superior generalization capability compared to SVM. These findings indicate that the combination of SelectKBest and Random Forest not only delivers high classification performance but also improves computational efficiency through feature dimensionality reduction, making it suitable for large-scale VPN traffic classification scenarios.
Sistem Informasi Produk Unggulan Desa Berbasis Web untuk Mendukung Promosi UMKM Kelvin, M.; Fatoni, Fatoni
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9146

Abstract

Banyu Urip Village possesses substantial local economic potential, particularly in the agriculture, fisheries, and home-based microenterprise sectors. However, limited promotional media and the absence of an integrated information system have resulted in low visibility of village flagship products and inefficient manual management of MSME data. This study aims to design and implement a web-based Information System for Featured Village Products as a solution to these challenges. The primary contribution of this research lies in the development of an integrated digital platform that combines MSME data management, digital presentation of featured products, and support for village administrative processes within a single accessible system. The system was developed using the Waterfall method to ensure a structured and systematic development process across all stages. Implementation results indicate that the system significantly improves the dissemination of information to the community, reduces reliance on manual administrative services, and enhances efficiency and transparency in managing village flagship products. Functional testing confirms that all system features operate effectively and meet user requirements. Therefore, this research contributes a practical and replicable model of a web-based village information system that supports local economic development and improves the quality of public services, particularly for rural areas with similar characteristics.
Klasifikasi Penyakit Daun Mangga Menggunakan YOLOv11 Berbasis Deep Learning dan Computer Vision Wijaya, Andrian; Rachmat, Nur
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9168

Abstract

Indonesia’s mango agriculture sector continues to face significant challenges due to leaf diseases that reduce crop productivity. Conventional disease identification methods remain inefficient because they rely on subjective visual observation. This study aims to develop a mango leaf disease classification model using the YOLOv11 deep learning algorithm. YOLOv11 is chosen for its capability in real-time object classification with an optimal balance between accuracy and processing speed. The research will utilize the Mango Leaf Disease dataset from Kaggle, consisting of eight classes (seven disease types and one healthy class). The planned methodology includes preprocessing, image augmentation, data splitting using K-Fold Cross Validation, and hyperparameter tuning on optimizer, learning rate, epoch, and batch size. Model performance will be evaluated using the Confusion Matrix. This research is expected to produce an accurate and efficient classification model that enables objective and rapid early detection of mango leaf diseases. The research utilizes a dataset from Kaggle consisting of 4,000 images across eight classes—comprising seven disease types and one healthy leaf class. The methodology involves preprocessing (resizing to 640x640 pixels and normalization), image augmentation, and data splitting using 10-Fold Cross Validation. Performance was optimized through hyperparameter tuning of the Adam optimizer, a learning rate of 0.001, a batch size of 16, and various epoch settings. The experimental results demonstrate that the YOLOv11s model achieves exceptional and stable performance. Evaluation using a Confusion Matrix shows that the model reached a 100% accuracy, precision, recall, and F1-score on the dataset used in this study. The model recorded an average training loss of 0.0979 and a validation loss of 0.0027. These findings confirm that YOLOv11s is not only highly accurate but also computationally efficient, making it a viable candidate for real-time detection systems on mobile or edge computing devices to support early disease detection in mango orchards. As the main contribution, this study provides a comprehensive evaluation of YOLOv11s for mango leaf disease classification using a 10-Fold Cross Validation scheme, stability analysis based on validation loss, and an assessment of its potential for real-time deployment on mobile and edge computing devices.
Transformasi Kelas Digital dan Dampak Implementasi TIK terhadap Literasi Digital Pendidik: Pendekatan Mixed Methods Rumiyadi, Arif; Azhar, Roza Cyintia Salwa; Nurrahman, Yusuf; Fahrudin, Arif; Murtiyasa, Budi
TIN: Terapan Informatika Nusantara Vol 6 No 8 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i8.9169

Abstract

The gap between the rapid demands of digital transformation in education, which include the adoption of ICT-based learning, LMS, and the integration of Coding and Artificial Intelligence materials, and the reality of implementation challenges in the field. These crucial challenges include the availability and distribution of inadequate supporting facilities and infrastructure at all levels of education according to national standards, as well as the urgent need to improve teachers' digital competence and literacy so they can adapt and teach innovatively in the era of the Industrial Revolution 4.0. This study uses a qualitative approach as the basic methodological framework because this approach is considered the most relevant for understanding in-depth the phenomenon of Information and Communication Technology (ICT) implementation in the context of learning in schools. The data collection technique used is interviews, because this technique is considered the most effective for gathering in-depth information regarding teachers' experiences, views, and practices in implementing ICT in learning. The results of the study indicate that the systematic application of ICT and supported by continuous training can improve teachers' understanding, technical skills, and positive attitudes towards digital technology. This transformation also has an impact on the creation of a collaborative and adaptive learning culture in the classroom. This article recommends the importance of institutional policies that support the digital ecosystem so that teachers' digital literacy continues to develop in line with the demands of the technological era. The contribution of this research is expected to provide a deeper understanding of the challenges and opportunities of digital classroom transformation at the junior high school level, while also producing strategic recommendations based on empirical evidence for policymakers and education practitioners so that digital transformation can improve the quality of learning sustainably.
Effect of Animated Video Based Digital Education on Anemia Knowledge among Adolescent Girls: A Pre Post Study Sapariah, Astri; Hassan, Hafizah Che; Yahya, Fatimah
TIN: Terapan Informatika Nusantara Vol 6 No 9 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i9.9184

Abstract

Anemia remains a major public health problem among adolescent girls, particularly in developing countries, where inadequate iron intake, menstrual blood loss, and limited health literacy contribute to its high prevalence. Insufficient knowledge regarding the causes, symptoms, and prevention of anemia often leads to poor dietary practices and low adherence to iron supplementation programs. In response to these challenges, digital health education using animated video media has emerged as an innovative and engaging strategy for improving adolescents’ understanding of health-related issues. This study aimed to examine the effect of animated video–based digital education on anemia-related knowledge among adolescent girls in a senior high school setting. A quantitative pre-experimental study with a one-group pretest–posttest design was conducted involving 52 adolescent girls selected through purposive sampling at SMAN 1 Cisarua, Indonesia. Participants received an educational intervention in the form of an animated video addressing the definition, causes, symptoms, consequences, and prevention of anemia. Knowledge levels were measured before and after the intervention using a validated structured questionnaire. Data were analyzed using a paired sample t-test after confirming normal data distribution. The results demonstrated a statistically significant increase in mean knowledge scores following the intervention (p < 0.001), indicating a meaningful improvement in participants’ understanding of anemia. These findings suggest that animated video–based digital education is an effective and accessible approach to enhancing anemia-related knowledge among adolescent girls. The use of such media may support school-based health education programs and contribute to strengthening anemia prevention efforts in adolescent populations.

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