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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA CommIT (Communication & Information Technology) Al-Jabar : Jurnal Pendidikan Matematika Union: Jurnal Ilmiah Pendidikan Matematika Jurnal Matematika: MANTIK Wacana Akademika : Majalah Ilmiah Kependidikan Numeracy : Jurnal Ilmiah Pendidikan Matematika IndoMath: Indonesia Mathematics Education BAREKENG: Jurnal Ilmu Matematika dan Terapan Teorema: Teori dan Riset Matematika JURNAL VOKASI TEKNOLOGI INDUSTRI (JVTI) Pedagogik : Jurnal Pendidikan Guru Sekolah Dasar Recent in Engineering Science and Technology Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Applied Mathematics and Statistics
Samsul Arifin
Binus University
Agriculture, Biological Sciences & Forestry Arts Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Journal : Recent in Engineering Science and Technology

 1 
Self-Protection Equipment Detection System in Heavy Weight Workshop of Politeknik Negeri Jakarta Using Artificial Intel-ligence Rezakusuma, Muhammad; Abdillah, Abdul Azis; Liliana, Dewi Yanti; Edistria, Ega; Arifin, Samsul; Muzakki, Zahran
Recent in Engineering Science and Technology Vol. 1 No. 01 (2023): RiESTech Volume 01 No. 01 Years 2023
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v1i01.4

Abstract

The creating process, how it works and the performance of the detection system using Artificial Intelligence. The development of this innovation contributes to the Heavy Equipment Workshop of the Jakarta State Polytechnic to detect the early potential for work accidents. The methods are device tuning, inputs, training models, performance, trials and outputs. The creating process and how the detection system works using Artificial Intelligence each has 3 steps and accuracy using 3 cameras, namely the internal webcam (1MP), the JETE external webcam (720P) and the Samsung Galaxy A22 mobile phone camera (13MP). The process of making this innovation has 3 steps, namely data input, export, file grouping. There are 3 steps to work, namely open the file, run and output. The result of the accuracy of the internal webcam is very low, the JETE external webcam is better than the internal webcam and the mobile phone camera is better than the JETE external webcam.
Machine Predictive Maintenance by Using Support Vector Machines Assagaf , Idrus; Sukandi, Agus; Abdillah, Abdul Azis; Arifin, Samsul; Ga, Jonri Lomi
Recent in Engineering Science and Technology Vol. 1 No. 01 (2023): RiESTech Volume 01 No. 01 Years 2023
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v1i01.6

Abstract

Predictive Maintenance (PdM) is an adoptable worth strategy when we deal with the maintenance business, due to a necessity of minimizing stop time into a minimum and reduce expenses.  Recently, the research of PdM is now begin in utilizing the artificial intelligence by using the machine data itself and sensors. Data collected then analyzed and modelled so that the decision can be made for the near and next future. One of the popular artificial intelligences in handling such classification problem is Support Vector Machines (SVM). The purpose of the study is to detect machine failure by using the SVM model. The study is using database approach from the model of Machine Learning. The data collection comes from the sensors installed on the machine itself, so that it can predict the failure of machine function. The study also to test the performance and seek for the best parameter value for building a detection model of machine predictive maintenance The result shows based on dataset AI4I 2020 Predictive Maintenance, SVM is able to detect machine failure with the accuracy of 80%.
Trend Analysis of the ARIMA Method: A Survey of Scholarly Works Arifin, Samsul; Manurung , Monica Mayeni; Jonathan, Stanley; Effendi, Melody; Prasetyo , Puguh Wahyu
Recent in Engineering Science and Technology Vol. 2 No. 03 (2024): RiESTech Volume 02 No. 03 Years 2024
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v2i03.65

Abstract

Recent research trends in bibliometric analysis using the ARIMA method have attracted the attention of many researchers in this field. This study aims to conduct a thorough review of related studies that apply the ARIMA method in bibliometric analysis. The dataset used was taken from the Scopus Web using VOSviewer. The main objective of this study is to identify the latest research trends related to the use of the ARIMA method in bibliometric analysis. The results of the analysis show that the use of the ARIMA method in bibliometric analysis has increased significantly in the last few years. Studies using this method have made valuable contributions to understanding research trends and scientific developments in various fields. These findings provide important insights for practitioners and researchers in the field of bibliometric analysis and can be used as a practical guide for those who wish to use the ARIMA method in bibliometric analysis. In addition, this study also discusses the strengths and weaknesses of using the ARIMA method in bibliometric analysis. This method has advantages in its ability to identify and model trends well but also has some limitations regarding parameter selection and interpretation of results. Therefore, this study provides a more comprehensive understanding of the application of the ARIMA method in bibliometric analysis and encourages further research in addressing the challenges associated with using this method. The benefit of this research lies in its ability to provide valuable insights for researchers, practitioners, and policymakers in understanding the latest research trends in bibliometric analysis using the ARIMA method. The findings of this research can be used to make strategic decisions regarding the development and publication of scientific publications, as well as strengthen an understanding of research trends in certain fields. In conclusion, this study provides a comprehensive review of the latest research trends in bibliometric analysis using the ARIMA method. The findings and conclusions of this study provide a deeper understanding of the application of the ARIMA method in bibliometric analysis, as well as provide recommendations for further research in developing analytical methods and looking at new aspects of bibliometric analysis using the ARIMA method.
Mobile Ad-Hoc Network (MANET) Method: Some Trends and Open Issues Wijonarko, Dwi; Arifin, Samsul; Faisal, Muhammad; Pratama, Muhammad Nabil; Priambodo, Okta Nindita; Nugraha, Edwin Setiawan
Recent in Engineering Science and Technology Vol. 3 No. 02 (2025): RiESTech Volume 3 No. 02 Years 2025
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v3i2.108

Abstract

This study analyzes the latest developments and trends in the field of Mobile Ad-Hoc Networks (MANET) through a bibliometric approach using a metadata dataset from publications taken from Scopus between 2021 and 2024. By utilizing VOSviewer to visualize the data, the study identified key keywords that dominated the MANET literature, such as "security", "routing protocols", "mobility", and "5G". The visualization results show several important clusters, including topics related to network security, vehicle networks (VANET), and the application of advanced technologies such as machine learning in network management. Despite the decline in the number of publications in 2023 and 2024, collaboration between authors continues to show a strong trend. The research also highlights various challenges that are still open problems, such as the development of efficient routing protocols, improving network security, and managing resources in a dynamic MANET environment. In addition to the VOSviewer analysis, further exploration was carried out using the built-in visualization tools from the Scopus web platform to enrich the interpretation of emerging topics and research connections. This was followed by a deeper conceptual mapping using Scopus AI, which provided a visual breakdown of interconnected themes such as security issues, routing protocols, and different network types like VANET and FANET. To complement and validate the findings, the study also incorporated evidence based summaries retrieved from Consensus.app, offering additional insights from AI-driven scientific consensus. This multi-platform approach enhances the reliability of the analysis and provides a more comprehensive view of current and future research directions in the MANET domain.
Co-Authors Abdillah, Abdul Azis Abdul Azis Abdillah Adi Adi Agus Sukandi Alfian Alfian Arif Rahman Hakim Arumella Surgandini Assagaf, Idrus Bobbi Rahman Dewi Yanti Liliana Dwi Anto, Septian Dwi Wijonarko Edistria, Ega Effendi, Melody Elita Putri, Rizky Ga, Jonri Lomi I Gusti Agung Anom Yudistira Indra Bayu Muktyas Indra Bayu Muktyas Jimy, Valensius Jonathan, Stanley Jufra, Arlita Aristianingsih Jufra, Jufra Klara Iswara Sukmawati Lucky, Henry Manurung , Monica Mayeni Manurung, Mika Meitriana Manurung, Monica Mayeni Muhamad Faisal, Muhamad Muhammad Amien Ibrahim Muhammad Faisal Muktyas, Indra Bayu Muzakki, Zahran Nerru Pranuta Murnaka, Nerru Pranuta Nugraha, Edwin Setiawan Pimpi, La Pratama, Muhammad Nabil Priambodo, Oktanindita Puguh Wahyu Prasetyo, Puguh Raditha, Alya Maura Ramadhani, Sausan Repka, Joe Rezakusuma, Muhammad Rinda Nariswari Rinda Nariswari RONI Rully Charitas Indra Prahmana Rusli P. D. Kolnel Safitri, Raudhatun Seleki, Jacob Stevy Setyawan, Fariz Siti A. M. Karubaba Suharno Suharno Sulistiawati Sulistiawati Sulistiawati Sulistiawati Susyanto, Nanang Sutrisno, Utis Tri Handayani Usep Widyakusuma, Nita Wijaya, Andryan Kalmer Wijayanti, Dian Eka Winarto Selamet, Muhammad Windria, Hening Wiwik Wiyanti, Wiwik Yanuar Yanuar Yulia Wulandari, Yulia Zenklinov, Amanatullah Pandu