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Menampilkan 81–90 dari 812 artikel
The Lack Of Digital Literacy On Instagram: A Case Study Of Reactive Behavior Based On Clickbait
Satyawan Tobing
; Albert Zebua
; Njue Steeven Tarigan
; Rahmad Ardiansyah
; Rafi Ryandieka Adinulhaq
; Muhammad Natsir
Inspirasi Dunia: Jurnal Riset Pendidikan dan Bahasa
Vol 4
, No 4
(2025)
This study analyzes the phenomenon of limited digital literacy on the social media platform Instagram, particularly concerning users’ tendency to respond emotionally to provocative titles (clickbait) without fully reading and comprehending the content. Employing a qualitative case study approach, the research highlights behavioral patterns in which users prioritize quick responses over critical understanding. The findings reveal that the primary factor contributing to this phenomenon is the atte...
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Effect of Natural Fiber Stacking Sequence on the Properties of Hybrid Composites for Drone Frame Applications
Janiviter Manalu
; Jefri Bale
; Khristhoper Aris Arianto Manalu
; Frans Augusthinus Asmuruf
; Fitriyana, Deni Fajar
; Nizar Alamsyah
; Januar Parlaungan Siregar
; Al Ichlas Imran
; Tezara Cionita
; Natalino Fonseca Da Silva Guterres
Advance Sustainable Science, Engineering and Technology
Vol 7
, No 4
(2025)
The present study highlights the effective utilization of waste fibers in structural composites for drone frame applications, offering a sustainable pathway for developing high-performance materials while simultaneously addressing the issue of textile waste pollution. This study investigates the effect of ramie and cotton fiber waste fabric stacking sequences on the physical and mechanical properties of composites for quadcopter drone frames. Waste fabric was selected as an eco-friendly material...
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Pengaruh Motivasi Kerja dan Kemampuan Kerja Terhadap Kepuasan Kerja Pegawai Pada Dinas Kelautan Perikanan Kabupaten Bima
Jurnal Ekonomi, Bisnis dan Manajemen (EBISMEN)
Vol 4
, No 4
(2025)
This study aims to analyze the influence of work motivation and work ability on employee job satisfaction at the Department of Marine and Fisheries of Bima Regency. The research employed a quantitative approach with an associative type of study. The population consisted of 67 employees, and a sample of 38 civil servants was selected using a purposive sampling technique. Data were collected through a closed-ended questionnaire using a five-point Likert scale and analyzed using multiple linear reg...
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Transformer-Augmented Deep Learning Ensemble for Multi-Modal Neuroimaging-Based Diagnosis of Amyotrophic Lateral Sclerosis
Asuai, Clive
; Andrew, Mayor
; Arinomor, Ayigbe Prince
; Ogheneochuko, Daniel Ezekiel
; Joseph-Brown, Aghoghovia Agajere
; Merit, Ighere
; Collins, Atumah
Journal of Computing Theories and Applications
Vol 3
, No 2
(2025)
Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disorder that presents significant diagnostic challenges due to its heterogeneous clinical manifestations and symptom overlap with other neurological conditions. Early and accurate diagnosis is critical for initiating timely interventions and improving patient outcomes. Traditional diagnostic approaches rely heavily on clinical expertise and manual interpretation of neuroimaging data, such as structural MRI, Diffusion Tensor...
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Dampak Price, Green Knowledge, dan Electronic Word of Mouth terhadap Purchase Intention Pada Sepeda Listrik di Kediri
Jurnal Ekonomi, Bisnis dan Manajemen (EBISMEN)
Vol 4
, No 4
(2025)
This study aims to analyze the effect of price, green knowledge, and electronic word of mouth (eWOM) on purchase intention toward electric bicycles in Kediri City. A quantitative approach with a causal-comparative design was employed. Data were collected through an online questionnaire involving 112 respondents familiar with electric vehicle concepts, using purposive sampling. The validity and reliability tests confirmed that all research instruments were valid and reliable. Data analysis was pe...
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EFL Teachers’ Readiness in Implementing Artificial Intelligence Tools through Daily Classroom Basis
Journal of Emerging Technology in Teaching and Learning
Vol 1
, No 2
(2025)
With the exponential advancement of sophisticated artificial intelligence tools, second language educators need to embrace this inevitable educational shift by possessing a more comprehensive understanding of how to maximize the full benefits of these powerful, technology-driven learning supports in their regular teaching and learning enterprises. With respect to the above-mentioned notion, the researchers undertook this small-scale library study using a thematic analysis approach. With the supp...
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Predicting First-Year Student Performance with SMOTE-Enhanced Stacking Ensemble and Association Rule Mining for University Success Profiling
Kikunda, Philippe Boribo
; Kasongo, Issa Tasho
; Nsabimana, Thierry
; Ndikumagenge, Jérémie
; Ndayisaba, Longin
; Mushengezi, Elie Zihindula
; Kala, Jules Raymond
Journal of Computing Theories and Applications
Vol 3
, No 2
(2025)
This study examines the application of Educational Data Mining (EDM) to predict the academic per-formance of first-year students at the Catholic University of Bukavu and the Higher Institute of Edu-cation (ISP) in the Democratic Republic of Congo. The primary objective is to develop a model that can identify at-risk students early, providing the university with a tool to enhance student support and academic guidance. To address the challenges posed by data imbalance (where successful cases outnu...
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2 Sitasi
Model Klasifikasi Emosi Berbasis Teks dengan Algoritma Decision Tree dan Support Vector Machine
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 7
, No 2
(2025)
Text-based communication has become a key means of interaction across various sectors. Previous studies have applied supervised learning algorithms to emotion classification in text. These studies used different datasets, but this diversity also introduced a risk of overfitting in text-based emotion classification models. Consequently, the use of cross-validation and hyperparameter optimization is required to ensure the model’s generalization ability. The aim of this research is to compare the p...
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Implementasi Algoritma K-Nearest Neighbor Dalam Prediksi Penyakit Jantung
Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 7
, No 2
(2025)
Heart failure is a serious and pressing health problem that affects millions of people worldwide. Several factors influence the occurrence of heart failure, such as age, type of pain, blood pressure, cholesterol levels, and other risk factors associated with heart disease. With current technological developments, data mining and machine learning can be used to predict patient health conditions. Therefore, the problem of this research is how to implement data mining techniques for identifying hea...
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Hybrid Dynamic Programming Healthcare Cloud-Based Quality of Service Optimization
Journal of Computing Theories and Applications
Vol 3
, No 2
(2025)
The integration of Internet of Things (IoT) with cloud computing has revolutionized healthcare systems, offering scalable and real-time patient monitoring. However, optimizing response times and energy consumption remains crucial for efficient healthcare delivery. This research evaluates various algorithmic approaches for workload migration and resource management within IoT cloud-based healthcare systems. The performance of the implemented algorithm in this research, Hybrid Dynamic Programming...
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