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All Journal Jurnal Ilmiah Kursor Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Ansyah, Adi Surya Suwardi
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Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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Integrated Named Entity Recognition and Identical-Entity Detection for Extracting Unique Information Sources in News Articles Ansyah, Adi Surya Suwardi; Oranova Siahaan, Daniel; izqi Paradisiaca , Brian R
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 16 No. 2 (2025): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v16i2.27687

Abstract

Native advertising is often difficult to detect because it resembles regular news articles. One indicator is the absence of diverse information sources or the reliance on a single perspective. Therefore, it is necessary to employ an extraction technique capable of consolidating various forms of identical entity mentions. This study integrates an NER model based on XLNet+BiLSTM+CRF with identical entity classification using Levenshtein distance features and static and contextual vector representations. The results show an F1-score of 93.71% at the entity level and 92.84% for identical entity identification, along with a list of unique citation sources. These findings demonstrate that this unique list can be an additional feature in detecting native advertising, which often relies on a single source. With an average unique entity coverage of 97.40%, the proposed architecture can extract unique entities within news articles
APPLYING FUZZY LOGIC AND IOT FOR INTELLIGENT AUTOMATION IN CRAYFISH WATER QUALITY CONTROL Ansyah, Adi Surya Suwardi; Arifin, Miftahol; Laili, Umi
Jurnal Ilmiah Kursor Vol. 12 No. 3 (2024)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v12i3.334

Abstract

Crayfish, known for their high market value due to their substantial meat volume compared to other freshwater shrimp, necessitate improved cultivation efficiency, which can be significantly enhanced with advanced technology. In this study, we designed a highly effective automatic water quality control system specifically for crayfish cultivation that strategically integrates an Internet of Things (IoT)-based control system and a smartphone application. Uniquely, the system incorporates fuzzy logic within the decision-making algorithm, which maintains water quality by adaptively adjusting drainage and temperature control parameters based on dynamic pH and turbidity conditions. This seamless and responsive mechanism ensures optimal cultivation conditions are maintained efficiently. This study manifests that this novel IoT and fuzzy logic technology integration proved effective for automatic water quality control and monitoring. The research contribution is the pioneering integration of fuzzy logic and IoT technologies to devise an intelligent automation system for crayfish water quality control. This system offers real-time remote monitoring and control from a smartphone application and automatically adapts to varying pH and turbidity conditions, ensuring consistently optimal water quality for crayfish cultivation. Such a system holds the potential to set a new standard for precision aquaculture, elevating productivity and sustainability within the crayfish farming sector.
Co-Authors Daniel Oranova Siahaan izqi Paradisiaca , Brian R MIFTAHOL ARIFIN, MIFTAHOL Umi Laili