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Menampilkan 81–90 dari 9952 artikel
Design and Optimization of an Automated Ceramic Drying System Using Arduino for Small and Medium Enterprises
The ceramic drying process in Small and Medium Enterprises (SMEs) often relies on ambient conditions, leading to prolonged drying times and inconsistencies in product quality. This study presents the design and optimization of an automated ceramic drying system that utilizes an Arduino-based microcontroller to regulate temperature and airflow in real-time. A full factorial experimental design was employed to investigate the influence of two critical parameters—temperature (35°C, 40°C, 45°C) and...
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Strengthening Vocational High School Teachers' Pedagogical Competence in Developing AI-Based Learning Materials through Prompt Engineering Training
This paper reports a community service program designed to strengthen vocational high school teachers' pedagogical competence through prompt engineering training to support AI-assisted instructional design. The program was conducted as an in-house training at SMK Negeri 1 Bulakamba involving 90 teachers from different subject areas. Activities included initial needs mapping, hands-on training on developing teaching modules, lesson plans, and assessment items using structured prompts, followed by...
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Enhancing Sustainability in Linear WSNs Using DSDVTRI: A Triple-Interleaving Routing Approach for Pipeline Monitoring
Kumaran, Divya Nacciar
; Siva Kumar Subramaniam
; Ahamed Fayeez Bin Tuani Ibrahim
; Vigneswara Rao Gannapathy
The safety and efficiency of oil and gas pipelines remain critical due to the high risks associated with leaks, pressure surges, and undetected structural damage. WSNs provide an effective solution for real-time monitoring by deploying sensor nodes along the pipeline. However, existing routing protocols such as DSDV and AODV face challenges with congestion, packet loss, and uneven energy consumption in long linear topologies. This study proposes DSDVTRI, a triple-interleaving extension of the DS...
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Microwave-Pyrolysed Rice Husk-Derived Activated Carbon as a Sustainable Anode Material for Lithium-Ion Half-Cell Batteries
Surib , Nur Atiqah
; Mohd Abdah, Muhammad Amirul Aizat
; Farhana Syakirah Ismail
; Wong, Weng Pin
; Ab Latif, Farah Ezzah
; Mustafa, Muhammad Norhaffis
; Rashmi Walvekar
; Mohammad Khalid
Agricultural waste biomass is explored as a sustainable precursor for activated carbon. In this study, rice husk-derived activated carbon (RHAC) was synthesized via microwave-assisted pyrolysis and KOH activation at 600, 700, and 800 °C. The KOH activation enhanced the thermal stability of the samples, with RHAC_700 exhibiting a spongy, interconnected structure and a surface area of 390.33 m² g⁻¹. When evaluated as a half-cell anode materials for lithium-ion batteries, RHAC_700 delivered an init...
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Analisis Penerimaan Pengguna terhadap Gamifikasi Shopee Games dan Dampaknya pada Perilaku Pembelian Online: Perspektif Technology Acceptance Model (TAM)
Penelitian ini bertujuan menganalisis penerimaan pengguna terhadap fitur gamifikasi Shopee Games serta dampaknya terhadap perilaku pembelian online menggunakan kerangka Technology Acceptance Model (TAM). Pendekatan kuantitatif dengan metode survei diterapkan pada 100 responden pengguna Shopee Games. Analisis jalur berbasis regresi berganda digunakan untuk menguji hubungan antar konstruk TAM: persepsi kemudahan penggunaan (PEOU), persepsi kegunaan (PU), sikap penggunaan (ATU), niat perilaku (BI),...
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Algoritma Apriori untuk Menganalisis Pola Pembelian Produk di PT. Tridaya Medima Sakti
WillaWiranata, Danniel Riyantus
; Sihotang, Fransiska Prihatini
; WillaWiranata, Danniel Riyantus
; Sihotang, Fransiska Prihatini
Ketidakseimbangan antara tingkat persediaan dan permintaan pasar dapat mengakibatkan kelebihan stok, meningkatnya biaya penyimpanan, dan meningkatnya risiko kerusakan produk. PT. Tridaya Sakti Medima, sebuah perusahaan distribusi farmasi yang berlokasi di Palembang, menghadapi tantangan serupa dalam mengelola persediaannya. Penelitian ini bertujuan untuk menganalisis pola pembelian dengan menerapkan teknik penambangan data menggunakan algoritma Apriori dan untuk merancang sistem rekomendasi prod...
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Experimental Analysis of Voltage and Multi-Point Temperature Distribution in a 6S Lithium-Ion Battery Pack Under Constant Current Loading
Lithium-ion batteries are widely utilized in energy storage applications; however, temperature non-uniformity remains a critical issue affecting performance, safety, and lifespan. This study presents an experimental investigation of the correlation between voltage and multi-point temperature distribution in a 6S lithium-ion battery pack under a constant ±5 A charge–discharge current. Temperature measurements were obtained from three sensor locations to capture spatial thermal variations during o...
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Optimization of Mangrove Glucomannan Addition to Improve Physicochemical Properties of Kefir
Jeki Mediantari Wahyu Wibawanti
; Zulfanita
; Dita Yuzianah
; Harisun Binti Ya’acob
; Anang Mohamad Legowo
; Setya Budi Muhammad Abduh
; Sri Mulyani
Kefir is widely recognized as a functional fermented dairy product. However, its physicochemical stability, particularly pH, acidity, and syneresis, remains a challenge during processing and storage. The addition of functional polysaccharides, such as mangrove-derived glucomannan, has been proposed to improve kefir quality. This study aimed to investigate the effect of mangrove-derived glucomannan on the physicochemical properties of kefir. A Completely Randomized Design with different concentra...
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Hybrid XGBoost-LSTM Framework for Accurate SOC, SOH, DOD and Internal Resistance Estimation in Li-ion Cells
Accurate estimation of State of Charge (SOC), State of Health (SOH), Depth of Discharge (DOD), and internal resistance is critical for Battery Management Systems (BMS) in electric vehicles and energy storage. Conventional methods fail to capture the nonlinear and temporal dynamics of lithium-ion cells, while existing machine learning approaches lack systematic benchmarking for embedded deployment. This study evaluates three hybrid models XGBoost-LSTM, XGBoost-SVR, and Linear Regression-Random Fo...
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MORPHOLOGICAL CHARACTERIZATION OF BRAIN TUMOR TISSUE IN MRI IMAGES USING CNN AND TRANSFER LEARNING
Hilmi, Dafa Fadhilah
; Wibawa, Aji Prasetya
; Agustavada, Ardha Ardhana Putra
; Sholum, Abdullah
; Dwiyanto, Felix Andika
This study evaluates the role of computational pattern recognition as an observational method for analyzing morphological characteristics of brain tumor tissue in MRI data. A total of 6,056 labeled MRI images, including glioma, meningioma, and pituitary tumor cases, were examined. The images were standardized to maintain uniform structural representation and processed using three convolutional-based architectures: a baseline CNN, MobileNetV2, and EfficientNet-B0. Model performance was assessed u...
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