Article Per Year (5 Year)
p-Index From 2020 - 2025
1.006
P-Index
This Author published in this journals
All Journal Electron: Jurnal Ilmiah Teknik Elektro Jurnal Ecocentrism EJOIN : Jurnal Pengabdian Masyarakat Akademika
Rabiula, Andre
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
PENERAPAN SISTEM KONTROL DAN MONITORING LEVEL AIR BERBASIS INTERNET Of THINGS (IoT) DENGAN TELEGRAM DI HANZA FARM SEBAGAI STRATEGI PENGUATAN PRODUKTIVITAS PERTANIAN HIDROPONIK Hais, Yosi Riduas; Nehru, Nehru; Fuady, Samratul; Rabiula, Andre; Fortuna, Dewi; Damayanti, Liza
EJOIN : Jurnal Pengabdian Masyarakat Vol. 2 No. 5 (2024): EJOIN : Jurnal Pengabdian Masyarakat, Mei 2024
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/ejoin.v2i5.2857

Abstract

Hidroponik merupakan budidaya pertanian yang tidak menggunakan tanah sebagai medianya. Kelebihan dalam bercocok tanam menggunakan media non tanah adalah salah satu cara penghematan lahan dan juga tidak memakan banyak biaya. Untuk kelemahan nya sendiri adalah perlu nya ketelitian tinggi. Hidroponik Hanza Farm menggunakan jenis hidroponik dengan metode Nutrifit Film Technique (NFT) di lahan terbuka. Hidroponik di lahan terbuka menimbul permasalahan yang lebih kompleks dari pada jenis hidroponik pada green house, namun dari sisi investasi lebih menguntungkan. Belum ada penerapan teknologi, baik konvensional maupun otomastis pada hidroponik mitra. Semuanya masih dikontrol secara konvensional oleh manusia. Pengendalian level air pada tandon dan sirkulasi air hidroponik masih menggunakan tenaga manusia, yang terkadang terjadi human error. Terbuangnya nutrisi pada saat kondisi hujan, karena air tandon yang sudah di isi dengan nutrisi menjadi tumpah karena tambahan air hujan.  Tumbuhan hidroponik menjadi layu dan kering akibat sirkulasi air yang tidak terkontrol. Untuk mengatasi masalah tersebut, maka diterapkan teknologi sistem otomatis. Pada pengabdian ini difokuskan pada masalah kontrol level air pada tandon nutrisi hidroponik. Sistem kontrol dan monitoring level air dibangun berbasis Internet of Things (IoT) menggunakan aplikasi telegram. Perangkat yang digunakan untuk mengukur level air berupa sensor level swicth. Data yang dibaca sensor kemudian dikirimkan ke NodeMCU ESP8266. NodeMCU akan mengolah data dan mengontrol on/off dari pompa, kemudian data juga dikirim ke telegram user menggunakan internet. Sehingga user dapat memonitoring dan mengontrol level air dari jarak jauh. Berdasarkan hasil pengujian yang telah dilakukan terhadap alat pendeteksi  banjir ini dapat ditarik kesimpulan bahwa, perangkat dapat mengukur ketinggian sebagaimana fungsinya, sensor jarak mampu mengukur ketinggian air dengan tingkat error -3 cm diatas jarak 150 cm dan rata-rata delay pengiriman data dari telegram ke Hidroponik adalah 3 detik. Dengan penerapan alat ini petani lebih mudah untuk memonitoring kondisi cuaca dan level air dari jarak jauh. Selain memonitoring alat ini juga dapat dikendalikan untuk mengaktifkan dan mengnonaktifkan pompa air.
IMPEMENTASI ALGORITMA YOLO UNTUK PENGENALAN OBJEK SAMPAH: Classification, Deep Learning, Image Processing, YOLO Rabiula, Andre; Haryatama Putri, Frenti; Nehru, Nehru
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1677

Abstract

Human activities cannot be separated from production and consumption activities which have an impact on the generation of waste, such as the use of plastic. Therefore, waste detection and sorting should be carried out at the initial stage of waste management to maximize the amount of waste that can be recycled. This research aims to apply image processing and deep learning algorithms in plastic waste classification, as well as testing the performance of the classification system. The research method used refers to the research stages, namely literature study, data collection, pre-processing, system design, implementation, testing, evaluation and data analysis. The research results show that plastic waste classification system obtained accuracy, precision, recall and F1 scores, namely 98.7%, 1, 0.98 and 0.99.
INTEGRASI PROJECT-BASED LEARNING DALAM PEMBELAJARAN INTERAKSI MANUSIA DAN KOMPUTER DI PROGRAM STUDI SISTEM INFORMASI: Human-Computer Interaction, learning outcomes, Project-Based Learning, student creativity, UI/UX. Abidin, Zainil; Hutabarat, Benedika Ferdian; Rabiula, Andre
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1688

Abstract

This study aims to analyze the effect of implementing the Project-Based Learning (PjBL) model on student learning outcomes and task creativity in the Human-Computer Interaction course. The research method used is quantitative with a quasi-experimental design. The research subjects consisted of two classes: a control class using conventional methods and an experimental class applying PjBL. Data were collected through final exam tests and a rubric-based assessment of UI/UX project creativity. The analysis results showed that the PjBL class achieved significantly higher scores in both final exams and task creativity (p < 0.05). It is concluded that the PjBL model is effective in enhancing students' understanding and UI/UX design skills in the Information Systems program.
ANALISIS PERBANDINGAN MODEL GRU DAN LSTM UNTUK PREDIKSI HARGA SAHAM BANK RAKYAT INDONESIA: Deep Learning, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), Stock Price Prediction Perdana, Yogi; Raisa Hanum, Nindy; Rabiula, Andre; Anzari, Yandi
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1692

Abstract

This research implements and compares two deep learning architectures, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), for predicting the stock price of Bank Rakyat Indonesia (BRI) using historical data from February 2023 to October 2024. Through systematic hyperparameter tuning and comprehensive evaluation, the study finds that GRU consistently outperforms LSTM across all regression metrics, with a 10.7% improvement in R² and an 18.5% reduction in MAPE. The optimal GRU configuration (100 units, 100 epochs, batch size 32, learning rate 0.001) achieves an MSE of 6517.5 and MAPE of 1.3764%. Visual analysis confirms GRU's superior ability to capture stock price fluctuations and adapt more quickly to trend changes. The simpler architecture of GRU with fewer parameters proves more effective for handling the high-noise characteristics and varying volatility of stock price data. While both models face challenges in predicting extreme market events, GRU demonstrates better resilience and faster recovery after such occurrences. This research contributes to the understanding of recurrent neural network applications in financial time series forecasting and provides practical insights for developing more accurate stock price prediction systems.
POTENSI PEMANFAATAN LIMBAH PADAT KELAPA SAWIT SEBAGAI UPAYA MENINGKATKAN EFISIENSI ENERGI DI PABRIK KELAPA SAWIT Gusri, Lailal; Putri, Prameswari Amalia; Manab, Abdul; Rabiula, Andre
Jurnal Ecocentrism Vol. 5 No. 2 (2025): Jurnal Ecocentrism
Publisher : Program Studi Teknik Lingkungan, Fakultas Teknik, Universitas Mahasaraswati Denpasar, Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36733/jeco.v5i2.12914

Abstract

The palm oil industry has a significant impact on the regional and national economy, generating employment, especially for farmers. Crude palm oil (CPO) can be processed into edible oil, cosmetics, and biofuels, making it a strategic commodity in global trade. However, this industry also produces abundant solid and liquid waste, such as shells, fibers, and empty fruit bunches. Factory waste must be managed and processed to prevent environmental pollution. Poor waste management can lead to various environmental problems, necessitating effective and sustainable management strategies. This type of solid waste has the potential to be used as an alternative energy source and raw material for value-added products. The objective was to determine the utilization of palm oil solid waste and its percentage, as an effort to optimize industrial waste management. The methods used included direct observation of the processing and utilization of solid waste at the factory, collection of production data, and a review of relevant literature. The results showed that empty fruit bunches are used as compost and mulch in plantations, shells are used as boiler fuel to generate steam energy, and fiber is used as supplementary fuel. According to the literature review, this solid waste still has potential for further development, such as the production of briquettes, pellets, and biomass-based activated carbon. Optimizing the utilization of palm oil solid waste can increase the energy efficiency of factories and reduce the volume of waste.
Analisis Kontingensi Saluran Transmisi 150 kV pada Subsistem Jambi Nazwan, Ahmad Rifki; Tessal, Dasrinal; Rabiula, Andre
ELECTRON Jurnal Ilmiah Teknik Elektro Vol 6 No 2: Jurnal Electron, November 2025
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/electron.v6i2.285

Abstract

High-voltage electrical systems are essential for maintaining a stable and efficient electricity supply. However, increasing capacity and expanding networks increase the risk of disruptions that can trigger blackouts. System reliability relies heavily on its ability to survive sudden disturbances, such as loss of generation or transmission line breaks. Contingency analysis (N-1) is used to predict system conditions and design appropriate mitigations to improve reliability. This study analyzes contingency in the Jambi 150 kV subsystem using the Newton-Raphson method in ETAP 19.0.1 software, with a Performance Index (PI) approach. The results show the Muara Bulian - Aurduri line has the highest PI (4.3382), while Aurduri - Muara Sabak has the lowest (1.4754). Contingency on the Aurduri - Muara Bulian line causes low voltage at the Sarolangun and Muara Bulian buses, 130.376 kV and 131.193 kV respectively. In addition, there is a redistribution of power flow that increases the load by 20.42% on the Muara Tebo - Aurduri line. As a mitigation measure, the installation of shunt capacitors of 5.807 MVar at Sarolangun bus and 23.074 MVar at Muara Bulian is recommended
Co-Authors Abdul Manab Abidin, Zainil Benedika Ferdian Hutabarat Damayanti, Liza Dasrinal Tessal Dewi Fortuna Fuady, Samratul Gusri, Lailal Haryatama Putri, Frenti Nazwan, Ahmad Rifki Nehru Nehru Perdana, Yogi Putri, Prameswari Amalia Raisa Hanum, Nindy Yandi Anzari Yosi Riduas Hais