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All Journal Jurnal Penelitian Pendidikan IPA (JPPIPA) Indonesian Journal of Classroom Action Research (IJCAR) Time in Physics: Journal for Theoretical, Instrumentation, Material-Molecular, and Education Physics
Permana, Roni
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Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Physics Social Sciences

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Development of Flipbook-Based Thematic Learning to Improve Elementary School Students Learning Outcomes Dzakiyah, Muniroh; Shidiq, Galih Albarra; Permana, Roni
IJCAR: Indonesian Journal of Classroom Action Research Vol. 1 No. 1 (2023): Indonesian Journal of Classroom Action Research-Available Online in July 2023
Publisher : DAS Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53866/ijcar.v1i1.300

Abstract

Education is a means to lead to the growth and development of the nation. Flipbook-based thematic learning is an effort made so that students can improve learning outcomes. This study aims to examine and explore the application of flipbook teaching materials in thematic learning to improve learning outcomes. The method used in this research is a systematic literature study and in accordance with the discussion, namely thematic learning, flipbooks, and learning outcomes. Based on the results of a systematic review of the literature, flipbook-based thematic learning can be used as an alternative by teachers to improve student learning outcomes. However, the findings indicated that flipbook-based thematic learning can improve learning outcomes of elementary students through a positive impact on thematic learning in the elementary school students. Therefore, it is important to explore more detail on the efficient in delivering material and easy to understand and increase student interest in thematic learning. 
Implementation of Adaptive Neural Fuzzy Inference Systems (Anfis) For Speech Recognition Applications In Smart Home Control Permana, Roni; Sanjaya, W S Mada; Aliah, Hasniah
TIME in Physics Vol. 2 No. 2 (2024): September
Publisher : Universitas Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/timeinphys.2024.v2i2p77-84

Abstract

Signal Processing is signal processing that is related to the presentation, transformation, and manipulation of signal content and information. Digital Signal Processing is signal processing that is related to the presentation, transformation, and manipulation of signal content and information in digital form. The speech control system is very efficient. Speech signals are signals that change over time at a relatively slow speed. If observed at short intervals (between 5 and 100 miles per second), the practical characteristics are constant, but if observed at longer intervals, the characteristics appear to change according to the sentences spoken. This study uses the signal pattern recognition method with the MFCC and ANFIS methods as learning. The performance results of the entire system obtained an accuracy value with 6 feature extractions in 2 respondents, namely 65% ​​-72.5% and the smarthome control system worked well.
Utilization of Pineapple as Essential Oil for Respiratory Disorders: Case Study Permana, Roni; Afiyatusyifa, Fidya; Dewi, Riska Yuliana
TIME in Physics Vol. 3 No. 1 (2025): March
Publisher : Universitas Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/timeinphys.2025.v3i1p15-19

Abstract

This study aims to examine the effectiveness of pineapple (Ananas comosus) Essential oil in alleviating mild respiratory disorders such as cough and shortness of breath. A quasi-experimental method was used, involving two groups: an experimental group receiving therapy with pineapple Essential oil and a control group receiving warm water without oil. The results showed a significant reduction in respiratory symptoms in the experimental group (p < 0.01), while no significant change was observed in the control group. The bromelain content and volatile compounds in pineapple play a role in reducing inflammation and helping to open the airways. These findings indicate that pineapple Essential oil has potential as a natural alternative therapy for mild respiratory problems.
Thermal Image-Based Classification of Okra Maturity: A Comparative Study of CNN, SVM, and LSTM Sumardi, Tedi; Robiyana, Iqbal; Permana, Roni; Suhendra, Muhamad Agung
Jurnal Penelitian Pendidikan IPA Vol 11 No 11 (2025): November: In Progress
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i11.12748

Abstract

Post-harvest quality assessment remains a major challenge in agriculture, particularly for okra (Abelmoschus esculentus), which deteriorates rapidly due to high moisture content. Traditional grading based on manual inspection often results in inconsistency and product damage. This study explores thermal imaging as a non-destructive alternative for okra maturity classification. A dataset of 501 thermal images was acquired under controlled conditions and analyzed using three machine learning models: Convolutional Neural Network (CNN), Support Vector Machine (SVM) with Histogram of Oriented Gradients (HOG) features, and Long Short-Term Memory (LSTM) network. Experimental results show that CNN achieved the highest accuracy (99.01%), outperforming SVM (95.05%) and LSTM (91.09%). Confusion matrix and ROC analyses confirmed CNN’s superiority in capturing spatial thermal patterns related to maturity stages. Compared with RGB or hyperspectral imaging reported in prior studies, thermal imaging integrated with AI provides a more robust, illumination-independent, and non-destructive solution. The findings demonstrate the potential of CNN-based thermal imaging systems for automated sorting of okra in agricultural supply chains. Future work will focus on larger datasets, multi-class maturity levels, and real-time implementation to enhance practical deployment in post-harvest management.
Co-Authors afiyatusyifa, Fidya Dewi, Riska Yuliana Dzakiyah, Muniroh Hasniah Aliah Iqbal Robiyana Muhamad Agung Suhendra Sanjaya, W S Mada Shidiq, Galih Albarra Tedi Sumardi