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All Journal Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Innovative and Creativity
Muhammad Farhan Fadhila
Universitas Bina Sarana Informatika
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mathematics Neuroscience Social Sciences Transportation Other

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Rancang Bangun Mobil Remote Control dengan Arduino Berbasis Internet of Things (IoT) Muhammad Farhan Fadhila; Budi Supriyadi; Reni Widyastuti; Dicky Purwanto
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 5 (2025): Oktober 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i5.9834

Abstract

Abstrak - Penelitian ini merancang sebuah sistem mobil remote control yang berbasis Internet of Things (IoT) dengan menggunakan Arduino dan modul Bluetooth HC-06 sebagai perangkat penghubung nirkabel. Sistem ini memungkinkan pengendalian mobil secara jarak jauh melalui aplikasi yang terhubung dengan perangkat seperti smartphone android. Arduino bertindak sebagai mikrokontroler utama yang mengatur motor dan komponen lain, sementara Bluetooth HC-06 menyediakan konektivitas antar perangkat untuk komunikasi data. Dengan integrasi IoT, sistem ini juga memungkinkan pemantauan kondisi mobil secara real-time melalui jaringan internet. Hasil dari penelitian ini menunjukkan bahwa penerapan teknologi Arduino dan IoT dapat menghasilkan solusi kontrol mobil yang efisien, yang memiliki potensi aplikasi dalam pengembangan teknologi otomasi dan pengendalian perangkat berbasis IoT.Kata Kunci: Internet of Things; Teknologi; Arduino; Remote control;  Abstract - This study designs a remote control car system based on the Internet of Things (IoT) using Arduino and the Bluetooth HC-06 module as a wireless connecting device. This system allows remote control of the car through an application connected to a device such as an Android smartphone. Arduino is the main microcontroller that regulates the motor and other components, while Bluetooth HC 06 provides connectivity between devices for data communication. With IoT integration, this system also allows real-time monitoring of car conditions via the internet network. The results of this study indicate that the application of Arduino and IoT technology can produce an efficient car control solution, which has potential applications in the development of automation technology and IoT-based device control.Keywords: Internet of Things; Technology; Arduino; Remote control;
Prediksi Harga Penutupan Indeks Harga Gabungan (IHSG) Menggunakan Algoritma Long Short-Term Memory Berbasis Data Historis Muhammad Farhan Fadhila; Rian Septian Anwar; Albert Riyandi
Journal of Innovative and Creativity Vol. 5 No. 3 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v5i3.4318

Abstract

The dynamic fluctuation of stock prices makes market movement prediction a significant challenge in financial analysis. This study aims to develop and evaluate a Long Short-Term Memory (LSTM) model to predict the daily closing price of the Indonesia Composite Index (IDX Composite) using historical data from 2005 to 2025. The methodology employed includes systematic data pre-processing, such as normalization and the creation of sequential input, as well as the implementation of a two-layer LSTM architecture. Model performance was evaluated through two approaches, namely experimental testing on test datasets and practical validation in short-term prediction scenarios. Experimental results demonstrate very high accuracy, with a Mean Absolute Percentage Error (MAPE) value of 0.69% on the test data. This performance consistency is reinforced by the practical validation, which yielded an overall MAPE of 0.34%, proving the model's capability in predicting previously unseen data. Thus, the hypothesis that the LSTM model can achieve significant prediction accuracy (MAPE<10%) is accepted. Overall, the developed LSTM model is proven to be highly effective and valid, making it a suitable tool to support investment decisions in the stock market.
Co-Authors Albert Riyandi Budi Supriyadi Dicky Purwanto Reni Widyastuti Rian Septian Anwar