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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) Madaniya
Nur Jamiludin Ramadhan
Politeknik Manufaktur Bandung
Religion Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences

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Rancang Bangun Alat Pemisah Padi Portabel Untuk Masyarakat Desa Cibuluh Kabupaten Subang Jawa Barat Anggraeni Mulyadewi; Nur Wisma Nugraha; Aris Budiyarto; Nur Jamiludin Ramadhan; Hilda Khoirunnisa
Madaniya Vol. 4 No. 4 (2023)
Publisher : Pusat Studi Bahasa dan Publikasi Ilmiah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53696/27214834.685

Abstract

Salah satu tahapan dalam proses panen padi adalah pemisahan padi dari batangnya. Secara umum petani Desa Cibuluh, Kabupaten Subang masih melakukan kegiatan tersebut secara manual. Alat pemisah padi yang ada tidak efisien digunakan karena berat dan sulit untuk dibawa ke lokasi panen. Perancangan dan pembuatan alat pemisah padi portabel dengan memodifikasi alat pemisah padi yang sudah ada dilakukan dengan membuat alat pemisah padi menjadi dua bagian yaitu badan utama dan mesin penggerak. Kedua bagian tersebut dilengkapi tali gendongan yang membuat alat pemisah padi mudah untuk digunakan secara langsung oleh petani. Hasil uji menunjukkan bahwa alat ini mampu meningkatkan produktivitas petani dengan meningkatkan hasil panen dengan waktu yang singkat. Sebanyak kurang lebih 1000 kg biji padi dihasilkan selama dua jam waktu pemisahan padi dengan menggunakan alat pemisah padi portabel ini.
Pengembangan Konsep Landasan Robot Beroda Omnidirection Pemindah Barang Berbahan Extrusi Profil Aluminium Ade Ramdan; Reka Ardi Prayoga; Nur Jamiludin Ramadhan; Irham Subekti; Rifania Anjani
JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) Vol 6 No 2 (2024): Volume: 6 | Nomor: 2 | Oktober 2024
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat (P3M) Politeknik Manufaktur Bandung (Polman Bandung)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.48182/jtrm.v6i2.170

Abstract

This research examines how concept development was carried out to design an omnidirectional wheeled robot base made from extruded aluminum profiles used for moving goods. Concept design goes through a series of stages, that is: identifying problems, determining the function structure, looking for alternative solutions, building concept variations, assessing concept variations and determining the selected concept. After going through all these stages, it was concluded that an omnidirectional robot base can be divided into 2 sub-functions, namely: base frame and electrical energy converter. These two sub-functions have 6 parameters that can be varied, such as: various frame shapes, type of frame material, type of frame bar shape, type of frame connection, type of wheel, type of motor. Alternative solutions can be sought for each parameter, combined and assessed to obtain a variation of the selected concept that meets the list of requirements.
Predictive Analytics for Energy Consumption of Autonomous Mobile Robot Using Hybrid ARIMA-XGBoost Pipit Anggraeni; Wahyu Adhie Candra; Surya Dharma Jatnika; Noval Lilansa; Adhitya Sumardi Sunarya; Nur Jamiludin Ramadhan; Andri Wiyono
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 3 (2026): Article Research July 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i3.16484

Abstract

The deployment of autonomous mobile robots in smart manufacturing and intralogistics has grown rapidly, yet current battery management systems can only monitor real-time charge levels without predicting future energy consumption. This reactive limitation risks mid-mission battery depletion and production disruption. The study presents a predictive analytics system for the Polebot autonomous mobile robot integrated with a Robot Operating System 2 data historian pipeline and an InfluxDB time-series database. The objective is to evaluate whether an autoregressive time-series model or a gradient-boosted machine learning model better suits different operational conditions, specifically constant-velocity static operation versus acceleration-heavy dynamic operation. Data were collected from three sensor sources across six operational protocols covering baseline, high-load, stop-and-go, creep, burst acceleration, and mixed conditions, yielding 10,800 synchronized data points at 1 Hz after resampling. Results show that the Autoregressive Integrated Moving Average model with parameters (2,1,3) achieves a Mean Absolute Error of 1.047% and a symmetric Mean Absolute Percentage Error of 1.74% for battery State of Charge prediction under static conditions. Extreme Gradient Boosting achieves a Mean Absolute Error of 0.022 watts for motor power prediction, 136 times more accurate than the time-series model for the same variable. The proposed Condition-Based Temporal Switching framework was validated on 1,803 data points and autonomously produced 265 model transitions during a 30-minute mixed operational test, with static conditions comprising 83.9% of the validation window. Adaptive model selection outperforms single-model strategies for energy prediction in autonomous mobile robot platforms.
Co-Authors Ade Ramdan Adhitya Sumardi Sunarya Andri Wiyono Anggraeni Mulyadewi Aris Budiyarto Irham Subekti Khoirunnisa, Hilda Nur Wisma Nugraha Pipit Novita Anggraeni Reka Ardi Prayoga Rifania Anjani Surya Dharma Jatnika Wahyu Adhie Candra