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All Journal Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Jurnal Serumpun Teknik Informatika
Rizky Ananda Ramadhan
Universitas Pembangunan Nasional “Veteran” Jawa Timur
Humanities Computer Science & IT Economics, Econometrics & Finance Education Social Sciences Other

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Pengaruh Lingkungan Sekolah Terhadap Pembentukan Nilai Agama Siswa Sekolah Dasar di Surabaya Andiniya Rahma Heryanto; Windyana Ludfi Wardani; Syarafina Nur Shadrina; Muhammad Rizal Haris; Nabilah Liliana Putri; Rizky Ananda Ramadhan; Daffa Alif Firdaus; Erwin Kusumastuti
MISTER: Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Vol. 1 No. 3b (2024): JULI (Tambahan)
Publisher : UNIVERSITAS SERAMBI MEKKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/mister.v1i3b.1729

Abstract

Penelitian ini membahas mengenai pengaruh sebuah lingkungan sekolah terhadap pembentukan nilai dan karakter agama siswa sekolah dasar di Surabaya. Lingkungan sekolah mencangkup proses pembelajaran, kegiatan keagamaan, interaksi antara siswa dengan guru serta siswa dengan siswa lainnya. Penelitian ini menganalisis bagaimana faktor-faktor lingkungan sekolah, seperti budaya sekolah, kegiatan keagamaan, dan peran guru berkontribusi terhadap pembentukan nilai agama pada siswa. Artikel ini mengungkapkan bahwa lingkungan sekolah yang kondusif dan didukung oleh program-program keagamaan yang terstruktur dapat secara signifikan meningkatkan pemahaman dan penerapan nilai-nilai agama pada siswa. Metode yang digunakan dalam penelitian ini adalah tinjauan pustaka. Wawasan yang diperoleh dari analisis ini memberikan pemahaman yang lebih mendalam mengenai bagaimana lingkungan sekolah mempengaruhi pembentukan nilai agama seorang siswa sekolah dasar di Surabaya.
Predicting Bitcoin Price Trends Using an LSTM Model Based on Multi-Variable Technical Indicators Rizky Parlika; Ilham Asy’ari; Rizky Ananda Ramadhan
Jurnal Serumpun Teknik Informatika Vol. 1 No. 2 (2026): April 2026
Publisher : Yayasan Ibrahim Learning Centre Agam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66485/jsti.v1i2.21

Abstract

The sharp price fluctuations in the cryptocurrency market, particularly in Bitcoin (BTC), create significant risks while simultaneously offering speculative profit potential for investors. Traditional analytical methods are often ineffective in detecting non-linear patterns present in stochastic financial time series data. This study proposes the application of a Deep Learning model utilizing the Long Short-Term Memory (LSTM) architecture to project the directional trend of Bitcoin prices (whether upward or downward) for the upcoming one-hour period. In the model's development, historical price data is integrated with a set of crucial technical variables, including the Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Exponential Moving Average (EMA), which serve as input attributes to enhance accuracy. Market data is retrieved in real-time via the Binance API, covering the last 1000 candlesticks. Experimental results using a Stacked LSTM architecture demonstrate that the model achieves an accuracy rate of 51.08% on the test data. Although this classification accuracy is considered moderate, a simple backtesting simulation indicates a positive profitability potential of 2.88% with a win rate of 48.39%. The output of this research also includes a web-based system prototype that integrates a Python backend with a visual interface for real-time monitoring of prediction signals.
Co-Authors Andiniya Rahma Heryanto Daffa Alif Firdaus Erwin Kusumastuti Ilham Asy’ari Muhammad Rizal Haris Nabilah Liliana Putri Parlika, Rizky Syarafina Nur Shadrina Windyana Ludfi Wardani