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TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27227987     DOI : -
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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 8 Documents
 1 
Search results for , issue "Vol 6 No 9 (2026): February 2026" : 8 Documents clear
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.
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.
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.
Penerapan Natural Language Processing Dalam Klasifikasi Sentimen Komentar Youtube Tentang Judi Online Lase, Fransiskus Oktanesius; Pieter S, Yoel; Lase, Kristian Juri Damai
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.v6i9.9256

Abstract

YouTube, as a video-sharing platform, has become a public interaction space rich in opinions regarding online gambling issues in Indonesia. However, large-scale manual sentiment analysis is difficult due to the high data volume and local language nuances. This study aims to develop a sentiment classification model for Indonesian-language YouTube comments using Natural Language Processing (NLP) techniques to understand public perceptions of the online gambling phenomenon. Data of 3,000 comments were collected from YouTube videos related to online gambling through the YouTube Data API in Indonesia. All data were manually annotated by three annotators (kappa 0.85) into three sentiment classes (positive, negative, neutral) along with relevance, then divided into 80% training and 20% testing. Pre-processing included case folding, text cleaning, tokenization, stopword removal, stemming, lemmatization, and slang normalization. Models tested included Naive Bayes, Support Vector Machine (SVM), Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and IndoBERT. Evaluation using accuracy, precision, recall, and F1-score metrics showed IndoBERT achieved the best performance with 91.67% accuracy, 90% precision (negative class), 95% recall (negative class), and 91.66% F1-score. This research contributes to understanding public attitudes toward online gambling and the development of an adaptive sentiment classification system for the Indonesian language.
Youth-Oriented Digital Media Visibility on Instagram: A Multimodal Qualitative Analysis of USSFeeds Ridho, Muhammad Rajwa; Sumarlan, Iman
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.v6i9.9272

Abstract

Social media platforms have reshaped how visibility is produced, sustained, and contested within contemporary digital media environments. Despite extensive research on social media branding and engagement, limited attention has been given to how youth-oriented digital media actors strategically construct visibility as an ongoing communicative process rather than mere exposure. This study aims to examine how a youth-oriented digital media account builds and maintains visibility on Instagram through everyday visual, narrative, and participatory practices. Employing a qualitative content analysis, this research analyzes selected Instagram posts published by USSFeeds between March and September 2025. The analysis focuses on three analytical dimensions: visual discourse, narrative framing, and participatory circulation. The findings indicate that visual coherence operates as a semiotic anchor that stabilizes media identity, while narrative framing grounded in youth culture enhances cultural resonance and interpretive alignment. The audience participation amplifies visibility by enabling relational circulation of meaning within platform-mediated and algorithmically structured environments. This study contributes to media and communication scholarship by conceptualizing digital visibility as a relational and processual phenomenon shaped by discourse, participation, and platform logics, thereby extending existing understandings beyond linear models of attention and reach.
Evaluasi Gangguan Jaringan Distribusi Tegangan Menengah Menggunakan Failure Mode and Effect Analysis (FMEA) Mubarok, Kholifah Yusuf; Marbun, Musa Partahi
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.v6i9.9280

Abstract

Disturbances in the medium voltage distribution network at PT PLN Persero UP3 Makassar Selatan cause repeated outages that disrupt supply continuity in a major economic hub of Eastern Indonesia, with 1,207 incidents recorded in 2024 dominated by the rainy season. This study aims to quantify unserved energy losses for each disturbance type, determine the severity and occurrence levels of failure modes, apply Failure Mode and Effect Analysis (FMEA) for risk mapping, and formulate preventive mitigation strategies. Historical outage data from 2024 and expert judgements from distribution maintenance personnel are processed through three‑phase power and Energy Not Supplied (ENS) calculations, severity–occurrence scaling, FMEA tabulation, and a 5×5 risk matrix to classify risk levels. The results show that lightning/extreme weather, trees/vegetation, animals, and “unidentified” causes generate the largest ENS and fall into the highest risk classes, while internal equipment failures generally remain at moderate to low risk. Recommended actions include reinforcing lightning protection and grounding, systematic vegetation management, installation of animal protection devices, improvement of joints and construction quality, optimization of protection operation, and community/social stakeholder outreach, which are estimated to be more cost‑effective than tolerating recurring outage losses.
Analisis Kualitas Sistem E-Rapor SP Menggunakan Metode WebQual 4.0 dan IPA Ekayanti, Gusti Ayu Mas; Saskara, Gede Arna Jude; Putra, I Nyoman Tri Anindia
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.v6i9.9318

Abstract

One form of information technology implementation in education is the use of the e-Rapor SP system in preparing students’ learning outcome reports. However, users still experience various difficulties in its implementation, indicating that the system quality needs improvement. This study aims to measure the quality of the e-Rapor SP system at the junior high school level based on users’ perceptions in Buleleng Regency and to identify low-performing aspects for improvement recommendations. System quality was measured using the WebQual 4.0 variables, including usability, information quality, service interaction quality, and overall impression. This study employed a quantitative approach using a survey method. Data were collected from 84 respondents through a WebQual 4.0-based questionnaire and analyzed using descriptive statistics, the WebQual Index, and Importance Performance Analysis (IPA). The results show that the e-Rapor system is perceived as having good quality but has not yet met users’ expectations. The WebQual Index value of 0.78 indicates a good but not ideal level of system quality. Gap and conformity analyses revealed negative gaps and conformity values below 100%, indicating a mismatch between system performance and user expectations. The recommended improvements focus on enhancing service quality through clearer helpdesk support or guidance, as well as faster and more consistent service responses. The findings of this study provide a basis for decision-making to improve the quality of the e-Rapor system.
Penerapan Naive Bayes dalam Mengidentifikasi Penyebab Remaja Desa Terlibat dalam Judi Online Annabil, M Haziq; R, Rakhmat Kurniawan
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.v6i9.9350

Abstract

The development of digital technology and increased internet access have driven changes in adolescent social behavior, including increased involvement in online gambling activities, not only in urban areas but also in rural areas. This study aims to identify the factors that influence adolescent involvement in online gambling and to measure the level of influence of each factor using a machine learning-based classification approach. The research was conducted in Payageli Village, Sunggal District, Deli Serdang Regency, involving 507 adolescent respondents who were surveyed using a questionnaire containing 23 questions. The data obtained was analyzed using the Naive Bayes algorithm with data preprocessing, categorical attribute coding, and data division into training and test data with a ratio of 80:20. The results showed that the dominant factors influencing adolescent involvement in online gambling included peer influence, intensity of exposure to online gambling advertisements, online gaming habits, low positive leisure activities, and lack of parental supervision. The classification model built produced an accuracy rate of 98%, with high precision and recall values in each class. These findings indicate that the Naive Bayes algorithm is effective in identifying adolescents at risk of engaging in online gambling and has the potential to be used as a basis for developing data-driven prevention strategies at the village level.

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