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Hastito, Fadli
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Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Engineering Industrial & Manufacturing Engineering

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Pengembangan Perangkat Surface Plasmon Resonance (SPR) sebagai Transduser Biosensor Hastito, Fadli; Juliastuti, Endang; Yuliarto , Brian
Jurnal Otomasi Kontrol dan Instrumentasi Vol 17 No 2 (2025): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2025.17.2.3

Abstract

This study developed a simple and cost-effective laboratory-scale Surface Plasmon Resonance (SPR) device called β SPR. SPR is a sensitive, real-time, and non-labeling technique widely used to detect the concentration and quality of solutions. However, the very high price of commercial SPR devices is a barrier, so a portable and affordable version was developed. The β SPR device uses a Kretschmann configuration with a 670 nm laser, a polarizer, and a modified Porro BA4010 prism for a simpler and more efficient optical configuration. A thin gold film (~50 nm) is placed on the prism using immersion oil, and the test solution is flowed through a flow cell. The laser is fired at a 90° angle to induce p-polarized waves that trigger surface plasmon resonance. This phenomenon decreases the light reflectance, forming a dip curve used for analysis. The device was tested using glucose solution (0.05–0.27 M) and compared with a commercial SPR device (α SPR). The results show a shift in the angle with increasing concentration. The highest error was 6.53% at 0.05 M, and the lowest was 0.94% at 0.27 M. The β SPR sensitivity was recorded at 4.41⁰/M, showing promising performance for cost-effective biosensor applications.
Pemetaan Emosi Publik seputar Pengumuman UTBK 2025 di Indonesia: Pendekatan Multi-Label dengan Kalibrasi Bertarget Sari, Rizki Yustisia; Sabar, Sabar; Joni, Joni; Pratama, Gelard Unthirta; Ronal, Ronal; Hastito, Fadli
Jurnal Otomasi Kontrol dan Instrumentasi Vol 18 No 1 (2026): Jurnal Otomasi Kontrol dan Instrumentasi [Terbitan akan Datang]
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2028.18.1.1

Abstract

This study maps public emotions in Indonesian-language tweets related to the 2025 UTBK announcement using multi-label emotion classification. The main challenges in multi-label emotion classification on social media include extreme label imbalance, distribution shift between training and application data, and weak lexical signals for specific emotions. This study aims to build a reliable emotion modeling framework for long-tail social media corpora while demonstrating generalizable post-training calibration practices. The novelty lies in the integration of four components: (1) per-label posterior calibration using Platt scaling, (2) precision-targeted per-label thresholding frozen from the development set, (3) score-quantile–based rate targeting to align predicted prevalence with domain-based rates, and (4) context-limited lexicon-aware boosting with a final clamp. The proposed pipeline is lightweight and model-agnostic. This research adopts a quantitative experimental approach by varying post-training calibration components to measure their impact on classification performance. An IndoBERTweet model is trained using BCEWithLogitsLoss on manually annotated data, then calibrated and evaluated on development and test sets. The results demonstrate balanced micro- and macro-level performance, improved detection of minority labels, and emotion mapping over 3,500 tweets with prevalence distributions consistent with Plutchik’s theory of emotions.
Co-Authors Endang Juliastuti Joni Joni Pratama, Gelard Unthirta Ronal, Ronal Sabar Sabar Sari, Rizki Yustisia Yuliarto , Brian