Claim Missing Document
Check
Articles

Found 2 Documents
Search

Sentiment Analysis of Instagram Comments for Monitoring Personal Branding of YBM Brilian Scholarship Recipients, Regional Office, Makassar Kherani, Riska; Arda, Abdul Latief; Jalil, Abdul; Asnimar, Asnimar; Iskandar, Akbar
Inspiration: Jurnal Teknologi Informasi dan Komunikasi Vol. 15 No. 1 (2025): Inspiration: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat Sekolah Tinggi Manajemen Informatika dan Komputer AKBA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35585/inspir.v15i1.103

Abstract

This study focuses on the implementation of the Multilingual BERT (mBERT) architecture combined with a Long Short-Term Memory (LSTM) model to classify Instagram comments into positive, negative, and neutral sentiments. The primary objective is to support the monitoring of personal branding among recipients of the Bright Scholarship managed by the Baitul Mall BRILiaN Foundation (YBMRILiaN) at the Makassar Regional Office. The experimental results indicate that mBERT is capable of effectively analyzing sentiment from Instagram comments on scholarship awardees from Hasanuddin University and UIN Alauddin Makassar. Using a sample of 10 awardees, the model demonstrates a consistent increase in accuracy across epochs, achieving an average accuracy of 63.87% and a peak accuracy of 73.18% for Awardee 10, with a corresponding loss value of 1.094. These findings highlight the potential of this approach to assist scholarship organizers in systematically evaluating the personal branding of awardees on social media. Moreover, the analysis identifies one awardee whose personal branding performance may require further consideration regarding scholarship eligibility.
Development of a Web-Based Electronic Data Capture Monitoring System Using the PIECES and Waterfall Models Iskandar, Akbar; Aji Bimantara, Vitara; Kamaruddin, Kamaruddin; Kherani, Riska; Patel, Kavya; Amiruddin, Erwin Gatot; Sobirov, Bobur
Jurnal Abdimas Cendekiawan Indonesia Vol. 2 No. 3 (2025): September
Publisher : Yayasan Cendekiawan Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jaci.v2i3.148

Abstract

The development of digital transactions has driven the need for more accurate and easily monitored Electronic Data Capture (EDC) devices to support payment processes in the retail and distribution sectors. However, the manual and unintegrated EDC monitoring mechanism leads to data inconsistencies, delays in operational information, and low device traceability throughout its lifecycle. This research develops a real-time, web-based EDC population monitoring system to improve device management efficiency and operational data quality. The needs analysis was conducted using the PIECES framework, while the development process adopted the Waterfall model, encompassing analysis, design, implementation, and testing. The resulting system supports device registration, distribution monitoring, activation tracking, mutation recording, and device closure. Test results show significant improvements in data accuracy, reporting speed, and monitoring process effectiveness compared to manual methods. These findings contribute to the literature on enterprise digital asset management and demonstrate that a structured development approach can optimize the EDC device monitoring process in large-scale retail networks.