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Development and Performance Evaluation of a Micro-Scale RDF Briquette–Fueled Steam Power Prototype
Syarifah
; Latricia Aina Hidayat
; Rini Yunita Sari
; Maratis, Jerry
; Andri Krisna Hidayat
; Pawenary
; Hendri
Plastic waste is a major environmental problem in Indonesia due to its non-biodegradable nature. One innovative solution is converting waste into energy using Refuse-Derived Fuel (RDF) briquettes for small-scale power generation. This research designed and tested an RDF-based micro power plant prototype using briquettes composed of 80% dry organic biomass and 20% plastic for safe and stable combustion. The prototype consists of a combustion chamber, heat exchanger, impulse-type micro steam turbi...
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Attention-Augmented GRU for Stock Forecasting: A Trade-Off Between Directional Accuracy and Price Prediction Error
R. Daniel Hartanto
; Guruh Fajar Shidik
; Farrikh Alzami
; Ahmad Zainul Fanani
; Aris Marjuni
; Abdul Syukur
Journal of Computing Theories and Applications
Vol 3
, No 4
(2026)
Attention mechanisms have been widely incorporated into recurrent neural network architectures for financial time series forecasting, with most prior work reporting improvements in price-level error metrics. This study revisits that claim through a controlled empirical comparison of four deep learning architectures on nearly two decades of Telkom Indonesia (TLKM) closing price data from the Indonesia Stock Exchange (IDX). The models evaluated are a three-layer Gated Recurrent Unit (GRU) baseline...
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Behavioral Malware Detection via API Call Sequences: A Comparative Study of LSTM and Transformer Architectures Using NLP-Inspired Representations
Journal of Computing Theories and Applications
Vol 3
, No 4
(2026)
The increasing sophistication of malware has rendered traditional signature-based detection methods insufficient, necessitating behavior-driven and adaptive analytical frameworks. This study presents a sequential deep learning framework that models system-level API call sequences as structured linguistic representations for behavioral malware detection. Unlike conventional comparative studies, this work systematically evaluates recurrent and attention-based architectures under controlled experim...
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A Systematic Analysis of the Impact of Non-Academic Factors on Student Academic Performance Prediction Using Data Mining
Ningsih, Gabriella Caroline Prihayu
; Universitas Sebelas Maret
; Liantoni, Febri
; Sebelas Maret University
; Sujana, Yudianto
; Sebelas Maret University
Telematika
Vol 19
, No 1
(2026)
This study investigates the prediction of students' academic performance using machine learning models through the analysis of 27 research articles. The primary objective is to identify a minimal set of essential features that significantly influence academic outcomes, aiming to optimize model performance and reduce data complexity. A Systematic Literature Review (SLR) was conducted following the PRISMA framework, focusing on key features such as midterm grades, faculty, department, demographic...
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Exploration of the Gesek Godong Leaf-Transfer Technique for Textile Pattern Creation Using Wooden and PVC-Based Tools
Textile motifs are works that employ designs created through various techniques. One method of creating textile motifs is the gesek godong technique. This technique is a traditional method in textile design that uniquely uses dried leaves as natural materials to transfer leaf patterns. In this study, the gesek godong technique will be developed using different tools: a wooden rolling pin, a wooden cutting board, and PVC pipe. This study aims to explore the creation of innovative and creative tex...
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ENVIRONMENTAL HEALTH RISK ASSESSMENT OF GROUNDWATER NITRATE AND NITRITE EXPOSURE AMONG FARMERS IN COASTAL AREA OF REMBANG, CENTRAL JAVA, INDONESIA
Irawati, Septiria
; Putri, Cita Fitria
; LPPM Universitas Diponegoro
; Gunungsari Village Government, Kaliori Subdistrict, Rembang Regency
Jurnal Kesehatan Masyarakat Indonesia
Vol 21
, No 1
(2026)
Background: The increasing use of fertilizers and pesticides in agricultural areas maycontaminate groundwater with nitrate and nitrite, posing health risks. Objective: This study aimed to assess the health risk from nitrate and nitrite exposure through groundwater consumption among farmers in the coastal area of Rembang, Central Java. Methods: A crosssectional study was conducted in Gunungsari Village, Kaliori Subdistrict. Groundwater samples from seven households were analyzed using spectrophot...
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Antagonistic activity of phyllosphere fungi isolated from medicinal plants against Colletotrichum sp. causing anthracnose in chilli (Capsicum annuum L.)
Anthracnose disease caused by the fungus Colletotrichum sp. is one of the main problems in chili cultivation (Capsicum annuum L.) and can cause significant yield losses. The intensive use of chemical pesticides in controlling this disease has a negative impact on the environment and health. This study aimed to evaluate the antagonistic potential of phyllosphere fungi isolated from five medicinal plants, namely Phaleria macrocarpa, Curcuma domestica, Kleinhovia hospita, Hibiscus rosa-sinensis, an...
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Evaluating Civil Servant Selection through Machine Learning Analysis of National Insight, General Intelligence, and Personal Characteristics Test Scores
This study analyzes the score distribution of 2,490 candidates in the 2024 Ministry of Finance Public sector recruitment, focusing on the CNI, GIT, and PCT sections using machine learning classification. Models used include Logistic Regression (accuracy 0.7897), Random Forest (0.9779), and XGBoost (0.9809), all trained with default parameters (n_estimators=100, max_depth=None) and evaluated using accuracy, precision, recall, and F1-score. While ensemble models outperformed Logistic Regression, t...
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Viscosity Modeling of MES and SLS Using Machine Learning Method
Fathaddin, Muhammad Taufiq
; Setiati, Rini
; Akbar, Fahrurrozi
; Sumirat, Iwan
; Bharoto
; Ramadhan, Ranggi Sahmura
; Onnie Ridaliani Prapansya
; Ristawati, Arinda
Viscosity is crucial to improve the efficiency of injected fluids for oil displacement in reservoirs. Traditionally, research has focused on polymers that help reduce the mobility of injected fluids, while surfactant viscosity has received less consideration. This research investigated the viscosity behavior of methyl ester sulfonate (MES) and sodium lauryl sulfate (SLS) surfactant solutions using a machine learning method—adaptive neurofuzzy inference system (ANFIS). This study aimed to predict...
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Cam Simulation and Dimensional Verification of CNC-Machined Orthopaedic Femoral Components: Toolpath Optimization and 3D-Scan Metrology
Setyoadi, Yuris
; Rifky Ismail
; Bayuseno, Athanasius Priharyoto
; I Nyoman Jujur
; Novriansyah, Robin
; Darmanto
; Prawibowo, Hartanto
; Anggoro, Paulus Wisnu
This study investigates the optimization of manufacturing femoral components for Total Knee Replacement (TKR) using Computer-Aided Manufacturing (CAM) simulation and 5-axis CNC milling, followed by dimensional verification based on 3D scanning. The machining process was simulated in Autodesk PowerMill to generate collision-free toolpaths for AISI 316L stainless steel. Dimensional verification was conducted by comparing the 3D-scanned physical model (using Creality CR-Scan Ferret Pro) with the or...
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