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Menampilkan 101–110 dari 7675 artikel
Data-Driven Techno-Behavioral Segmentation of Post-Pandemic Tourists Using TwoStep Cluster Analysis
Post-pandemic tourism is characterized by increasing behavioral heterogeneity as digital technologies reshape travel planning and mobility practices, challenging traditional demographic-based segmentation. This study develops a techno-behavioral, data-driven segmentation framework within the Smart Tourism Ecosystem perspective by conceptualizing digital adoption as a mediating mechanism between socio-demographic attributes and travel behavior. Using survey data from 805 domestic tourists in Yogy...
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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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Digital Transformation as a Reinforcement of Competitive Advantage and Resilience of Highland Tourism Villages in Central Java
This study aims to analyze the role of digital transformation in strengthening competitive advantage and resilience of highland tourism villages in Central Java. Highland tourism villages face increasing competition, environmental vulnerability, and market uncertainty, requiring adaptive and innovation-driven strategies. Digital transformation is considered a strategic instrument to enhance destination competitiveness, expand market access, and improve institutional resilience. This research emp...
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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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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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Design and Experimental Evaluation o`f a PID Based Ship Rudder Control Prototype Referenced to SOLAS
The Proportional–Integral–Derivative (PID)-based ship rudder control system is an effective method for maintaining a vessel’s heading automatically. This study aims to design and evaluate a ship rudder control prototype in accordance with SOLAS safety standards. The research method employed is Research and Development (R&D), which includes needs analysis, system design, prototype development, and model testing. The cargo ship prototype is equipped with an HMC5883L compass sensor, an Arduino...
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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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Analisis Pola Global dan Lokal Determinan Prevalensi Stunting di Jawa Tengah Tahun 2024 Menggunakan Geographically Weighted Regression
Nugroho, Ivan Wahyu
; Febriansyah, Candra Rifki Eka
; Rahmadhani, Oktavia Suci
; Murti, Basugandhi Sasangka
; Sabil, Safina
; Zuhdi, Shaifudin
; Shaifudin Zuhdi, Universitas Sebelas Maret, Fakultas Teknologi Informasi dan Sains Data
Jurnal Kesehatan Masyarakat Indonesia
Vol 21
, No 1
(2026)
Latar belakang: Stunting masih menjadi permasalahan kesehatan masyarakat yang serius di Indonesia, salah satunya di Jawa Tengah. Pendekatan analisis global sering kali belum mampu menangkap perbedaan pengaruh determinan stunting secara local. Tujuan: Penelitian ini bertujuan untuk mengidentifikasi pola global dan lokal determinan stunting di Jawa Tengah menggunakan. Metode: Penelitian kuantitatif ini menggunakan data sekunder agregat dari 35 kabupaten/kota di Jawa Tengah. Analisis dilakukan meng...
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