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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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Analisis Publikasi Ilmiah mengenai Prestasi Belajar Siswa melalui Pendekatan Bibliometrik dan Teknologi Arifin, Samsul
JURNAL VOKASI TEKNOLOGI INDUSTRI (JVTI) Vol 6, No 2 (2024): Jurnal Vokasi, Teknologi, dan Industri (JVTI)
Publisher : Institut Teknologi Sains Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36870/jvti.v6i2.362

Abstract

Pendidikan sangat berarti bagi kehidupan manusia dalam ruang lingkup pendidikan yang luas menjadi penopang bangkitnya sebuah bangsa, untuk itu kualitas pembangunan sumber daya manusia menjadi faktor utama penentu kemajuan suatu bangsa. Salah satu upaya dalam tolak ukur kualitas, yaitu dengan mengetahui tingkat kualitas siswa yang dimiliki oleh setiap lembaga pendidikan atau bangsa. Untuk meningkatkan hal tersebut, maka berbagai macam penelitian terus dilakukan yang berkaitan langsung dengan prestasi belajar siswa baik dari pengaruh metodologi pembelajaran, media ajar dan lain sebagainya. Terlepas dari seberapa banyak yang meneliti prestasi belajar dan variabel terkait penelitian yang mengukur atau memeriksa perkembangan tersebut masih sangat terbatas sedangkan kebutuhan akan tantangan pendidikan harus dihadapi. Penelitian ini bertujuan untuk melihat dan mengukur sejauh mana perkembangan penelitian tentang prestasi belajar siswa dari tahun 2023-2024, dan menemukan keterbaruan. Penelitian ini menggunakan metode analisis bibliometrik yang mengambil metadata dari Scopus sebanyak 1.800 metadata. Hasil dari proses analisis menunjukkan ada 1.803 penulis yang terhimpun dalam penelitian yang terkait, namun dalam penelitiannya tidak begitu banyak hubungan antar penulis satu dengan yang lainnya, hanya sebagian yang menerbitkan jurnal lebih dari 5 yaitu 2 orang penulis dengan jumlah terbitan sebanyak 7 dokumen. Adapun asal negara yang paling dominan adalah United States. Kemudian kata kunci yang paling banyak terkait adalah human, academic achievement, students, motivation, gender, literacy, highschool, knowledge dan artikel yang paling banyak dikutip adalah milik Bai B,; Wang J. Yang terbit tahun 2023
Web Application for IHSG Prediction Using Machine Learning Algorithms Wijaya, Andryan Kalmer; Lucky, Henry; Arifin, Samsul
Indonesian Journal of Applied Mathematics and Statistics Vol. 2 No. 1 (2025): Indonesian Journal of Applied Mathematics and Statistics (IdJAMS)
Publisher : Lembaga Penelitian dan Pengembangan Matematika dan Statistika Terapan Indonesia, PT Anugrah Teknologi Kecerdasan Buatan PT Anugrah Teknologi Kecerdasan Buatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71385/idjams.v2i1.21

Abstract

This study investigates the effectiveness of the Long Short-Term Memory (LSTM) method in predicting the stock price of the Composite Stock Price Index (CSPI). LSTM, a variant of Recurrent Neural Networks, is designed to overcome challenges such as the vanishing gradient problem and long-term dependencies in time-series data. Given the dynamic and volatile nature of financial markets, accurate stock price prediction is crucial for investors and analysts. The data set used in this study consists of daily CSPI prices from January 2000 to December 2023, which serve as both training and testing data for model development. The LSTM model is trained to forecast the next day’s stock price, and its performance is compared with traditional statistical models, particularly the Autoregressive Integrated Moving Average (ARIMA) model and linear regression. Performance evaluation is based on the Mean Absolute Percentage Error (MAPE), a widely used metric for assessing predictive accuracy. The results indicate that while the ARIMA model achieves a lower MAPE of 0.7%, demonstrating slightly superior accuracy, the LSTM model also performs well, with a MAPE of approximately 1%. These findings suggest that while statistical models like ARIMA remain highly effective for stock price forecasting, deep learning approaches such as LSTM still offer promising predictive capabilities, especially when handling large and complex datasets. The ability of LSTM to capture non-linear patterns and temporal dependencies makes it a viable alternative for financial forecasting, potentially benefiting traders and market analysts seeking data-driven decision-making tools.
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.
Unimodular matrix and bernoulli map on text encryption algorithm using python Arifin, Samsul; Muktyas, Indra Bayu; Prasetyo, Puguh Wahyu; Abdillah, Abdul Azis
Al-Jabar: Jurnal Pendidikan Matematika Vol 12 No 2 (2021): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v12i2.10469

Abstract

One of the encryption algorithms is the Hill Cipher. The square key matrix in the Hill Cipher method must have an inverse modulo. The unimodular matrix is one of the few matrices that must have an inverse. A unimodular matrix can be utilized as a key in the encryption process. This research aims to demonstrate that there is another approach to protect text message data. Symmetric cryptography is the sort of encryption utilized. A Bernoulli Map is used to create a unimodular matrix. To begin, the researchers use an identity matrix to generate a unimodular matrix. The Bernoulli Map series of real values in (0,1) is translated to integers between 0 and 255. The numbers are then inserted into the unimodular matrix's top triangular entries. To acquire the full matrix as the key, the researchers utilize Elementary Row Operations. The data is then encrypted using modulo matrix multiplication.
Text security by using a combination of the vigenere cipher and the rubik's cube method of size 4×4×4 Safitri, Raudhatun; Prasetyo, Puguh Wahyu; Wijayanti, Dian Eka; Arifin, Samsul; Setyawan, Fariz; Repka, Joe
Al-Jabar: Jurnal Pendidikan Matematika Vol 14 No 2 (2023): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v14i2.14276

Abstract

Background: In the current era of technology, information security is increasingly important. The growth of technology leads to a higher level of threat to the security of data and information dissemination, and cryptography is a valuable protective tool.Aim: The primary objective of this research is to enhance text security through the fusion of the Vigenere cipher and the Rubik's cube algorithm. By leveraging this novel approach, we aim to fortify the confidentiality of textual data against potential eavesdroppers and adversaries. To demonstrate the practicality of this method, we perform a simulation using the Python programming language within the Google Colab environment. Method: This study employs a qualitative research methodology supplemented by empirical simulation. The combination of the Vigenere Cipher and the Rubik's Cube algorithm in a 4×4×4 configuration is implemented to encrypt and decrypt text. The simulation is executed using the Google Colab platform, enabling a practical illustration of the encryption process.Result: The results of our research indicate the feasibility of generating ciphertext through the amalgamation of the Vigenere Cipher and the Rubik's Cube algorithm in the specified 4×4×4 configuration. The simulation conducted in Google Colab serves as concrete evidence of the effectiveness and practicality of this combined encryption method.Conclusion: In conclusion, this research offers a compelling approach to bolstering text security in the modern era of information technology. By combining the Vigenere Cipher with the Rubik's Cube algorithm in a 4×4×4 configuration, we have demonstrated the potential to significantly enhance the confidentiality of sensitive textual data. The empirical simulation conducted in Google Colab reaffirms the practicality and viability of this innovative encryption technique, highlighting its potential as a valuable tool in the realm of information security.
OUTPUT VISUALIZATION FROM RESULT OF DISCRETE EVENT SYSTEM SIMULATION WITH ‘simmer’ R PACKAGE Yudistira, I Gusti Agung Anom; Nariswari, Rinda; Arifin, Samsul
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.269 KB) | DOI: 10.30598/barekengvol17iss1pp0581-0592

Abstract

This study aims to describe the various capabilities of the simmer package on R, especially in running a discrete event simulation model of a circular system, then develop a DES simulation model building technique, which is effective and can represent real systems well, and explore the simulation output on this simmer, both in statistical summary form and parameter estimation. The method used in this research is the literature study with descriptive and exploratory approaches. Model development is more effective when it is carried out starting from simple models, to more complex forms step by step, and describing the system using a flow chart. Replication for simulations is easy to perform so as to get standard error values ​​for model parameter estimators. The stages in developing a discrete event simulation model with a simmer, start with compiling a simple flowchart to a more complex form, and replication is carried out. The simmer output in the form of a data frame makes it very easy to process the output further. The simple R API on Simmer will also make it easier to simulate.
Stunting Risk Factor Analysis Using Seemingly Unrelated Regression (SUR) Integrated with Machine Learning Wiyanti, Wiwik; Zenklinov, Amanatullah Pandu; Seleki, Jacob Stevy; Ramadhani, Sausan; Jimy, Valensius; Arifin, Samsul
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%.
ANALISIS FAKTOR JARINGAN KOLABORASI PENELITI MENGGUNAKAN METODE ANALISIS BIBLIOMETRIK Dwi Anto, Septian; Elita Putri, Rizky; Winarto Selamet, Muhammad; Widyakusuma, Nita; Arifin, Samsul
Pedagogik : Jurnal Pendidikan Guru Sekolah Dasar Vol. 13 No. 1 (2025): PEDAGOGIK : Jurnal Pendidikan Guru Sekolah Dasar
Publisher : Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/pedagogik.v13i1.10631

Abstract

Penelitian ini bertujuan untuk menganalisis jaringan kolaborasi peneliti dengan menggunakan metode analisis bibliometrik. Data jaringan yang divisualisasikan dalam bentuk grafis menggunakan VOSviewer menunjukkan hubungan antara peneliti berdasarkan faktor kolaborasi. Analisis ini mengidentifikasi peneliti kunci, pola kolaborasi, serta klaster atau kelompok berdasarkan faktor keterkaitan dalam penelitian. Hasil penelitian ini memberikan gambaran tentang struktur kolaborasi dalam komunitas akademik serta potensi kolaborasi antar peneliti. Data dikumpulkan dari database Scopus dengan menggunakan kata kunci “analisis AND faktor". Kemudian penulis menggunakan software VOSviewer untuk menganalisis dan memvisualisasikan database yang diperoleh. Hasil penelitian menunjukkan bahwa hasil analisis sitasi menunjukkan jumlah kutipan per tahun dari 2020 - 2024 adalah 2.562 data.
Trends, Contributions and Prospects: Bibliometric Analysis of ANOVA Research in 2022-2023 Sutrisno, Utis; Wulandari, Yulia; Usep; Arifin, Samsul; Roni; Manurung, Monica Mayeni; Faisal, Muhamad
Indonesian Journal of Applied Mathematics and Statistics Vol. 1 No. 1 (2024): Indonesian Journal of Applied Mathematics and Statistics (IdJAMS)
Publisher : Lembaga Penelitian dan Pengembangan Matematika dan Statistika Terapan Indonesia, PT Anugrah Teknologi Kecerdasan Buatan PT Anugrah Teknologi Kecerdasan Buatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71385/idjams.v1i1.7

Abstract

This study aims to analyze the development and contribution of research on the topic of ANOVA (Analysis of Variance) using the bibliometric analysis method. ANOVA is a statistical method used to compare the means of three or more groups. Through bibliometric analysis, we explore articles published in journals related to ANOVA within a certain time span, namely 2022-2023. The method of bibliometric analysis involves collecting bibliographic data from relevant sources and analyzing characteristics such as frequency of publication, notable authors, and most frequently cited journals. This study uses a bibliometric analysis method that retrieves 1,911 metadata from Scopus. The results of the bibliometric analysis revealed an increase in the number of publications about ANOVA during the time span studied, namely 2022-2023. These findings indicate that ANOVA remains a relevant and interesting topic for researchers in various disciplines. In addition, there is a wide variety of research topics related to ANOVA, including the use of ANOVA in various contexts, such as laboratory experiments, clinical research, and analysis of survey data. By analyzing the contribution of research on the topic of ANOVA, this study provides valuable insights for us. Moreover, the researcher also discussed prospects for future research on this topic, including the development of new analytical methods and the wider application of ANOVA in various scientific and practical contexts.
Clustering Analysis: A Note on Methodologies and Trends Raditha, Alya Maura; Arifin, Samsul
Indonesian Journal of Applied Mathematics and Statistics Vol. 2 No. 2 (2025): Indonesian Journal of Applied Mathematics and Statistics (IdJAMS)
Publisher : Lembaga Penelitian dan Pengembangan Matematika dan Statistika Terapan Indonesia, PT Anugrah Teknologi Kecerdasan Buatan PT Anugrah Teknologi Kecerdasan Buatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71385/idjams.v2i2.23

Abstract

This study conducts a bibliometric analysis of clustering techniques in scientific research using VOSviewer and Gen-AI-based Consensus.app. The dataset was collected from Scopus and the Web of Science using predefined queries to filter articles published in 2024 and 2025. VOSviewer was utilized to visualize co-authorship networks, keyword co-occurrence, citation relationships, bibliographic coupling, and co-citation patterns, revealing key research clusters and influential studies. Additionally, Consensus.app was employed to generate AI-driven insights, summarizing key themes and emerging trends in clustering methodologies. The results indicate that clustering research is highly collaborative, with strong institutional networks and interdisciplinary applications. Machine learning, data mining, and network analysis emerge as dominant themes, with key publications shaping methodological advancements. The co-citation network highlights foundational studies that have influenced the field. By combining traditional bibliometric techniques and AI-based analysis, this study offers a comprehensive perspective on clustering research, identifying knowledge gaps and potential future directions. These findings provide valuable insights for researchers seeking to explore emerging topics, collaborate effectively, and contribute to the development of clustering methodologies. However, this study is limited to publications indexed in Scopus and Web of Science within the years 2024–2025, which may not fully capture longer-term developments. Future research could expand the scope to other databases and timeframes for a broader perspective.
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