Article Per Year (5 Year)
p-Index From 2021 - 2026
5.58
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Pengajaran MIPA TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmu Komputer (JIK) Indonesian Journal of Disability Studies Journal of Engineering and Technological Sciences ELINVO (Electronics, Informatics, and Vocational Education) Jurnal Penelitian dan Pembelajaran IPA Indonesian Journal of Science and Technology QUANTUM: Jurnal Inovasi Pendidikan Sains JOIV : International Journal on Informatics Visualization AL ISHLAH Jurnal Pendidikan Knowledge Engineering and Data Science Jurnal Penelitian Pendidikan IPA (JPPIPA) Momentum: Physics Education Journal MUST: Journal of Mathematics Education, Science and Technology Journal of Natural Science and Integration JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI THABIEA (JOURNAL OF NATURAL SCIENCE TEACHING) JURNAL PENDIDIKAN TAMBUSAI Journal of Education Technology Jurnal Tekno Insentif Jurnal Sains Dirgantara Education and Human Development Journal Jurnal Paedagogy Cendikia : Media Jurnal Ilmiah Pendidikan Journal Evaluation in Education (JEE) Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Digital Transformation Technology (Digitech) IJOEM: Indonesian Journal of Elearning and Multimedia Finger : Jurnal Ilmiah Teknologi Pendidikan Bulletin of Social Informatics Theory and Application Jurnal Guru Komputer Jurnal Pendidikan Teknologi Informasi dan Komunikasi Journal of Computers for Society
Lala Septem Riza
Universitas Pendidikan Indonesia, Bandung, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

Published : 59 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 59 Documents
Search

 2   3   4   5   6 
Predicting Solar Flares Using Data Products Vector Magnetic SDO/HMI dan Random Ferns Rooseno Rahman Dewanto; Lala Septem Riza; Judhistira Aria Utama
Journal of Computers for Society Vol 4, No 2 (2023): JCS: September 2023
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v4i2.71184

Abstract

Solar flares (SFs) are the most powerful bursts of energy in the solar system that often have a bad effect on space weather. Until now, the cause of its appearance is not known for sure. Nevertheless, SFs are known to have magnetic properties attached to them. Therefore, understanding the configuration of the magnetic field on the sun plays an important role in SFs prediction efforts. Using SFs flux data recorded by X-ray Sensors on the Geostationary Operational Environmental Satellite (GOES) which is mapped with 13 parameters of the magnetic vector data of the solar photosphere layer recorded by the Helioseismic and Magnetic Imager (HMI) at the Solar Dynamic Observatory (SDO) and the Machine Learning (ML) Random Ferns (RFe) algorithm,  This study tries to predict the emergence of multiclass SFs (B, C, M, and X) along with binary SFs (BC and MX). This study uses data from May 1, 2010 to May 10, 2020, with a total of 30 classes X, 443 classes M, 1032 classes C, 751 classes B, 473 classes MX, and 1783 classes BC. This study also applies the oversampling method to handle the imbalanced nature of the data on SFs data. Overall, it can be seen that predicting the occurrence of SFs using RFe is a valid effort. The highest average scores achieved by this study for sensitivity/recall, precision, and True Skill Statistics (TSS) in multiclass SFs were 74.4%, 50.3%, and 58.7%, respectively; and in binary SFs are 87.7%, 77.7%, and 72.8%.
Implementation of Internet of Things Using Electrocardiogram Sensors to Identify Atrial Fibrillation Heart Disease Muhammad Ramdan Pamungkas; Wawan Setiawan; Lala Septem Riza
Journal of Computers for Society Vol 4, No 1 (2023): JCS: June 2023
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v4i1.71177

Abstract

Atrial Fibrillation (AF) is one of the most common heart diseases and increases the risk of stroke and heart failure up to five times. The symptoms of AF are very diverse and often asymptomatic, so an immediate examination is needed to detect it. Given the dangers of AF that could lead to heart failure or death, a diagnosis that can record daily heart rhythms is urgently needed. Research trends show increased use of the Internet of Things (IoT) due to its efficiency and real-time monitoring capabilities. The purpose of this study is to utilize the IoT concept by designing a prototype AF detection device called Atrial Fibrillation Detector (AFD) using a ESP8266 microcontroller device and an AD8266 Electrocardiogram (ECG) sensor. The results of the study show that AFD can identify AF through 4 main stages, including the process of recording ECG data, the process of sending data from the AFD device to the server, the process of processing data to identify the appearance of AF and the process of sending notifications if there is an indication of the appearance of AF. To further test AFD, two experimental scenarios were applied; blackbox testing and comparison of the suitability of AF detection results. In the first experiment, AFD managed to pass the total number of scenarios that existed at 16 scenarios. In the second experiment, AFD only managed to identify exactly 9 out of 15 scenarios.
Natural Language Processing and Levenshtein Distance for Generating Error Identification Typed Questions on TOEFL Lala Septem Riza; Faisal Syaiful Anwar; Eka Fitrajaya Rahman; Cep Ubad Abdullah; Shah Nazir
Journal of Computers for Society Vol 1, No 1 (2020): JCS: June 2020
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v1i1.24940

Abstract

Test of English as a Foreign Language (TOEFL) is one of the evaluations requiring good quality of the questions so that they can reflect the English abilities of the test takers. However, it cannot be denied that making such questions with good quality is time consuming. In fact, the use of computer technology is able to reduce the time spent in making such questions. This study, therefore, develops a model to generate error identification typed questions automatically from news articles. Questions from the sentences on news sites are created by utilizing Natural Language Processing, Levenshtein Distance, and Heuristics. This model consists of several stages: (1) data collection; (2) preprocessing; (3) part of speech (POS) tagging; (4) POS similarity; (5) choosing question candidates based on ranking; (6) determining underline and heuristics; (7) determining a distractor. Testing ten different news articles from various websites, the system has produced some error identification typed questions. The main contributions of this study are that (i) it can be used as an alternative tool for generating error identification typed questions on TOEFL from news articles; (ii) it can generate many questions easily and automatically; and (iii) the question quality are maintained as historical questions of TOEFL.
Correlation Analysis of Open Street Map, Demography, and Vaccination on the Number of Covid-19 Cases Using Multiple Linear Regression and Pearson Correlation Product Moment Aqhbar Habib; Erna Piantari; Lala Septem Riza
Journal of Computers for Society Vol 5, No 2 (2024): JCS: September 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i2.70798

Abstract

At the beginning of 2020, the world was shocked by the spread of Coronavirus Disease 2019 (Covid-19). The resulting losses cover various areas. This research aims to analyze the correlation between spatial data, demographic data, and vaccination data on the spread of Covid-19 in Bandung City using Multiple Linear Regression (MLR) and Pearson Correlation Product Moment (Pearson's r). The results show that there are only 3 variables that are significantly correlated with Covid-19 cases. The lowest variables are Residential, Population Density, and Healthy Homes. Has a significant simultaneous correlation with Covid-19 cases with a coefficient of determination (R^2) of 0.55404. The model built also passed the 3 Classical Assumptions test so that the results can be trusted for their level of truth and feasibility. The results of experiments using the Pearson's r model involving 5 vaccination periods show that out of 30 sub-districts in Bandung City, there are 20 sub-districts that have a significant correlation between vaccination and the addition of Covid-19 cases and have a negative correlation direction of 80.54%. The results of the Pearson's r model experiment involving 6 vaccination periods show that there are 9 sub-districts that have a relationship. With a negative correlation direction of 72.93%.
Apache Spark Implementation on Algorithms Boyer-Moore Horspool for Case Studies Internal Transcribed Spacer and Restriction Enzyme Fidela Zhafirah; Topik Hidayat; Lala Septem Riza
Journal of Computers for Society Vol 5, No 1 (2024): JCS: June 2024
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/jcs.v5i1.70790

Abstract

The huge increase in the amount of data is a problem today. The increase in large amounts of data makes storage very large and processing data becomes very long. Meanwhile, the speed of the process is very necessary to streamline time. This research is dedicated to solving storage and process problems as a big data processing solution by creating a string matching computational model using the Boyer-Moore Horspool algorithm using the Big Data platform, Apache Spark where the Hadoop Distributed File System as data storage on the cluster. In this study, a comparison of string matching process time between stand-alone, the use of Apache Spark single nodes, the use of Apache Spark 3 nodes, 5 nodes, 11 nodes and 16 nodes using Hadoop Distributed File System storage on clusters on Google Cloud Platform. The case study used is bioinformatics by solving two problems in the field of biology, namely the search for motives related to determining the group of flowering plants with other plant groups and the search for motives as detection of begomovirous symptoms as the cause of curly leaf disease. In the results of the study, insignificant time was obtained because the data used could still be processed by classical programs so that the execution time was not much different. The accuracy of the program run on Apache Spark is 83.5%.
Analysis Of The Validity And Reliability Of A Critical Thinking Skills Instrument On The Topic Of Wave-Particle Duality Using Rasch Model Juandi, Tarpin; Kaniawati, Ida; Samsudin, Achmad; Riza, Lala Septem; Susilawati, Susilawati; Sapiruddin, Sapiruddin
QUANTUM: Jurnal Inovasi Pendidikan Sains Vol 15, No 2 (2024): Oktober 2024
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/quantum.v15i2.19996

Abstract

This study aims to analyse the validity and reliability of a critical thinking skills instrument on the topic of wave-particle dualism using the Rasch model. Data collection was carried out by administering a critical thinking skills test to students enrolled in a modern physics course. A total of 36 students from a university in West Nusa Tenggara participated. Data analysis was performed using the Rasch model through the Winsteps 4.6.1 software. The results indicated that the instrument is valid and reliable. The instrument's validity was tested by examining the data's fit to the Rasch model through infit and outfit MNSQ values and ZSTD, all of which were within the expected acceptance range. Construct validity was analysed through standardized residual variance, showing that the Rasch model can explain most of the variance in the data. Similarly, the instrument's reliability showed that the item reliability was in the very good category (0.93) and the person reliability was in the moderate category (0.68), with a Cronbach's alpha value of 0.86, indicating very good internal reliability. These findings confirm that the Rasch model is effective in assessing and improving the quality of critical thinking skills evaluation instruments in the context of modern physics education.
Utilizing Learning Media In Biology: A Step Towards Interactive Media Development Putri, Iffa Ichwani; Rahmat, Adi; Riandi, Riandi; Riza, Lala Septem
Journal of Natural Science and Integration Vol 7, No 2 (2024): Journal of Natural Science and Integration
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jnsi.v7i2.29493

Abstract

The study addresses the complexities inherent in teaching and learning biology, a subject that is often challenging for students due to its intricate concepts. Focusing on the intersection of pedagogy and technology, this research evaluates the perceptions of high school teachers and students towards the integration of contemporary learning media in biology instruction. Utilizing a descriptive and quantitative approach, the research engaged a purposively sampled cohort of educators and learners to explore their views. this study involved 56 teachers and 133 students spread across several schools. Data were gleaned through a combination of structured questionnaires and interviews, subsequently subjected to quantitative analysis. The findings reveal a consensus on the critical role of media in facilitating biology education. Teachers and students agree that technology-based media can improve understanding of biological concepts and strengthen student engagement. While there is a significant reliance on media to convey biological concepts, the findings indicate that the potential of technology-based media. However, the study uncovers a lag in the effective deployment of technological resources, with interactive multimedia being underutilized by a notable fraction of educators. This gap underscores the need for enhanced strategies to foster the adoption of technology-enhanced learning tools in the biological sciences.Keywords: interactive, multimedia, science, technology
Comparison of Machine Learning Algorithms for Species Family Classification using DNA Barcode Riza, Lala Septem; Rahman, M Ammar Fadhlur; Prasetyo, Yudi; Zain, Muhammad Iqbal; Siregar, Herbert; Hidayat, Topik; Samah, Khyrina Airin Fariza Abu; Rosyda, Miftahurrahma
Knowledge Engineering and Data Science Vol 6, No 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um018v6i22023p231-248

Abstract

Classifying plant species within the Liliaceae and Amaryllidaceae families presents inherent challenges due to the complex genetic diversity and overlapping morphological traits among species. This study explores the difficulties in accurate classification by comparing 11 supervised learning algorithms applied to DNA barcode data, aiming to enhance the precision of species family classification in these taxonomically intricate plant families. The ribulose-1,5-bisphosphate carboxylase-oxygenase large sub-unit (rbcL) gene, selected as a DNA barcode locus for plants, is used to represent species within the Amaryllidaceae and Liliaceae families. The experimental results demonstrate that nearly all tested models achieve accurate species classification into the appropriate families, with an accuracy rate exceeding 97%, except for the Naïve Bayes model. Regarding computational time, the Random Forest model requires significantly more time for training than other models. Regarding memory usage, the Least Squares Support Vector Machine with a polynomial kernel, and Regularized Logistic Regression consume more memory than other models. These machine learning models exhibit strong concordance with NCBI's classifications when predicting families using the test dataset, effectively categorizing species into the Amaryllidaceae and Liliaceae families.
The Implementation of Project-Based Learning (PBL) with ADDIE Model to Improve Students' Creative Thinking Ability Wahyudin, Wahyudin; Qobus, Muhammad Shofwan; Fatimah, Nusuki Syariati; Riza, Lala Septem; Adedokun-Shittu, Nafisat Afolake
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 9 No. 2 (2024): November 2024
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/elinvo.v9i2.77240

Abstract

Creative thinking ability is one of the thinking concepts used to find ideas that people are starting to be interested in. Creative thinking can be used as a relevant tool in building innovation and as a method for building innovation models, one of which is a learning model. The project-based learning model is a solution that influences students' activeness and creativity in learning. The purpose of this research is to apply a project-based learning model that is expected to improve students' creative thinking abilities on creative product and entrepreneurship subjects on the Internet of Things material. The development model used in this research is ADDIE (Analyze, Design, Development, Implementation, Evaluation) with a One Group Pretest-Posttest research design. Based on the research results, there are several conclusions, including the following: 1) Students' creative thinking abilities by implementing the project-based learning model can be seen from the average pretest score of 38.24 and the average posttest score of 70.15. 2) The normalized gain test results obtained a mean of 0.517 with the "Medium" criteria, which means there is a difference in creative thinking abilities after the treatment process. There are four aspects given when giving the TAM questionnaire to students, namely the user's perception of usefulness with a percentage of 86.67%, the user's perception of ease of use with a percentage of 84.71%, attitude towards use with a percentage of 83.53 and attention. With a percentage of 86.27%, and the average obtained for the four aspects was 85.29% in the "Very Good" category.
Evaluating Research Trends and Gaps in Disaster Literacy within Science Education: A Bibliometric Perspective Prasetyaningsih, Prasetyaningsih; Kaniawati, Ida; Riza, Lala Septem; Utama, Judhistira Aria
Journal Evaluation in Education (JEE) Vol 6 No 1 (2025): January
Publisher : Cahaya Ilmu Cendekia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37251/jee.v6i1.1248

Abstract

Purpose of the study: This study aims to evaluate research trends, gaps, and global patterns in disaster literacy within science education to identify areas for improvement and provide actionable recommendations for enhancing education strategies in disaster-prone regions. Methodology: A bibliometric analysis was conducted using data from the Scopus database (2000-2024). Tools used include R Studio with the Bibliometrix package for generating visualizations such as co-occurrence networks, word clouds, and trend analyses. The dataset comprises 315 articles selected using “disaster literacy” and "science education". Main Findings: Findings indicate an increasing focus on disaster literacy research, with eminent themes such as technology integration and project-based learning. However, significant gaps remain in contributions from developing nations and the long-term evaluation of disaster literacy programs. Collaborative international research has been identified as a growing trend. Novelty/Originality of this study: This study uniquely combines bibliometric analysis with an evaluative approach to highlight disparities in disaster literacy research and propose strategies for improving curriculum integration and global collaboration. It advances understanding by identifying underexplored areas and providing a foundation for targeted educational interventions.
Co-Authors Abdullah, Cep Ubad Abu Samah, Khyrina Airin Fariza Achmad Samsudin Ade Gafar Abdullah, Ade Gafar Ade Rohayati Ade Sobandi, Ade Adedokun-Shittu, Nafisat Afolake Adi Rahmat Ahmad Zainal Abidin Akbar, Anthonio Al Husaeni, Dwi Fitria Al Husaeni, Dwi Novia Aldi Zainafif Alejandro Rosales Pérez Alejandro Rosales-Pérez Alfitri, Latifahny Aridia Alivia, Zsalzsa Puspa Amay Suherman Amirah Misdan, Nur Farhanah Anisyah, Ani anne Hafina, anne Aqhbar Habib Arianti, Andini Setya Asep Bayu Dani Nandiyanto Asep Wahyudin Atqiya, Muhammad Azka AZ Pranata Budiana, Dian Budiman Budiman Cep Ubad Abdullah Dadang Lukman Hakim Destian, Rangga Dewini Dewini Didin Wahyudin, Didin Edy Soewono Edy Soewono Eka Fitrajaya Rahman Eki Nugraha Eliyawati Eliyawati Enjang Ali Nurdin Erlangga, E. Erna Piantari Faisal Syaiful Anwar Farhan Dhiyaa Pratama Fathimah, Nusuki Syari'ati Fatimah, Nusuki Syariati Ferry Mukharradi Simatupang Fidela Zhafirah Gerraldi, Alief Gintara, Andre Rangga Gunarso Hamzah, Raseeda Hasanah , Lilik Nur Hasrol Jono, Mohd Nor Hajar Hayati , Nurlaila Herbert Siregar Homdijah, Oom Siti Huda, Kirana Syafa Husni Firmansyah Ida Kaniawati ISKANDAR, AYSHA ALIA Isma Widiaty Jaja Kustija, Jaja Judhistira Aria Utama Junaeti, Enjun Kafilli, Muhammad Fikri Kenny David Kenny David Khyrina Airin Fariza Abu Samah Kuntjoro Adji Sidarto Kuntjoro Adji Sidarto Liliasari M. FURQON Mahmoud Fahsi Mediayani, Melani Mohd Nor Hajar Hasrol Jono Muhammad Afif Auliya Muhammad Aziz Muhammad Bahrul Ulum Muhammad Hazmi Zuhdi Muhammad Irfan Firmansyah Muhammad Ramdan Pamungkas Muhammad Syafri Syamsudin Mumu Komaro Munir Munir, Munir N. Nurjanah Nanang Dwi Ardi Naufal Rabah Wahidin Nazir, Shah Nor Aiza Moketar Novi Sofia Fitriasari Nur Maisarah Nor Azharludin Nuraulia, Anti Nurhayati, Ai Siti Nurqueen Sayang Dinnie Wirakarnain Nursalman, Muhammad Nusratullo, Samialloi Olyan, Warzuqni Parlindungan Sinaga Pérez, Alejandro Rosales Pertiwi, Anita Dyah Piantari, Erna Prabawa, Harsa Wara Prasetyaningsih Prasetyaningsih, Prasetyaningsih Prasetyaningsih, Prasetyaningsih Pudjo Sukarno Pudjo Sukarno Putri , Ananda Hafizhah Putri , Liandha Arieska Putri Amelia Solihah Putri, Iffa Ichwani Qobus, Muhammad Shofwan Rahman, M Ammar Fadhlur Rambari Apandi, Anjar Rani Megasari Raseeda Hamzah Rasim, Rasim Rena Zaen Rendi Adistya Rosdiyana Riandi Riandi Riezqa Andika Rika Rafikah Agustin Rizky Rachman Judie Rooseno Rahman Dewanto Rosa, Elisa Rosi Oktiani Rosyda, Miftahurrahma Safitri, Fibriyana Sahidin, M. Zaenal Iskandar Samah, Khyrina Airin Fariza Abu Sapiruddin, Sapiruddin Selvi Marcellia Shah Nazir Shah Nazir Siregar, Herbert Solihat, Syifa Sonjaya, Rebina Putri Sugeng Rifqi Mubaroq Suratno Susilawati, Susilawati Tarpin Juandi Taufiq Hidayat Topik Hidayat Tutuka Ariadji Tyas Farrah Dhiba Wahyudin Wahyudin - Wahyudin Wahyudin Sanusi Rosada Wahyudin Wahyudin Wahyudin, W. Wawan Setiawan Wibisono, Yudi Wihardi, Yaya Yudi Prasetyo Zain, Muhammad Iqbal Zainab Othman