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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) 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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DESIGN OF FISHERMAN BOAT PULLING MACHINE FOR IMPROVING WORK EFFICIENCY AND WELFARE OF TRADITIONAL FISHERMEN AT PASIE KATAPIANG BEACH, PADANG PARIAMAN Effiandi, Nota; Irwan, Irwan; Seno, Abdi; Arifian, Naf'an; Haris, Haris; Nusyirwan, Nusyirwan; Hamdani, Rifqi; Sumiati, Ruzita
International Journal of Multidisciplinary Research and Literature Vol. 3 No. 2 (2024): INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH AND LITERATURE
Publisher : Yayasan Education and Social Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53067/ijomral.v3i2.204

Abstract

This study aims to design an efficient boat-pulling machine to support traditional fishermen at Pasie Katapiang Beach, Padang Pariaman. The research method employed is the design of the tool based on the principles of design engineering, involving a systematic process in creating a machine that can assist fishermen in the boat docking process more efficiently. Through calculations and planning, it was found that the force required to pull the fishermen's boat is 6,522.88 N, using a shaft made of ST 37 material with a diameter of 22.413 mm. The rotations generated on the transmission shaft are 2000 rpm, while on the wheel and drum shafts are 750 rpm and 500 rpm, respectively. The selection of a slip clutch with 2 bolts on the transmission shaft and the use of pillow block bearing ucp 206 ass 30 with specified bearing life estimates have been considered in the machine design. Practical test results indicate that the time required to reel or pull the boat is 0.98 minutes. In this research, the design of the boat-pulling machine meets operational needs. It has the potential to positively contribute to improving the work efficiency and welfare of traditional fishermen in the field
PELATIHAN PERAWATAN, CARA PENGOPERASIAN DAN UJI COBA ALAT BANTU PENARIK PERAHU NELAYAN UNTUK KELOMPOK NELAYAN MUTIARA LAUT NAGARI KATAPIANG PADANG PARIAMAN Efiandi, Nota; Haris, Haris; Nusyirwan, Nusyirwan; Hamdani, Rifki; Seno, Abdi; Ilham, M.; Sumiati, Ruzita
LOGISTA - Jurnal Ilmiah Pengabdian kepada Masyarakat Vol 8 No 1 (2024)
Publisher : Department of Agricultural Product Technology, Faculty of Agricultural Technology, Universitas Andalas Kampus Limau Manis - Padang, Sumatera Barat Indonesia-25163

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/logista.8.1.36-40.2024

Abstract

Menangkap ikan adalah mata pencarian yang ditekuni setiap hari oleh masyarakat pesisir pantai Katapiang Padang Pariaman Sumbar. Biasanya, nelayan menangkap ikan di tengah laut dan hasil tangkapan dibawa dengan perahu kedarat. Setelah perahu sampai dibibir pantai kemudian perahu yang berisi hasil tangkapan ikan di tarik ke darat bersama sama oleh kelompok nelayan secara manual menggunakan tenaga manusia. Proses tersebut menurut nelayan tidak efektif dan meminimalkan hasil tangkapan karena harus dibagi ke anggota penarik. Adapun tersedia alat penarik sederhana tetapi tidak layak pakai karena tidak terawat dengan baik. Tujuan pengabdian pada masyarakat ini adalah mengedukasi masyarakat tentang alat bantu penarik perahu melalui pelatihan singkat tentang alat penarik perahu, cara operasi dan perawatannya supaya alat dapat berfungsi dengan baik dan memiliki umur pakai yang lama. Metoda yang digunakan adalah metoda pelatihan langsung ke kelompok Nelayan mitra. Hasil yang didapat setelah pelatihan ini anggota kelompok nelayan mampu mengoperasikan alat penarik kapal dan mampu melakukan perawatan harian pada alat penarik perahu. Kata kunci: penarik perahu nelayan, alat bantu tarik, pelatihan pengoperasian mesin, nelayan, tangkapan ikan ABSTRACT Fishing is the daily livelihood of the coastal community in Katapiang, Padang Pariaman, West Sumatra. Typically, fishermen catch fish in the open sea and bring their catch to shore by boat. Once the boat reaches the beach, the fishermen manually pull the boat, filled with their catch, to shore together as a group. This manual process is considered inefficient by the fishermen, as it reduces their catch since it has to be divided among the pullers. Although there is a simple pulling device available, it is not in usable condition due to poor maintenance. The aim of this community service is to educate the community about the boat pulling device through a brief training session on its operation and maintenance, ensuring the device functions properly and has a longer lifespan. The method used is direct training for the partner fishermen group. The outcome of this training is that members of the fishermen group are able to operate the boat pulling device and perform daily maintenance on it. Keywords: fisherman boat pulling device, assistive pulling equipment, machine operation training, fishermen, fish catch
Predictive Modeling For Low Alloy Steel Mechanical Properties: A Comparison Of Machine Learning Algorithms And Parameter Optimization Leni, Desmarita; Putri Utami, Lega; Sumiati, Ruzita; Camim, Moh.; Khan, Sharif
IJIMCE : International Journal of Innovation in Mechanical Construction and Energy Vol. 1 No. 1 (2024): IJIMCE : International Journal of Innovation in Mechanical Construction and Ene
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ijimce.v1i1.7

Abstract

The development of machine learning in predicting the mechanical properties of alloy steel has become an important research subject in recent years. This is due to the ability of machine learning to extract complex patterns from large and intricate data, which can be used to understand the relationship between chemical composition, microstructure, and mechanical properties of alloy steel. This research aims to design a machine learning model to predict the mechanical properties of low alloy steel, such as Yield Strength (YS) and Ultimate Tensile Strength (UTS), based on the percentage composition of chemical elements in low alloy steel and the heat treatment applied. The machine learning model in this study consists of 10 input variables and 2 target variables. The research compares the performance of 3 machine learning algorithms, namely Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). The research findings indicate that the ANN algorithm model performs best in predicting the mechanical properties of low alloy steel. This model has Mean Absolute Error (MAE) values of 16.5 and 19.593 for predicting YS and UTS, Root Mean Square Error (RMSE) values of 19.111 and 22.005, and coefficient of determination (R) values of 0.964 and 0.947 for YS and UTS respectively. The modeling uses the ANN algorithm with an 80% training data and 20% testing data split, and applies the K-Fold Cross Validation method with a value of K=5. The best parameters obtained are a learning rate of 0.001, momentum of 0.1, and a hidden layer neuron count of 9. These results indicate that ANN has great potential in addressing the complexity and variability in material data. The implications of these findings are that the implementation of ANN in manufacturing and material engineering industries can enhance the accuracy and efficiency in material strength prediction processes, which, in turn, can aid in designing and developing better and more durable products.
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.
PEMBUATAN ALAT TRAINER STARTING SYSTEM UNTUK MEDIA PRATIKUM JURUSAN KENDARAAN RINGAN SMK DHUAFA PADANG Chadry, Rivanol; Leni, Desmarita; Nofriadi, Nofriadi; Sumiati, Ruzita; Budiman, Dadi; Mulyadi, Mulyadi
Jurnal Vokasi Vol 7, No 3 (2023): November
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/vokasi.v7i3.4186

Abstract

Tim PKM PNP jurusan Teknik Mesin telah berhasil memberikan kontribusi yang dalam upaya meningkatkan kualitas media praktikum di SMK Dhuafa Padang, khususnya dalam bidang jurusan kendaraan ringan. Dengan pembuatan Alat Trainer Starting System yang efektif dan efisien, tercipta sebuah media praktikum yang memadai bagi para siswa-siswi. Alat praktikum ini memungkinkan siswa-siswi untuk secara efektif mengaplikasikan teori yang telah dipelajari dan mengembangkan keterampilan yang esensial dalam industri kendaraan bermotor. Untuk melihat kepuasan dari mitra tim pengabdian memberikanangket kepada beberapa orang guru kendaraan ringan, dan hasil menunjukkan kepuasan mereka terhadap alat media pembelajaran yang diberikan. Mengingat pentingnya Starting System dalam mesin kendaraan, pendekatan kurikulum SMK Dhuafa Padang yang fokus pada praktikum menjadi semakin terwujud. Meskipun tantangan hadir dalam bentuk keterbatasan alat praktikum yang tersedia, kolaborasi ini berhasil mengatasi hambatan tersebut dan memberikan solusi berkelanjutan. Sejalan dengan kemajuan teknologi pada kendaraan bermotor, inovasi di dalam pembelajaran menjadi semakin dibutuhkan, dan SMK Dhuafa Padang menjadi pilar penting dalam mempersiapkan siswa-siswi untuk menghadapi perubahan tersebut. Oleh karena itu, melalui pengabdian masyarakat ini, dampak positif telah diberikan kepada pendidikan siswa-siswi di jurusan kendaraan ringan SMK Dhuafa Padang.
Rancang Bangun Pompa Hidram Untuk Menaikan Air Dari Sumber Mata Air Ke Perkebunan Penduduk Nusyirwan; Gani Pratama; Ruzita Sumiati; Yetri, Yuli
JURNAL INTEGRASI Vol. 17 No. 1 (2025): Jurnal Integrasi - April 2025
Publisher : Pusat Penelitian dan Pengabdian Masyarakat Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/ji.v17i1.7815

Abstract

The hydram pump has been designed and manufactured to help people who lack water on plantation land. Hydraulic pumps are an appropriate technology in the field of pumping that use water momentum (water hammer) to raise the pumped water. The design and manufacture of hydram pumps aims to raise water from springs to residents' plantations. The specifications for making a hydram pump are 2 inches for the pump body, 3 inches for the pump air tube, with 3 valves (2 exhaust valves and 1 delivery valve). The results of test 1 at an output height (h) of 1m produced a pump output discharge of 3.12x10-4m3/s, a discharge at the exhaust valve of 7.52x10-4m3/s, and an efficiency of 19.59%. Test 2 at an output height (h) of 2.5m produced a pump output discharge of 2.08x10-4m3/s, a discharge at the exhaust valve of 7.27x10-4m3/s, and an efficiency of 36.96%. Then test 3 at an output height (h) of 5m produced a pump output discharge of 1.08x10-4m3/s, a discharge at the exhaust valve of 7.16x10-4m3/s, and an efficiency of 43.66%. The test results show that the higher the h output, the smaller the water discharge coming out of the hydram pump, and the greater the efficiency of the hydram pump.
Modifikasi Mesin Pengupas Serabut Kelapa Bukhari; Leni, Desmarita; Ikbal; Fardinal; Sumiati, Ruzita
JURNAL SURYA TEKNIKA Vol. 9 No. 2 (2022): JURNAL SURYA TEKNIKA
Publisher : Fakultas Teknik UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jst.v9i2.4376

Abstract

Rancangan modifikasi mesin pengupas serabut kelapa ini dibuat untuk membantu proses pemisah serabut kelapa dari batok kelapa. Untuk mengupas serabut kelapa masih menggunakan proses manual dengan pisau yang membutuhkan tenaga serta banyak waktu kurang dari 1 jam untuk mengupas 10 buah kelapa. Rancang mesin pengupas serabut kelapa bertujuan untuk meningkatkan produktivitas pengupasan serabut kelapa. Pada penguspasan 10 buah kelapa pengupasan waktu rata rata yang digunakan untuk mengupas satu buah kelapa berkisar 5-9 detik, sehingga menghemat waktu dan tenaga manusia. Pengupasan dilakukan menggunakan mesin dimana sistem pengoperasiannya menggunakan poros dan dibantu dengan pengerak motor. Motor bensin 6 hp yang menggerakan beberapa transmisi ,di antaranya menggerakan gearbox sampai menggerakan mata pisau,dalam pengujian alat pengupasan kelapa lebih tinggi kapasitasnya dibandingkan dengan pengupasan manual.
Pemodelan Machine Learning untuk Memprediksi Tensile Strength Aluminium Menggunakan Algoritma Artificial Neural Network (ANN) Leni, Desmarita; Yermadona, Helga; Usra Berli , Ade; Sumiati, Ruzita; Haris, Haris
JURNAL SURYA TEKNIKA Vol. 10 No. 1 (2023): JURNAL SURYA TEKNIKA
Publisher : Fakultas Teknik UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jst.v10i1.4843

Abstract

This research designs a machine learning model using an Artificial Neural Network (ANN) algorithm to predict the tensile strength of aluminum. This research produces a machine learning model that has 8 (eight) input data variables consisting of the percentage of aluminum chemical composition such as Mg, Zn, Ti, Cu, Mn, Cr, Fe, Si, and 1 output (output), namely aluminum tensile strength. This study makes changes to several variations of parameters, such as variations in the number of split data, training cycles, learning rates, and hidden neurons. This Artificial Neural Network (ANN) modeling produces an RMSE value of 15,383 with the best parameters being split into 60 training and 40 testing data, training cycle of 100, learning rate of 0.08, momentum 0.9, and hidden neuron 7.This research designs a machine learning model using an Artificial Neural Network (ANN) algorithm to predict the tensile strength of aluminum. This research produces a machine learning model that has 8 (eight) input data variables consisting of the percentage of aluminum chemical composition such as Mg, Zn, Ti, Cu, Mn, Cr, Fe, Si, and 1 output (output), namely aluminum tensile strength. This study makes changes to several variations of parameters, such as variations in the number of split data, training cycles, learning rates, and hidden neurons. This Artificial Neural Network (ANN) modeling produces an RMSE value of 15,383 with the best parameters being split into 60 training and 40 testing data, training cycle of 100, learning rate of 0.08, momentum 0.9, and hidden neuron 7.
PELATIHAN 3D PRINTING UNTUK JURUSAN KENDARAAN RINGAN SMK DHUAFA PADANG Sumiati, Ruzita; Nofriadi, Nofriadi; Fajri Arsyah, Ahmad Hasnul; Nusyirwan, Nusyirwan; Adriansyah, Adriansyah; Leni, Desmarita; Nasirwan, Nasirwan
Jurnal Pengabdian Masyarakat Polmanbabel Vol. 5 No. 02 (2025): DULANG : Jurnal Pengabdian Kepada Masyarakat
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/dulang.v5i02.412

Abstract

3D Printing training has been implemented as part of efforts to develop technical competence in vocational education, especially for students of the Light Vehicle Department at SMK Dhuafa Padang. This study aims to assess the effectiveness of 3D Printing training in improving students' skills in the application of additive manufacturing technology in the automotive sector. The training methods applied include the delivery of theoretical materials, technical demonstrations, and exercises. Evaluation of the effectiveness of the training was conducted through comparative analysis of pre-test and post-test results, which aims to measure the improvement of participants' competence before and after attending the training. The results of data analysis showed a significant increase in students' mastery of concepts and technical skills, especially in the use of 3D printing technology for component manufacturing. This training is expected to be a relevant and adaptive learning model, in order to prepare SMK graduates to face the dynamics of the automotive industry which is increasingly based on technology and innovation
Optimizing Students' Understanding of the Mechanical Properties of Stainless Steel through Interactive Learning Media based on Machine Learning Karudin, Arwizet; Leni, Desmarita; Nasrullah, Nasrullah; Sumiati, Ruzita; Haris, Haris
IJIS Edu : Indonesian Journal of Integrated Science Education Vol 6, No 2 (2024): July 2024
Publisher : UIN Fatmawati Sukarno Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29300/ijisedu.v6i2.3114

Abstract

Traditional learning media tends to have limitations in providing interactive experiences that can stimulate better understanding. This is supported by changes in learning styles among students, influenced by extensive exposure to computers and the internet, leading students to prefer learning with the aid of visualizations. This research designs, develops, and tests a machine learning-based visualization tool integrated with the Streamlit framework to enhance students' understanding of the mechanical properties of materials. This visualization tool consists of four main features: data analysis, correlation analysis, 3D visualization, and prediction models using machine learning. The data used for training the machine learning model includes tensile test data of low-alloy steel, comprising mechanical properties, chemical elements, and heat treatment temperatures. The research results indicate that the visualization tool can illustrate the cause-and-effect relationships of parameters influencing the changes in the mechanical properties of low-alloy steel. Each feature in this visualization tool can be utilized to support the analysis of mechanical properties and improve students' understanding of material mechanical properties. Additionally, the visualization tool is evaluated by experts, with information accuracy scoring 4 in the good category, visualization quality at 4.25 in the good category, suitability for learning at 4 in the good category, and ease of use at 4.5 in the good category. Nevertheless, further research and development are needed to test and expand the use of this visualization tool in various learning contexts and other material fields.
Co-Authors ., Adriansyah ., Islahuddin ., Maimuzar ., Muchlisinalahuddin Abdul Aziz 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 M. Luthfi Artia Maimuzar Maimuzar Meiki Eru Putra 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 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 Sicilia Afriyani 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