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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 Jurnal Agrotek Tropika Teorema: Teori dan Riset Matematika JURNAL VOKASI TEKNOLOGI INDUSTRI (JVTI) Jurnal Inovasi Pendidikan dan Sains Jurnal Informatika Teknologi dan Sains (Jinteks) 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 Journal of Educational Studies
Arifin, Samsul
Institut Teknologi Sains Bandung
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Machine Predictive Maintenance by Using Support Vector Machines Idrus Assagaf; Agus Sukandi; Abdul Azis Abdillah; Samsul Arifin; Jonri Lomi Ga
Recent in Engineering Science and Technology Vol. 1 No. 1 (2023): RiESTech Vol. 1 No. 1 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 Samsul Arifin; Monica Mayeni Manurung; Stanley Jonathan; Melody Effendi; Puguh Wahyu Prasetyo
Recent in Engineering Science and Technology Vol. 2 No. 3 (2024): RiESTech Vol. 2 No. 3 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 Dwi Wijonarko; Samsul Arifin; Muhammad Faisal; Muhammad Nabil Pratama; Okta Nindita Priambodo; Edwin Setiawan Nugraha
Recent in Engineering Science and Technology Vol. 3 No. 2 (2025): RiESTech Vol. 3 No. 2 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.
Development Of 6CS Skills Oriented Interactive Mathematics Teaching Materials To Improve The Conceptual Understanding And The Critical Thinking Abilities On High School Students Nerru Pranuta Murnaka; Sulistiawati Sulistiawati; Samsul Arifin; Marini Marini; Muhammad Nur Huda; Elizabeth W. M. Indira; Ayatul Ulya; Haryanti Haryanti
Journal of Educational Studies Vol. 4 No. 2 (2026): July
Publisher : Lembaga Bale Literasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58218/jes.v4i2.2871

Abstract

This research is motivated by the importance of making teaching materials that are able to awaken students' 6C skills to face the era of the industrial revolution 4.0. The 6C skills referred to in this study include communication skills, critical thinking, collaboration, creativity, citizenship/culture, and character education/connectivity). The purpose of this research is to investigate the feasibility and effectiveness of interactive mathematics teaching materials on probability materials developed in improving the ability to conceptual understanding and critical thinking. The research method used is this development research refers to the 4D model developed by Thiagarajan which includes the stages of define, design, development, and dissemination. The research was conducted at SMA Islamic Village, Kelapa Dua, Tangerang in class XII IPA. Before the teaching materials developed are implemented for students, validation of the teaching materials is carried out which includes validation of material experts, language experts, media experts, and evaluation experts. The results obtained from this study are the teaching materials developed are declared feasible and ready to be used. Based on the results of the analysis using descriptive statistical techniques, the validity of the teaching materials developed is very valid.
Mapping Global Collaboration and Research Trends in Nanocellulose: A Bibliometric and Text Mining Analysis Edwin Kristianto Sijabat; Samsul Arifin
JURNAL INOVASI PENDIDIKAN DAN SAINS Vol 7 No 3 (2026): December
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Nahdlatul Wathan Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51673/jips.v7i3.2708

Abstract

Nanocellulose has emerged as a promising biomaterial with broad applications across sustainable packaging, biomedical engineering, and environmental remediation. Despite increasing global interest, a comprehensive understanding of the collaborative dynamics and evolving research directions in this field remains limited. This study aims to map the global research landscape of nanocellulose from 2021 to 2025 through an integrative bibliometric and text mining approach. A total of 2,971 scientific articles were retrieved from the Scopus database using a targeted query focused on nanocellulose-related keywords within the materials science domain. The metadata was analyzed using VOSviewer to visualize co-authorship networks, keyword co-occurrence, citation linkages, and bibliographic coupling. Complementary text analysis, including topic modeling via Latent Dirichlet Allocation (LDA), was conducted using Python libraries such as NLTK, spaCy, and Gensim. The results reveal China as the leading country in terms of research output, institutional collaboration, and funding, followed by India and the United States. Key thematic clusters center around biomedical applications, composite development, and water treatment. Highly cited authors and organizations are concentrated in specialized pulp and paper research institutes. This study not only delineates the structure and trajectory of global nanocellulose research but also highlights emerging areas and collaboration patterns. The findings can guide future research investments, inform policy decisions, and foster strategic academic partnerships in the rapidly evolving field of cellulose-based nanomaterials
Stunting Risk Factor Analysis Using Seemingly Unrelated Regression (SUR) Integrated with Machine Learning Wiwik Wiyanti; Amanatullah Pandu Zenklinov; Jacob Stevy Seleki; Sausan Ramadhani; Valensius Jimy; Samsul Arifin
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9630

Abstract

Stunting is a disorder in children caused by chronic nutritional problems. Stunting is usually characterized by a child’s failure to grow and develop optimally. In Indonesia, the government is focusing on addressing of stunting case, as it aims to develop the superior of human resources. In Tangerang regency is currently holding a “Gebrak Tegas” program to address the problem of stunting. The causes of stunting required scientific study to help the government understand the scientific factors that causing stunting. Therefore, this study aims to analyze the factors causing stunting the children in the Tangerang regency. The data analysis method in this study use the Seemingly Unrelated Regression (SUR), which is integrated with a machine learning, namely Random Forest. The data used in this study were obtained from primary data through questionnaires. The subjects of this study were parents of stunting and non-stunting children who were at “Posyandu” under of “Kelapa dua” and “Binong” health centers. Sampling method in this study is purposive-random sampling. The results of the data analysis showed that the five variables from the factors measured had the most significant influence, namely nutritional, socio-economi, and pregnancy and childbirth history factors. Five variables that influence children stunting are animal protein, which has the highest probability of 87.5% when the children consumes protein once or twice a week. The children consume vitamin A twice has a 97% probability. The source of income for the parents, whether from the private or self-employment, has a probability of over 90%. Furthermore, the consumption of iron-boosting tablets by mother during pregnancy and the amount of income from the parents have a probability of 84%.
THE EFFECT OF FERTILIZER DOSES ON VARIATIONS IN AGE OF PALM OIL PLANT Okta Nindita Priambodo; Anugerah Rafi Pratama; Samsul Arifin; Dani Lukman Hakim
Jurnal Agrotek Tropika Vol. 14 No. 3 (2026): JURNAL AGROTEK TROPIKA VOL 14, AGUSTUS 2026
Publisher : Departement of Agrotechnology, Agriculture Faculty, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jat.v14i3.11344

Abstract

To produce quality oil, proper plant care is essential, with fertilization being key to maintaining high productivity. As the plant ages, the required fertilizer quantity decreases, which can impact production outcomes. To assess the effects of reduced fertilization, observations were made on oil palm plants with decreased fertilizer quantities. These observations focused on plant health and oil palm production results. Analyzing plant health can be done in various ways, one of which is by using remote sensing technology. Remote sensing analysis of plant health can be conducted using Sentinel 2A satellite imagery, accessible and downloadable via Google Earth Engine. NDVI analysis is used on Sentinel 2A imagery to assess plant health. The analysis results show consistent health classification across different planting years (0.72-1), indicate a very healthy classification, demonstrating that reducing the quantity of fertilizer does not affect the NDVI values in different planting years. However, reducing the quantity of fertilizer does impact the productivity of oil palm plants. These findings provide an important contribution to fertilizer management, particularly in oil palm plantations.
Co-Authors Abdillah, Abdul Azis Abdul Azis Abdillah Adi Adi Agus Sukandi Alfian Alfian Alya Nabilah Amanatullah Pandu Zenklinov Amril Mutoi Siregar Anugerah Rafi Pratama Arif Rahman Hakim Arumella Surgandini Assagaf, Idrus Ayatul Ulya Bobbi Rahman Citra Nur Napiah Dani Lukman Hakim Dani Lukman Hakim Dewi Yanti Liliana Dwi Anto, Septian Dwi Wijonarko Edwin Kristianto Sijabat Edwin Setiawan Nugraha Ega Edistria Elita Putri, Rizky Eliza Ariesta Elizabeth W. M. Indira Favian Jarsi Taufiqqurakhman Haryanti Haryanti Hexsel Aldoegasha I Gusti Agung Anom Yudistira Indra Bayu Muktyas Indra Bayu Muktyas Jacob Stevy Seleki Jonri Lomi Ga Jufra, Arlita Aristianingsih Jufra, Jufra Klara Iswara Sukmawati Lucky, Henry Manurung, Mika Meitriana Manurung, Monica Mayeni Marini Marini Melody Effendi Merios Gusan Putra Monica Mayeni Manurung Muhamad Faisal, Muhamad Muhammad Amien Ibrahim Muhammad Faisal Muhammad Fathir Fahlevi Muhammad Nabil Pratama Muhammad Nur Huda Muhammad Rezakusuma Muktyas, Indra Bayu Nerru Pranuta Murnaka, Nerru Pranuta Nilam Atsirina Krisnaputri Nur Dava Kurniawan Nur Davi Kurniawan Nusaibah Okta Nindita Priambodo Pimpi, La Priambodo, Oktanindita Puguh Wahyu Prasetyo Puguh Wahyu Prasetyo, Puguh Raditha, Alya Maura Repka, Joe Rifky Kurniawan Rinda Nariswari Rinda Nariswari RONI Rully Charitas Indra Prahmana Rusli P. D. Kolnel Safitri, Raudhatun Sausan Ramadhani Setyawan, Fariz Siti A. M. Karubaba Stanley Jonathan Suharno Suharno Sulistiawati Sulistiawati Sulistiawati Sulistiawati Sulistiawati Sulistiawati Surjandy Susyanto, Nanang Sutrisno, Utis Taufiqqurahman Hutri Tiawan Tri Handayani Usep Valensius Jimy Widyakusuma, Nita Wijaya, Andryan Kalmer Wijayanti, Dian Eka Winarto Selamet, Muhammad Windria, Hening Wiwik Wiyanti Yanuar Yanuar Yulia Wulandari, Yulia Zahran Muzakki