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All Journal Cakrawala : Jurnal Humaniora Bina Sarana Informatika Equilibrium: Jurnal Ilmiah Ekonomi, Manajemen dan Akuntansi Journal of Economic, Bussines and Accounting (COSTING) IJISTECH (International Journal Of Information System & Technology) Management Studies and Entrepreneurship Journal (MSEJ) Akrab Juara : Jurnal Ilmu-ilmu Sosial IJISTECH Jurnal Ekonomi Jurnal Ilmu Ekonomi Manajemen dan Akuntansi Jurnal Ilmiah Teknik Informatika (TEKINFO) CEMERLANG :Jurnal Manajemen dan Ekonomi Bisnis Jurnal Nuansa: Publikasi Ilmu Manajemen dan Ekonomi Syariah Ebisnis Manajemen Global Leadership Organizational Research in Management Brilliant International Journal of Management and Tourism Jurnal Manajemen, Bisnis dan Kewirausahaan Jurnal Esensi Infokom : Jurnal Esensi Sistem Komputer dan Informasi Optimal: Jurnal Ekonomi dan Manajemen
Bilgah Bilgah
Universitas Bina Sarana Informatika
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Medicine & Pharmacology Social Sciences Transportation

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The Role of Social Media Analytics in Predicting Green Consumer Behavior: A Conceptual Framework Bilgah Bilgah; Andrianto, Usman; Rastryana, Ulta; Kiswati, Sri; Maryoso, Slamet
Brilliant International Journal Of Management And Tourism Vol. 6 No. 2 (2026): Brilliant International Journal Of Management And Tourism
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/bijmt.v6i2.7011

Abstract

This study proposes a conceptual framework to examine the role of social media analytics in predicting green consumer behavior. As sustainability becomes increasingly important in consumer decision-making, social media has emerged as a powerful tool for influencing attitudes and behaviors. The framework suggests that social media engagement, measured through analytics such as likes, shares, comments, and sentiment, influences green attitudes, environmental awareness, and green purchase intentions, which ultimately affect consumer behavior. Additionally, the study highlights that generational differences, environmental concern, and trust in green claims moderate these relationships. The proposed model builds upon existing theories in consumer behavior and sustainability marketing, offering new insights into how digital engagement shapes green consumer choices. From a practical perspective, this framework provides guidance for marketers to leverage social media analytics in promoting sustainable consumption, especially by tailoring strategies to different generational segments. Future research should empirically test the framework, explore its applicability across diverse cultural contexts, and examine the role of emerging social media platforms in fostering sustainable consumer behavior.
Pengujian Robot Otomatis Pendeteksi Rintangan Berbasis Mikrokontroler Nurul Aisyah; Aan Rahman; Rio Wirawan; Bilgah Bilgah; Susan Rachmawati; Alsen Medikano; Adianta Sebayang
Jurnal Esensi Infokom : Jurnal Esensi Sistem Informasi dan Sistem Komputer Vol 5 No 2 (2021)
Publisher : Institut Bisnis Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55886/infokom.v5i2.264

Abstract

Robot pendeteksi rintangan merupakan suatu bentuk robot bergerak yang mempunyai misi mengikuti suatu track atau jalur berupa dinding yang telah ditentukan. Dalam perancangan dan implementasinya, masalah-masalah yang harus dipecahkan adalah sistem penglihatan robot, arsitektur perangkat keras (hardware) yang meliputi perangkat elektronik dan mekanik, dan organisasi perangkat lunak (software) untuk basis pengetahuan dan pengendalian secara waktu nyata. Tujuan tugas akhir ini adalah merancang dan mengimplementasikan suatu Automomous Robot Pendeteksi Rintangan Berbasiskan Mikrokontroler AT C52.
AI in Financial Forecasting : Improving Accuracy and Strategy M.Mahdi Alatas; Bilgah Bilgah; Eka Putri Hanyani; Resti Yulistria
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 1 (2025): Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i1.6541

Abstract

Financial forecasting faces growing challenges due to market volatility and the inadequacy of traditional models like ARIMA and linear regression in handling non-linear, high-frequency financial data. Artificial intelligence (AI), particularly models such as long short-term memory (LSTM) networks and transformer-based systems, has demonstrated superior performance in tasks like predicting S&P 500 index movements and assessing corporate credit risk in real time. These models not only improve accuracy but also enable strategic applications—for instance, integrating live sentiment data from financial news to adjust portfolio allocations within milliseconds. AI systems have also been used by investment firms to simulate recession scenarios and guide capital reserve strategies. However, adoption remains hindered by issues such as the “black box” nature of deep learning, inconsistent data quality, and concerns over algorithmic bias. As AI continues to evolve, its value lies not just in forecasting precision but in supporting adaptive, transparent, and forward-looking financial management
Co-Authors A Asep Aan Rahman Adelia Lukitasari Adianta Sebayang Alsen Medikano Amanda Dwi Shafira Arman Syah Putra Arman Syah Putra Dedi Suharyadi Desi Pitasari Destyaningsih Sutrisno Dewi Kuntari Eka Putri Handayani Eka Putri Hanyani M. Mahdi Alatas M.Mahdi Alatas Mety Titin Herawaty Murniyati Murniyati Nurhadi Nurhadi Nurul Aisyah Nurul Aisyah Nurul Aisyah Nurzalinar Joesah Rani Kurniasari Rani Suryani Resti Yulistria Rio Wirawan Rio Wirawan Safrezi Fitra Siti Dalsidah Slamet Maryoso Sri Kiswati Suripah . Susan Rachmawati Susan Rahmawati Ulta Rastryana Usman Andrianto