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All Journal Jurnal Teknik Mesin Rekayasa Mesin Prosiding Semnastek JURNAL INTEGRASI Jurnal Rekayasa Material, Manufaktur & Energi Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Journal of Dynamics Logista: Jurnal Ilmiah Pengabdian Kepada Masyarakat Jurnal TEMAPELA JTM - Jurnal Teknik Mesin Jurnal Teknik Mesin Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Engine: Energi, Manufaktur, dan Material Jurnal Vokasi Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Surya Teknika Jurnal Pengabdian dan Peningkatan Mutu Masyarakat (JANAYU) International Journal of Research in Community Services Teknika Sains : Jurnal Ilmu Teknik Journal of Energy, Material, and Instrumentation Technology Jurnal Teknik Mesin International Journal of Multidisciplinary Research and Literature (IJOMRAL) METAL : Jurnal Sistem Mekanik dan Termal Dulang: Jurnal Pengabdian Kepada Masyarakat Industrial Research Workshop and National Seminar Jurnal Andalas: Rekayasa dan Penerapan Teknologi International Journal of Innovation in Mechanical Engineering and Advanced Materials Proceeding Applied Business and Engineering Conference Jurnal Polimesin IJIMCE : International Journal of Innovation in Mechanical Construction and Energy IJIS Edu : Indonesian Journal of Integrated Science Education JAPEPAM, Jurnal Pengabdian kepada Masyarakat
Ruzita Sumiati
Politeknik Negeri Padang
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Journal : Jurnal Teknik Mesin

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Modeling Mechanical Component Classification Using Support Vector Machine with A Radial Basis Function Kernel Ruzita sumiati; Moh. Chamim; Desmarita Leni; Yazmendra Rosa; Hanif Hanif
Jurnal Teknik Mesin Vol 16 No 2 (2023): Jurnal Teknik Mesin
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/jtm.16.2.1250

Abstract

The process of identification and classification of products in the era of modern manufacturing industries has become a crucial pillar in enhancing efficiency, productivity, and product quality. In this research, the modeling of manufacturing product classification, such as mechanical components consisting of four classes: bolts, washer, nuts, and locating pin, was conducted. The proposed model in this study is the Support Vector Machine (SVM) with Radial Basis Function (RBF). The dataset used consists of digital images of mechanical components, with each component having 400 samples, resulting in a total of 1600 samples. The dataset is divided into training and testing data, with 300 samples for each component in the training set, and 100 samples removed from the training set for external testing as model validation. The best model parameters were determined using grid search by varying the parameter values of C and γ (gamma). The model was evaluated using K=3 fold cross-validation, and external testing utilized a confusion matrix to calculate Accuracy, Precision, Recall, and F1-Score values. The research results indicate that the SVM model with the RBF kernel, using the combination of C=10 and γ=scale, achieves the best performance in classifying the four mechanical components. This is evident from the training results of the model, which were able to obtain evaluation metrics such as Accuracy of 94.17%, Precision of 0.94, Recall of 0.94, and F1-Score of 0.94. Meanwhile, the validation results with new data not present in the training dataset show that the model can achieve evaluation metrics with an Accuracy of 93%, Precision of 0.93, Recall of 0.93, and F1-Score of 0.93. These results are consistent with the training performance, indicating that the SVM model with the RBF kernel excels in classifying digital images of mechanical components, such as bolts, nuts, washer, and locating pin.
Rancang Bangun Alat Ukur Torsi dan Putaran Untuk Pengujian Turbin Savonius Pada Wind Tunnel Berbasis mikrokontroler Ruzita sumiati; Uyung Gatot S. Dinata; Dendi Adi Saputra; Riswan Riswan; Fahri Triharyono; Rahil Abde Andika; Fharel Abdillah
Jurnal Teknik Mesin Vol 17 No 1 (2024): Jurnal Teknik Mesin
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/jtm.17.1.1414

Abstract

The objective of this research is to design and develop a torque measurement device using a braking system and a rotational speed measurement tool for a Savonius turbine shaft, applied in a wind tunnel, with data acquisition controlled by an Arduino Uno microcontroller. The methodology employed in this research is the design and build method. The testing results indicate that the torque measurement device controlled by the Arduino Uno functions effectively. Comparing the results of braking force measurements using manual methods and data acquisition revealed a 2, 231 % error. Additionally, the rotational speed measurements using a tachometer and those using an encoder controlled by the Arduino Uno showed a small error of 0,59 %. Data were continuously monitored on a laptop screen during testing. Thus, this device can be utilized as an auxiliary measurement tool to assess the performance of a Savonius turbine
Analisis Gaya Drag Pada Mobil Sedan dengan Penambahan Komponen Drag Reduction Aziz, Abdul; Nofriadi, Nofriadi; Rudianto, Rudianto; Alfi, Rizki; Naro, Aulia; Sumiati, Ruzita
Jurnal Teknik Mesin Vol 18 No 1 (2025): Jurnal Teknik Mesin
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/jtm.18.1.1838

Abstract

The aerodynamic design of a vehicle body plays a critical role in reducing air resistance (drag), thereby contributing to improved fuel efficiency. Aerodynamic resistance in vehicles is influenced by several parameters, including body geometry, auxiliary elements, and the orientation of the vehicle relative to the airflow. This study aims to analyze the effects of body shape variations and the addition of a spoiler on drag force reduction in a sedan-type vehicle. The methodology employed in this research is numerical simulation using Ansys Fluent software. Simulation results indicate that the model with a more streamlined geometry (Model C) produces a lower drag force compared to the model equipped with a spoiler. The drag coefficients obtained for each configuration are as follows: Sedan A — 0.780, Sedan B with a spoiler — 0.775, and Sedan C with an improved body geometry — 0.647. These findings suggest that optimizing body shape is more effective in enhancing the aerodynamic performance of a vehicle than the addition of external aerodynamic elements such as a spoiler.
Co-Authors ., Adriansyah ., Islahuddin ., Maimuzar ., Muchlisinalahuddin Abdul Aziz Abdullah, Irinah binti Ade Usra Berli Adriansyah Adriansyah Adriansyah Afifah Afifah, Afifah Afriyani, Sicilia Aggrivina Dwiharzandis Aidil Zamri Aidil Zamri Alfi, Rizki Andrew Kurniawan Vadreas Angelia, Nike Anissa Vivia Fidela Arifian, Naf'an Arwizet Arwizet, Arwizet Asmed Asmed Budiman, Dadi Bukhari Camim, Moh. Candra Mayana, Hendri Dandi Ilham Delffika Canra Desmarita Leni Doni Marzuki Efiandi, Nota Elvando andha elvaris manalu Fahri Reza Fahri Triharyono Fajar Pradana Fajri Arsyah, Ahmad Hasnul Fanni Sukma Fardinal Fardinal Fardinal, Fardinal Fathir Alqodri Fharel Abdillah Fharel Abdillah Fitri Adona Gani Pratama Genta Ramadeto Ghandy Junne Putra Gusriwandi Gusriwandi Hamdani, Rifki Hamdani, Rifqi Hamzah Putra Hanif Hanif Hanif Hanif Haris ., Haris Haris Haris Haris Haris, Haris Helga Yermadona Hendra . Ikbal Ilham, M. Irwan Irwan Jana Hafiza Kesuma, Dytchia Septi Khairul Amri Khairul Amri Khan, Sharif kusuma, Yuda Perdana Lega Putri Utami Lim, Hooi Peng M. Luthfi Artia Maimuzar Maimuzar Meiki Eru Putra Menhendry Moh. Chamim Muchlisinalahuddin Mulyadi Mulyadi . Mulyadi Mulyadi Nandi Pinto NARO, AULIA Nasirwan Nasirwan Nasrullah Nasrullah Nofriadi Nofriadi Nofriyandi, R Nofriyanti, Elsa Nota Effiandi Nusyirwan Nusyirwan Nusyirwan Peng, Lim Hooi Rahil Abde Andika Rahmi, Nurfitri Rajimar Suhal Hasibuan Hasibuan Rakiman Rakiman Rakiman Rakiman Rama, Hilfama Ridho Pratama Fajri Riezky Idvi Alfitra Rina Rina Rina Rina Rina, Rina Rino Sukma Riswan Riswan Rivanol Chadry Robby Novrizal Rudianto Rudianto Saputra M, Dendi Adi Seno, Abdi Sir Anderson Siska Angraini Rikosa Rikosa Suliono Suliono Tri Ego Wiranata Usra Berli , Ade Uyung Gatot Syafrawi Dinata Veny Selviyanty Verdian, Riza Yanziwar Yanziwar Yazmendra Rosa Yogi Kogama Yuda Perdana Kusuma Yuhefizar Yuhefizar Yuli Yetri Yuliarman Yuliarman Yuliarman Yuliarman Yusri Mura