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Pembuatan Dan Penerapan Pupuk Organik Cair (Kocor) di Kebun Lordes Dalam Upaya Meningkatan Pertumbuhan Tanaman Melon (Cucumis melo L.)
Bria, Deseriana
; Mamo, Wenselaus
; Aja, Lorensius Yustianus
; Ndua, Natalia Desy Djata
; Naisali, Hyldegardis
; Tay, Delviana
; Naitili, Alexandria
The study aimed to develop and apply liquid organic fertilizer (kocor) in Lordes Farm to improve the growth and productivity of melon (Cucumis melo L.). The production of liquid fertilizer was carried out through fermentation using brown sugar, EM4, humic acid, and urea as nutrient sources, producing a nutrient-rich liquid suitable for soil application. The application was conducted by drenching the fertilizer around the root zone at regular intervals. The results showed that liquid organic fert...
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Development of contextual learning-based mathematics teaching modules on rational number materials
This research aims to develop a mathematics teaching module on rational number material for grade VII junior high school students that is valid, practical, and effective. This research is motivated by students' limited understanding of rational numbers and by the limitations of teaching materials that fail to connect the material to real-life contexts systematically. The research gap lies in the limited development of contextual modules that not only focus on validity and practicality but also c...
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A Nonlinear mathematical model of student motivation dynamics with an empirical calibration framework and simulation analysis
Radhiatul Husna
; Angelina Zaskya Hulda
; Indah Rahmadani
; Miftahul Jannah
; Muhammad Zikra
; Najla Nafisa Arsy
; Nanda Putra Kartama
Student learning motivation is a dynamic construct that changes over time in response to support, academic pressure, and fatigue. However, many existing studies examine motivation only at a single point in time or rely on descriptive approaches, limiting their ability to quantify how motivation evolves. This study develops a nonlinear mathematical model of student motivation dynamics and links the model to an empirical calibration framework. The proposed model represents motivation as a bounded...
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Mangrove Loss and Blue Carbon decline in Indonesia’s Coastal Regions
Indonesia has the largest mangrove area in the world and supports high diversity, including 92 true mangrove species. They provide critical ecosystem services such as protection from floods, disaster risk reduction, fisheries support, carbon sequestration, and erosion prevention. Despite their importance, Indonesia has experienced significant mangrove loss/destruction over the past two centuries. This is majorly driven by factors such as pollution, illegal logging, rapid urbanization, agricultur...
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Strengthening Business Networks Through Technology Utilization for MSMEs in Pegandon District
Digital technology enables the growing development of online shopping. This also makes it possible for each seller to market their products or services with a wider range and costs that are not as expensive as conventional ones. Pegandon District has many business actors or MSMEs. The GRDP growth rate in Pegandon District has not recovered after the COVID-19 pandemic. One way to increase the GRDP growth rate is to increase the capability of business actors in selling or distributing their produc...
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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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Bottleneck Analysis and Improvement in Apparel Manufacturing Production Processes Using Integration Design of Experiments and Discrete Event Simulation
Bottlenecks in apparel manufacturing often cause unbalanced production flows, increased waiting times, and reduced system performance. This study aims to analyze and eliminate bottlenecks by integrating Design of Experiments (DOE) and Discrete Event Simulation (DES). Four workstations (X1–X4) were selected as experimental factors, while system performance was evaluated using bottleneck indicators across six production stages (Y1–Y6). DOE was used to design capacity scenarios, and DES assessed sy...
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EFFECTS OF PRETREATMENT METHODS ON THE LIGNOCELLULOSIC COMPOSITION OF SALACCA MIDRIBS
This study aims to determine the effect of pretreatment on hemicellulose, cellulose, and lignin content of Salacca midrib. Unlike previous studies, this study was designed to evaluate the effects of single-, double-, and triple-stage pretreatments on the sallaca midrib. The study was also designed to evaluate the differences in the physical and biological pretreatment methods. The pretreatments applied consist of physical, chemical, biological, physicochemical, chemical-biological, physical-biol...
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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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