Claim Missing Document
Check
Articles

Found 30 Documents
Search

PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SQUARE TERHADAP KEMAMPUAN PEMAHAMAN KONSEP MATEMATIS SISWA Siti A. M. Karubaba; Bobbi Rahman; Samsul Arifin
IndoMath: Indonesia Mathematics Education Vol 2 No 1 (2019)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (542.246 KB) | DOI: 10.30738/indomath.v2i1.3150

Abstract

This study aims to investigate whether the ability to understand mathematical concepts of students who get cooperative learning think pair square type is higher than students who get conventional learning. The research method used is a quasi-experimental method with a research design that is nonequivalent control group design. In this study sample selection using the Convenience Sampling technique is students of class VIII.5 as the control class and students of class VIII.6 as the experimental class. Experimental class students get learning using the think pair square learning model, while students in the control class get conventional learning. The instruments in this study were in the form of pretest and posttest questions in the form of questions describing the ability to understand students' mathematical concepts. In the research that has been done, the significance (sig.) 0,000 is smaller than the significance level α = 0.05. The research hypothesis testing was carried out by the Mann-Whitney test using SPSS and a significance level of 5% (α = 0.05).. In this study it was found that the ability to understand mathematical concepts of students who received think pair square learning was higher than students who obtained conventional learning.
PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE THINK PAIR SQUARE TERHADAP KEMAMPUAN PEMAHAMAN KONSEP MATEMATIS SISWA Siti A. M. Karubaba; Bobbi Rahman; Samsul Arifin
IndoMath: Indonesia Mathematics Education Vol 2 No 1 (2019)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (542.246 KB) | DOI: 10.30738/indomath.v2i1.3150

Abstract

This study aims to investigate whether the ability to understand mathematical concepts of students who get cooperative learning think pair square type is higher than students who get conventional learning. The research method used is a quasi-experimental method with a research design that is nonequivalent control group design. In this study sample selection using the Convenience Sampling technique is students of class VIII.5 as the control class and students of class VIII.6 as the experimental class. Experimental class students get learning using the think pair square learning model, while students in the control class get conventional learning. The instruments in this study were in the form of pretest and posttest questions in the form of questions describing the ability to understand students' mathematical concepts. In the research that has been done, the significance (sig.) 0,000 is smaller than the significance level α = 0.05. The research hypothesis testing was carried out by the Mann-Whitney test using SPSS and a significance level of 5% (α = 0.05).. In this study it was found that the ability to understand mathematical concepts of students who received think pair square learning was higher than students who obtained conventional learning.
Penerapan Model Kooperatif Tipe Numbered Head Tgether Untuk Meningkatkan Kemampuan Komunikasi Matematis Siswa SMP Adi Adi; Samsul Arifin; Bobbi Rahman
IndoMath: Indonesia Mathematics Education Vol 2 No 2 (2019)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (705.619 KB) | DOI: 10.30738/indomath.v2i2.4409

Abstract

Mathematical communication skills are abilities that must be possessed by students in learning mathematics so that students can convey ideas or ideas both verbally and in writing. Based on the results of observations made at SMP Muhammadiyah 5 Kota Tangerang, students' mathematical communication skills are still low. Responding to these problems, teachers need to apply cooperative learning models. One type of cooperative learning model that can train students' mathematical communication skills is Numbered Head Together (NHT). The purpose of this study is to investigate the improvement in mathematical communication skills of students who get Numbered Head Together (NHT) learning higher than students who get conventional learning. This study uses a quasi experimental design type nonequivalent control group design. The population in this study were 4 grade VIII students of SMP Muhammadiyah 5 Kota Tangerang and the sample of this study were students of grades VIII.2 and VIII.3. The sampling technique uses cluster random sampling. The research hypothesis was tested with a nonparametric test, namely Mann Whitney because the sample in this study amounted to 38 students from two classes VIII.2 and class VIII.3. The results showed that the increase in mathematical communication skills of students who obtained mathematics learning with the Numbered Head Together (NHT) model was higher than students who obtained conventional learning.
An Explainable AI Model for Hate Speech Detection on Indonesian Twitter Muhammad Amien Ibrahim; Samsul Arifin; I Gusti Agung Anom Yudistira; Rinda Nariswari; Abdul Azis Abdillah; Nerru Pranuta Murnaka; Puguh Wahyu Prasetyo
CommIT (Communication and Information Technology) Journal Vol. 16 No. 2 (2022): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v16i2.8343

Abstract

To avoid citizen disputes, hate speech on social media, such as Twitter, must be automatically detected. The current research in Indonesian Twitter focuses on developing better hate speech detection models. However, there is limited study on the explainability aspects of hate speech detection. The research aims to explain issues that previous researchers have not detailed and attempt to answer the shortcomings of previous researchers. There are 13,169 tweets in the dataset with labels like “hate speech” and “abusive language”. The dataset also provides binary labels on whether hate speech is directed to individual, group, religion, race, physical disability, and gender. In the research, classification is performed by using traditional machine learning models, and the predictions are evaluated using an Explainable AI model, such as Local Interpretable Model-Agnostic Explanations (LIME), to allow users to comprehend why a tweet is regarded as a hateful message. Moreover, models that perform well in classification perceive incorrect words as contributing to hate speech. As a result, such models are unsuitable for deployment in the real world. In the investigation, the combination of XGBoost and logical LIME explanations produces the most logical results. The use of the Explainable AI model highlights the importance of choosing the ideal model while maintaining users’ trust in the deployed model.
A Bibliometric Study of 3D Printing's Educational Applications Arifin, Samsul
JURNAL VOKASI TEKNOLOGI INDUSTRI (JVTI) Vol 6, No 1 (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.v6i1.361

Abstract

Using 3D printing in education research will continue to grow over the next few years, according to experts. It may be seen in a broad variety of scientific fields as well. An examination of 1,384 3D printing research articles published in 793 scientific journals and authored by 5,438 authors was conducted in this study (103 single-authored documents and 5,335 multi-authored documents). The goal of this study is to identify the trending topic in 3D printing right now. R software's Bibliometrix tool was used to extract data from Scopus and run it via VOSviewer, which was then loaded into the database. We've chosen the world's most significant publications, journals, authors, nations, and affiliations based on citation analysis criteria. While keywords and phrases are likely to be the most important issues and conclusions of the research, it is probable that some major patterns and concerns contained in the complete text are not properly reflected in our study. The development of patterns in 3D Printing should be examined in future studies to give scientific knowledge, as well.
Penerapan Trilaterasi dan Underdetermined Linear System dalam Penentuan Posisi Objek di Bumi Melalui Global Positioning System (GPS) Jufra, Jufra; Pimpi, La; Jufra, Arlita Aristianingsih; Alfian, Alfian; Arifin, Samsul; Murnaka, Nerru Pranuta
Teorema: Teori dan Riset Matematika Vol 9, No 2 (2024): September
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/teorema.v9i2.14112

Abstract

Materi yang digunakan dalam penelitian ini adalah konsep matriks dan aljabar vektor yang dapat membantu dalam menyelesaikan sistem persamaan linear yang terbentuk dari perhitungan jarak antara satelit dan receiver di bumi. Jarak ini adalah panjang vektor. Penyelesaian sistem persamaan linier ini berupa titik yang menunjukkan letak benda di muka bumi. Materi selanjutnya adalah tentang cara kerja Global Positioning System (GPS). Alat yang digunakan dalam penelitian ini adalah fasilitas yang dimiliki oleh Departemen Laboratorium Komputasi Matematika Universitas Halu Oleo berupa fasilitas komputer dan perangkat lunak. Berdasarkan hasil pembahasan dapat disimpulkan bahwa. Matriks aljabar dan vektor berperan penting dalam menentukan posisi suatu benda di bumi, khususnya pada GPS. Konsep yang digunakan adalah dengan menerapkan matriks dan vektor dari sistem persamaan linier yang diperoleh berdasarkan perhitungan jarak satelit ke benda bumi yang diterima penerima. Kata kunci: GPS; Matriks; Vektor; Aljabar.
Program Evaluation and Review Technique (PERT) Analysis to Predict Completion Time and Project Risk Using Discrete Event System Simulation Method Yudistira, I Gusti Agung Anom; Nariswari, Rinda; Arifin, Samsul; Abdillah, Abdul Azis; Prasetyo, Puguh Wahyu; Susyanto, Nanang
CommIT (Communication and Information Technology) Journal Vol. 18 No. 1 (2024): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v18i1.8495

Abstract

The prediction of project completion time, which is important in project management, is only based on an estimate of three numbers, namely the fastest, slowest, and presumably time. The common practice of applying normal distribution through Monte Carlo simulation in Program Evaluation and Review Technique (PERT) research often fails to accurately represent project activity durations, leading to potentially biased project completion prediction. Based on these problems, a different method is proposed, namely, Discrete Event Simulation (DES). The research aims to evaluate the effectiveness of the simmer package in R in conducting PERT analysis. Specifically, there are three objectives in the research: 1) develop a simulation model to predict how long a project will take and find the critical path, 2) create an R script to simulate discrete events on a PERT network, and 3) explore the simulation output using the simmer package in the form of summary statistics and estimation of project risk. Then, a library research with a descriptive and exploratory method is used for data collection. The hypothetical network is used to obtain the numerical results, which provide the predicted value of the project completion, the critical path, and the risk level. Simulation, including 100 replications, results in a predicted project completion time and a standard deviation of 20.7 and 2.2 weeks, respectively. The DES method has been proven highly effective in predicting the completion time of a project described by the PERT network. In addition, it offers increased flexibility.
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.