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All Journal Jurnal Pendidikan Teknologi dan Kejuruan KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 E-Bisnis : Jurnal Ilmiah Ekonomi dan Bisnis Elkom: Jurnal Elektronika dan Komputer JUTIK : Jurnal Teknologi Informasi dan Komputer WIDYABHAKTI Jurnal Ilmiah Populer Journal on Education Jurnal Review Pendidikan dan Pengajaran (JRPP) Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Riset dan Inovasi Pembelajaran ARRUS Journal of Engineering and Technology Jurnal Mandiri IT Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika Brilliance: Research of Artificial Intelligence KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Ilmiah Manajemen, Bisnis dan Kewirausahaan Prosiding University Research Colloquium Smart Techno (Smart Technology, Informatic and Technopreneurship) Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Rechtsnormen Journal of Law GEMBIRA (Pengabdian Kepada Masyarakat) Jurnal SUTASOMA Journal of Engineering and Science Application JIS Siwirabuda (Jurnal Ilmiah Sains Sosial, Kewirausahaan dan Kebudayaan) KOMTEKS: Komputer dan Teknologi Sains
ABDI SUDIATMIKA, I PUTU GEDE
Institut Teknologi Dan Bisnis STIKOM Bali
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Journal : ARRUS Journal of Engineering and Technology

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AI-Based Tourist Guide Application in Bali Using Supervised Learning Method I Gusti Ngurah, Putra Arimbawa; I Made Dwi Darma Artanaya; Komang Ayu Krisna Dewi; I Putu Gede Abdi Sudiatmika
ARRUS Journal of Engineering and Technology Vol. 4 No. 2 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech3262

Abstract

Penelitian ini berfokus pada pengembangan aplikasi panduan wisata berbasis Kecerdasan Buatan (AI) dengan metode Supervised Learning untuk wisatawan di Bali. Urgensi penelitian ini didasari oleh kebutuhan akan panduan yang terstruktur dan kontekstual bagi wisatawan untuk menghindari pelanggaran norma dan adat istiadat setempat, yang sering terjadi karena kurangnya informasi. Tujuan penelitian adalah untuk menciptakan aplikasi yang dapat memberikan rekomendasi aktivitas "to do" dan "not to do" berdasarkan lokasi, preferensi, dan norma setempat di Bali. Metode yang digunakan meliputi pengumpulan data teks dan gambar terkait budaya, tradisi, dan aturan adat di Bali, yang kemudian digunakan untuk melatih model AI menggunakan Supervised Learning. Model ini akan dikembangkan dan diintegrasikan ke dalam aplikasi mobile. Aplikasi ini diharapkan mampu memberikan informasi dan rekomendasi wisata yang tepat, serta panduan terkait norma dan adat istiadat Bali, untuk meningkatkan pengalaman wisatawan dan menjaga kehormatan budaya lokal.
Comparison of LSTM and GRU Models Performance in Forecasting Gold Prices: A Case Study Using Historical Data from Yahoo Finance Sudiatmika, I Putu Gede Abdi; Putra, I Made Agus Wirahadi
ARRUS Journal of Engineering and Technology Vol. 4 No. 1 (2024)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/jetech2760

Abstract

This research aims to compare the performance of two types of recurrent neural network models, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), in forecasting gold prices based on historical closing price data. Historical gold price data from December 14, 2017, to March 14, 2024, was downloaded using the yfinance library. The data was normalized using MinMaxScaler and split into training and testing sets with an 80:20 ratio. LSTM and GRU models were constructed with two recurrent layers followed by a Dense layer for output. Both models were trained using the training data and evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and R-squared (R²) metrics. The experimental results indicate that the GRU model outperformed the LSTM model in predicting gold prices. GRU achieved an MSE of 337.70, MAE of 14.05, and R² of 0.933, whereas LSTM achieved an MSE of 808.98, MAE of 22.71, and R² of 0.839. Based on the model performance evaluation, it can be concluded that GRU consistently produced more accurate predictions closer to the actual values of gold prices compared to LSTM. This finding suggests that GRU may be a preferable choice in applications for forecasting gold prices using historical data.
Co-Authors , Rifky Lana Rahardian A.A Raka Jayaningsih A.A. Raka Jayaningsi Agus Yudi Wiputra Albert Fernando Albert Fernando Anak Agung Raka Jayaningsih Artana, Wayan Widya Bonanza, Muhammad Jodie Dewi, Ni Putu Thasya Tania Eka Yuliani Fakhriah, Syahriati Fathurriza, Ari Fridayanti, Ni Putu Yulia I Gusti Ayu Sri Melati I Gusti Ayu Sri Melati I Gusti Ayu Sri Melati, I Gusti Ayu I Gusti Ngurah Ketut Purwantha I Gusti Ngurah, Putra Arimbawa I Komang Budi Mas Aryawan I Komang Budi Mas Aryawan I Made Agus Widiana Putra I Made Dwi Darma Artanaya I Made Onky Antara I Made Pradipta I Made Pradipta I Made Wirayudha Jayendra I Putu Agus Bayu Bimantara I Putu Astya Prayudha I Putu Erwin Febriana I Putu Okta Priyana I Putu Yesha Agus Ariwanta Ida Ayu Lalita Rathintara Imama Lavi Insani Jayaningsih, A.A. Raka Jayanti, Ni Wayan Sri Kadek Adi Karismayana Kadek Ray Gangga Jyotika Marchendy Komang Ayu Krisna Dewi Komang Hari Santhi Dewi KOMANG HARI SANTHI DEWI . Komang Yogi Triana Kusumawati, Ni Made Refa Laksmi, Ida Ayu Agung Luh Putu Meyra Anjani Made Meita Puspadewi Melati, I Gusti Ayu Sri Ni Kadek Tasya Novita Devi Ni Putu Meiling Utami Ni Wayan Sri Jayanti Ni Wayan Sukarini Novita, Ni Kadek Tasya Nugraha, Dwi Haryadi Nyoman Bagus Paramartha Pradipta, I Made Pramartha, I Nyoman Bagus Pramartha, Nyoman Bagus Putra , I Made Agus Widiana Putra, I Made Agus Wirahadi Putra, Ida Ayu Gde Suwiprabayanti Putu Satya Saputra Rifky Lana Rahardian Santhi Dewi, Komang Hari Santhi, Komang Hari Saputra, I Gede Seri Dharma Bobby Saputra, S.TI., M.Kom., Putu Satya Setiawan, I Made Oka Adi Silvester Magnus Loogman Palit Syam, Riri Nurdina tanjung, rona Wayan Andrika Putera Wayan Andrika Putera Wayan Widya Artana Wiratama, Febri Yogi Arya Bawana Putra Raspati