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Addressing Algorithmic Bias and Data Privacy in Human Resource Management
Herdiana, Hendi
; Universitas Pendidikan Indonesia
Universitas Indonesia
Universitas Diponegoro
; Munir, Munir
; Department Management, Faculty of Economics and Business Education, Universitas Pendidikan Indonesia, Bandung, Indonesia
; Hurriyati, Ratih
; Department Management, Faculty of Economics and Business Education, Universitas Pendidikan Indonesia, Bandung, Indonesia
; Sultan, Mokh. Adib
; Department Management, Faculty of Economics and Business Education, Universitas Pendidikan Indonesia, Bandung, Indonesia
; Tua, Frans David
; Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia
; Ergashevna, Buriyeva Kibrio
; Faculty of pedagogical, Chirchik State Pedagogical University, Chirchik, Uzbekistan
Telematika
Vol 18
, No 2
(2026)
Artificial intelligence (AI) has transformed Human Resource Management (HRM) by automating recruitment, enhancing performance evaluation, and enabling data-driven workforce planning. However, its adoption raises critical concerns related to algorithmic bias, data privacy, and employee trust, creating a significant gap in understanding how these technical and ethical dimensions interact. This study aims to synthesize current evidence on the impact of AI on HRM functions, the challenges associated...
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Enhancing the GLANCE Framework for Line-Level Defect Prediction: An Empirical Study of Semantically-Aware Metrics and Non-Linear Classifiers
Telematika
Vol 18
, No 2
(2026)
Line-level defect prediction (LLDP) is critical for reducing software maintenance costs, yet its industrial adoption is often hindered by high false alarm rates that erode developer trust. While the state-of-the-art GLANCE-LR framework offers a lightweight solution, it relies on linear classifiers and purely syntactic heuristics, failing to capture the non-linear defect patterns and semantic risks associated with complex code constructs. To bridge the gap between operational efficiency and seman...
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Spatial Analysis of Flood-Prone Areas in Padang Terap, Kedah: Integrating Spatial Autocorrelation and Optimized Hotspot Analysis
Ahmad, Azizul
; Said , Mohd Zulhafiz
; Abdul Gapor , Salfarina
; Jamru , Lindah Roziani
; Jubit , Norita
; Mohd Najib , Sumayyah Aimi
; Masron, Tarmiji
; Ariffin, Nur Afiqah
; Zakaria , Yaniza Shaira
Forum Geografi
Vol 40
, No 1
(2026)
Flooding increasingly threatens socio-economic resilience in Malaysia, particularly in vulnerable districts such as Padang Terap, Kedah. Using a GIS-based framework integrating Spatial Autocorrelation (Moran’s I) and Optimized Hotspot Analysis (Getis-Ord Gi*), this study quantifies spatial clustering of flood-prone areas across four inundation levels (0.3 m–3.7 m). Results reveal intensifying positive spatial autocorrelation with rising flood depths, reflecting hydrological connectivity and topo...
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A Participatory GIS Framework for Multi-Hazard Climate Risk Mapping in Indonesia
Fariz, Trida Ridho
; Budiarti, Ratna
; Listyarini, Jassica
; Puspitasari, Atikah Tri
; Calysta, Nadia
; Naufal, Muhammad Ahganiya
; Heriyanti, Andhina Putri
; Eralita, Norma
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
Climate change has emerged as a global crisis with severe consequences for tropical and coastal regions. Pekalongan Regency, Indonesia, exemplifies these challenges, facing recurrent floods and landslides that threaten livelihoods and infrastructure. Risk mapping is urgently needed to guide adaptation strategies, yet many regions face constraints due to limited data availability. This study develops a multi-hazard risk mapping approach that integrates Geographic Information System (GIS) technolo...
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Development and Evaluation of an IndoBERT-Based NLP Model for Automated Clickbait Detection
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
The rapid growth of digital news platforms necessitates reliable and automated systems for maintaining content quality at scale. This study presents the engineering and evaluation of an IndoBERT-based Natural Language Processing (NLP) framework for automated clickbait detection in Indonesian news headlines. The proposed framework is designed as an end-to-end text classification pipeline, incorporating data preprocessing, tokenization, fine-tuning of a pretrained IndoBERT model, and systematic pe...
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Analysis and Design Android Augmented Reality Platform (Bilingual) for the Preservation of Cirebon Glass Paintings
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
This study analyzes and designs a bilingual Android Augmented Reality (AR) platform to support the digital preservation of Cirebon Glass Paintings. The development uses Unity and AR Core with a human-centered design approach. A total of 30 participants (n=30) evaluated usability and performance. 3D assets were produced using photogrammetry with an optimized polygon budget of ≤25,000 triangles per object. Model compression applied Draco and KTX2 to reduce memory load. Benchmark testing was conduc...
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Deep Learning-Based Classification of Cognitive Workload Using Functional Connectivity Features
Vineeta Khemchandani
; Alok Singh Chauhan
; Shahnaz Fatima
; Jalauk Singh Maurya
; Abhay Singh Rathaur
; Kumar Sharma, Narendra
; Daya Shankar Srivastava
; Vugar Abdullayev
Advance Sustainable Science, Engineering and Technology (ASSET)
Vol 8
, No 1
(2026)
Cognitive workload plays a vital role in tasks that demand dynamic decision-making, especially under high-risk and time-sensitive conditions. An excessive workload can lead to unexpected and disproportionate risks, whereas insufficient workload may cause disengagement, undermining task performance. This underscores the importance of maintaining an optimal level of mental focus in high-pressure situations to ensure successful task execution. This study leverages deep learning methods alongside fu...
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Pengembangan Aplikasi Analisis Sentimen pada Media Sosial XYZ untuk Pengumuman Acara Semilir Japan Matsuri 3 Menggunakan Metode SVM
Vol 5
, No 1
(2026)
Perkembangan media sosial yang pesat telah menghasilkan volume data teks yang sangat besar dalam bentuk opini dan ulasan pengguna. Analisis manual terhadap data ini untuk memahami sentimen publik tidak lagi efisien. Hal inilah yang mendasari dibuatnya sebuah aplikasi analisis sentimen otomatis menggunakan metode machine learning Support Vector Machine (SVM). Untuk mendukung penelitian yang dilakukan, peneliti menggunakan metode penelitian Research and Development (R&D) serta perancangannya m...
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Tinjauan Literatur: Chatbot dalam Budaya Populer: Peran, Tren, dan Dampaknya terhadap Masyarakat
Vol 5
, No 1
(2026)
Fenomena chatbot dalam budaya populer mengalami perkembangan pesat seiring majunya teknologi Artificial Intelligence (AI) dan Natural Language Processing (NLP). Melalui pendekatan Systematic Literature Review (SLR) terhadap sejumlah publikasi ilmiah periode 2017–2025, penelitian ini menganalisis tren, peran, dan dampak sosial-budaya dari penggunaan chatbot dalam berbagai domain seperti pendidikan, musik, anime, fandom, dan interaksi manusia–komputer. Hasil kajian menunjukkan adanya peningkatan s...
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Implementation of an Enterprise Resource Planning (ERP) System for Production Management and Raw Material Inventory in the Garment Industry
Syahwa Mutiara Putri
; Anita Rahmawati
; Alfina Chintya Bella
; Damar Aji Gurowo
; Supriyono Supriyono
JUISI : Jurnal Ilmiah Sistem Informasi
Vol 5
, No 1
(2026)
Industri garmen memiliki proses produksi yang kompleks dan ketergantungan tinggi terhadap ketersediaan bahan baku. Penggunaan sistem yang belum terintegrasi sering menimbulkan ketidaksesuaian data persediaan, keterlambatan produksi, dan keterbatasan dukungan dalam pengambilan keputusan manajerial. Kondisi tersebut mendorong perlunya penerapan sistem informasi terintegrasi. Penelitian ini menganalisis penerapan Enterprise Resource Planning (ERP) yang terintegrasi dengan Material Requirements Plan...
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