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All Journal Ruwa Jurai: Jurnal Kesehatan Lingkungan Indonesian Journal on Data Science
Arumsari, Dewi
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Computer Science & IT Environmental Science Health Professions Public Health

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HUBUNGAN KEBISINGAN DENGAN KESEHATAN PEKERJA BAGIAN PRODUKSI DI PT. CENTRALPERTIWI BAHARI FISH FEEDMILL Arumsari, Dewi
Ruwa Jurai: Jurnal Kesehatan Lingkungan Vol. 12 No. 2 (2018): (Upload ulang versi cetak)
Publisher : Poltekkes Kemenkes Tanjung Karang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26630/rj.v12i2.2761

Abstract

Tingginya intensitas kebisingan di ruang produksi PT.Centralpertiwi Bahari Fish Feedmill akan memberikan dampak terhadap kesehatan pekerja, baik gangguan fisiologis maupun psikologis. Penelitian bertujuan untuk mengetahui hubungan faktor kebisingan dengan gangguan kesehatan, meliputi intensitas kebisingan, sumber kebisingan, pengendalian transmisi kebisingan, dan penggunaan APD.Penelitian bersifat analitik dengan rancangan cross sectional, dilakukan pada bulan Juni 2017 di ruang produksi PT. Centralpertiwi Bahari Fish Feedmill. Variabel penelitian yaitu intensitas kebisingan, sumber kebisingan, pengendalian transmisi kebisingan, dan penggunaan APD dan gangguan kesehatan akibat kebisingan berupa gangguan fisologis dan psikologis. Pengukuran kebisingan dengan Sound Level Meter pada 10 titik pengukuran. Wawancara dilakukan untuk mendapatkan karakteristik, serta keluhan fisologis dan psikologis pekerja.Hasil penelitian mendapatkan bahwa tingkat kebisingan berkisar antara 79,87-92,86 dB. Sebanyak 32,5% pekerja mengalami gangguan fisiologis dan 47,5% gangguan psikologis, akibat paparan kebisingan. Namun, keseluruhan variabel tidak terdapat hubungan yang bermakna dengan gangguan kesehatan pekerja.
Sistem Chabot Layanan Informasi Mahasiswa Menggunakan Algoritma Long Short-Term Memory Arumsari, Dewi; kharisma; Aesyi, Ulfi Saidata
INDONESIAN JOURNAL ON DATA SCIENCE Vol. 2 No. 2 (2024): Indonesian Journal On Data Science
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/ijds.v2i2.1489

Abstract

In the era of globalization and rapid information flow, the demand for efficient and accurate information, especially within academic institutions, is rising. Students often face challenges in accessing educational resources and real-time information, particularly outside official working hours. Existing online information services have limitations in providing continuous access. This research focuses on developing and evaluating a student information service chatbot system at Universitas Jenderal Achmad Yani Yogyakarta (UNJAYA) using the Long Short-Term Memory (LSTM) algorithm. The primary objective is to create a system that delivers real-time, accurate, and efficient information services to students. The Machine Learning Development Cycle (MLDC) is employed in the model development process, including stages such as data collection, processing, model training, evaluation, and implementation. The system's performance is tested using a questionnaire distributed to students, with responses measured on a Likert scale. The results demonstrate a chatbot with a 97.76% accuracy rate, 98.34% precision, and 97.76% recall. The overall system evaluation yielded an average score of 3.87, categorized as good. This research concludes that the LSTM-based chatbot successfully enhances information services at the Faculty of Engineering and Information Technology, providing an innovative solution to meet student needs in real-time
Co-Authors Kharisma Ulfi Saidata Aesyi