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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi JTRM (Jurnal Teknologi dan Rekayasa Manufaktur) MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Madaniya
Nur Jamiludin Ramadhan
Politeknik Manufaktur Bandung
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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.
Sliding Mode Control for Trajectory Tracking on Non-Holonomic Autonomous Mobile Robot (AMR Muhammad Daffa Karim; Wahyu Adhie Candra; Pipit Anggraeni; Noval Lilansa; Adhitya Sumardi Sunarya; Nur Jamiludin Ramadhan; Andri Wiyono
MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Vol 8 No 2 (2026): Motivection : Journal of Mechanical, Electrical and Industrial Engineering
Publisher : Indonesian Mechanical Electrical and Industrial Research Society (IMEIRS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Trajectory tracking of non-holonomic autonomous mobile robots (AMRs) becomes more demanding when a passive trailer is towed and wheel slip occurs. This study developed a two-surface sliding mode control (SMC) scheme that regulates the distance and heading errors of a pure-pursuit lookahead point and maps the desired accelerations to wheel torques through dynamic inversion, with boundary-layer saturation, heading-singularity safeguards, and jackknife protection. The controller was evaluated in ROS 2 Jazzy and Gazebo Harmonic and integrated with a breadth-first search (BFS) planner using mode-adaptive obstacle inflation. On an oval path with a rigid hitch, the tracking root-mean-square error (RMSE) was 0.042 m, whereas a replicated three-surface baseline diverged (RMSE 4.68 m) with 79.5% torque saturation; the proposed controller required approximately five times less control effort without saturation. A LuGre-based slip test showed that wheel-odometry feedback diverged substantially from ground truth, supporting map-based localization. Hardware validation remains necessary.
Implementasi Algoritma Cuckoo Search untuk Optimasi Lintasan dan Penghindaran Rintangan Robot PoleBot Adhitya Sumardi Sunarya; Wahyu Adhie Candra; Rifqiaqil Mufahir Erwansyah; Pipit Anggraeni; Noval Lilansa; Nur Jamiludin Ramadhan
Jurnal Mekanova : Mekanikal, Inovasi dan Teknologi Vol 12, No 2 (2026): Oktober
Publisher : universitas teuku umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/jmkn.v12i2.15982

Abstract

This study implements the Cuckoo Search Algorithm (CSA) for path optimization and obstacle avoidance on the differential-drive PoleBot AMR running ROS2 Jazzy. CSA is applied at two levels: a global CSA that optimizes waypoints for three candidate paths, and a local CSA that selects linear and angular velocity pairs over a 1.15 s prediction horizon as the obstacle-avoidance layer. Both run as a single ROS2 node integrated with the Tongyi servo motor driver (CANopen), the Autonics LSC 270° 2D LiDAR, and AMCL localization. The global CSA planner was compared with the Genetic Algorithm (GA) and RE-RRT on an identical navigator with the CSA local layer fixed, in 30 2D-simulation runs (10 per configuration). All configurations reached the goal without collision. GA was the most efficient (17.4 m; 177 s) with the smallest minimum clearance (0.59 m); RE-RRT produced the longest and most variable paths (19.4 ± 1.8 m) with the largest minimum clearance (1.69 m); CSA lay in between (17.6 m; 181 s; 0.67 m). On the physical robot with static obstacles, 10 of 10 runs succeeded without collision (242 ± 32 s; path efficiency 0.84). The physical implementation exposed six integration problems, including stale TF poses and the motor braking limit, together with their fixes.Keywords— Autonomous Mobile Robot, Cuckoo Search Algorithm, Obstacle Avoidance, PoleBot, ROS2
Co-Authors Ade Ramdan Adhitya Sumardi Sunarya Andri Wiyono Anggraeni Mulyadewi Aris Budiyarto Irham Subekti Khoirunnisa, Hilda Muhammad Daffa Karim Nur Wisma Nugraha Pipit Novita Anggraeni Reka Ardi Prayoga Rifania Anjani Rifqiaqil Mufahir Erwansyah Surya Dharma Jatnika Wahyu Adhie Candra