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Menampilkan 251–260 dari 16173 artikel
Strategic Integration of Lean Construction into Green Building Regulations: A Factor-Based Assessment of Green Construction Indicators
The construction sector plays a critical role in sustainability through effective construction waste management. In Indonesia, green building practices are guided by the Green Construction Site Index (GCSI) and the Minister of Public Works and Housing Regulation No. 21 of 2021; however, their strategic alignment with Lean Construction principles remains limited. This study examines the strategic integration of Lean Construction into green building regulations by validating regulatory-based indic...
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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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Pelatihan Koding dan Kecerdasan Artifisial bagi Guru SD di Sukoharjo sebagai Upaya Peningkatan Literasi Digital di Era Society 5.0
Buletin KKN Pendidikan
Vol 8
, No 1
(2026)
Era Society 5.0 menuntut penguatan literasi digital dan computational thinking sejak pendidikan dasar, namun kesenjangan kompetensi guru di daerah pedesaan masih menjadi tantangan utama dalam implementasinya. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kapasitas guru sekolah dasar dalam mengintegrasikan koding dan kecerdasan artifisial (AI) ke dalam pembelajaran sebagai upaya mendukung peningkatan literasi digital siswa. Kegiatan dilaksanakan di SDN 03 Mulur, Sukoharjo...
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Immersive Commerce: Implementasi Augmented Reality untuk Meningkatkan Kepercayaan Konsumen dalam Transaksi E-Commerce
DHARMA EKONOMI
(2026)
This study aims to describe the concept of Immersive Commerce based on Augmented Reality (AR) in increasing consumer confidence in E-Commerce transactions and to design a conceptual prototype design framework for an AR E-Commerce system with a clear technical flow. The research method uses a literature study through a comprehensive review of AR-based E-Commerce implementations and needs analysis from the perspective of consumer problems and business opportunities. The main problem identified is...
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Ekosistem Bisnis Digital: Analisis Faktor Kesuksesan UMKM Generasi Z di Indonesia
DHARMA EKONOMI
(2026)
Digital transformation has reshaped the landscape of MSMEs in Indonesia, particularly those managed by Generation Z. This study aims to analyze key success factors of Generation Z MSMEs in building sustainable digital business ecosystems. The research employs a systematic literature review methodology by analyzing various academic sources, industry reports, and related publications from 2019-2024. Findings reveal five primary success factors: adaptive digital technology adoption, high digital li...
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Pengaruh Liquidity, Leverage, Profitability, Sales Growth, dan Firm Size Terhadap Cash Holding
This research analyzed the influence of liquidity, leverage, profitability, sales growth, and firm size on cash holdings. The research is quantitative, using secondary data from annual financial reports of primary consumer industries listed on the Indonesia Stock Exchange from 2022 to 2024. Liquidity is measured by the Current Ratio, which is calculated as current assets divided by current liabilities. Leverage, proxied by the Debt-to-Equity Ratio, is measured by total liabilities divided by tot...
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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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Faktor Internal Terhadap Kinerja Keuangan Pada Perusahaan Sektor Barang Food & Beverage
KOMPAK : Jurnal Ilmiah Komputerisasi Akuntansi
Vol 1
, No 2
(2026)
This study aims to analyze the influence of internal company factors, including company size, networking capital, operating efficiency, liquidity, and leverage, on financial performance, proxied by Return on Assets. The research population includes 40 food & beverage subsector companies listed on the Indonesia Stock Exchange during the 2019–2024 period. Using purposive sampling, 17 sample companies were selected, yielding a total of 102 data observations. This study adopts a quantitative app...
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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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