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All Journal Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal Teknika : Jurnal Teoritis dan Terapan Bidang Keteknikan JOINTECOMS (Journal of Information Technology and Computer Science) Diteksi : Jurnal Pengabdian Kepada Masyarakat
Agus Sehatman Saragih
Universitas Palangka Raya
Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering

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Rancang Bangun Prototype Monitoring Banjir Berbasis Website Anorgi, Andrew; Saragih, Agus Sehatman; Sari, Nova Noor Kamala
Journal of Information Technology and Computer Science Vol. 3 No. 2 (2023): JOINTECOMS : Journal of Information Technology and Computer Science
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jointecoms.v3i2.10819

Abstract

Indonesia usually has certain areas where flooding occurs in different locations that can be flooded by rainfall that falls then will flow through the upstream of the river or the end of the river path where the water will pass and collect to a place where the water can accommodate is no longer available. again wasted water that there is no drain line. Based on these problems, a website-based flood monitoring prototype system is needed by adding the following functions IoT (Internet of Things) which can monitor floods about the condition of the water level graph on the website that can be seen by officers. This study uses an experimental method that was developed based on the needs of the research. In hardware system design used is microcontroller NodeMCU ESP8266 as system control. An ultrasonic sensor for water level and an anemometer to determine the current speed determines the water level in the box. Based on the research that has been carried out, the conclusion is that the system can predict when a flood will occur in the next few hours when water enters the box and the website graph appears. After the water is full it will send a notification via telegram bot to the owner of the officer within 3 minutes.
PERBANDINGAN NILAI AKURASI DISTILBERT DAN BERT PADA DATASET ANALISIS SENTIMEN LEMBAGA KURSUS Saputra, Ade Chandra; Saragih, Agus Sehatman; Ronaldo, Deddy
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 18 No. 2 (2024): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47111/jti.v18i2.13278

Abstract

Penelitian ini bertujuan untuk menerapkan Analisis Sentimen dalam Ulasan Kursus dengan menggunakan pendekatan Transfer Learning menggunakan model bahasa DistilBERT dalam konteks pengembangan sistem pendidikan. Dengan pertumbuhan yang pesat dalam domain e-learning dan layanan kursus online, pemahaman pengguna terhadap berbagai kursus menjadi semakin penting bagi institusi pendidikan. Metode transfer learning, yang mengandalkan model-model NLP yang sudah terlatih seperti DistilBERT, telah terbukti efektif dalam tugas analisis sentimen dengan kinerja yang baik dan efisiensi yang tinggi. Dengan peningkatan minat pada pembelajaran online, penelitian ini menginvestigasi bagaimana pendekatan analisis sentimen dapat memberikan wawasan yang lebih dalam terhadap ulasan kursus. Dengan penerapan teknik DistilBERT, diharapkan sistem mampu efektif dalam mengekstrak sentimen yang terkandung dalam ulasan tersebut, memberikan pemahaman menyeluruh terkait pendapat dan perasaan pengguna terhadap kursus yang mereka ikuti. Melalui penelitian ini, diharapkan dapat memberikan kontribusi penting bagi penyelenggara kursus dalam meningkatkan kualitas layanan pendidikan yang mereka tawarkan, memberikan umpan balik yang lebih terperinci dan tepat waktu kepada pengguna. Diharapkan diseminasi hasil penelitian ini memberikan pandangan yang lebih luas mengenai penerapan transfer learning dalam analisis sentimen, terutama dalam konteks ulasan kursus
Co-Authors Ade Chandra Saputra Anggeraeni, Natasya Anorgi, Andrew Christina, Sherly Efrans Christian Elshawina, Tiara Fahrizal Maulana Gunawan, Vincentius Abdi I Nyoman Adi Putra Khairul Fahmi Licantik, Licantik Melati, Erma Nova Noor Kamala Sari Pentanugraha, Elsan Ramadhani, Aditya Ananda Ronaldo, Deddy Sahay, Abertun Sagit Sherly Christina Viktor Handrianus Pranatawijaya Widiatry, Widiatry