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All Journal Journal of Aceh Physics Society Jurnal Penelitian Pendidikan IPA (JPPIPA) JURNAL PENDIDIKAN TAMBUSAI Research on Instrumentation
Leni Aziyus Fitri
Department of Physics, Universitas Negeri Padang, Padang, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Materials Science & Nanotechnology Physics Social Sciences

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Application of uCT-scan and infrared spectroscopy for determination of urinary stone components Vepy Asyana; Leni Aziyus Fitri; Freddy Haryanto; Taufik Ridwan; Nanda Fitri Ayu Muningrat
Journal of Aceh Physics Society Volume 10, Number 4, October 2021
Publisher : PSI-Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jacps.v10i4.19114

Abstract

Abstrak. Batu kemih merupakan salah satu penyakit dengan tingkat prevalensi yang cukup tinggi di Indonesia. Pengetahuan komposisi pada kandungan batu kemih dapat membantu tenaga medis dalam melakukan justifikasi penanganan tindakan lanjut pada pasien dengan tepat.Tujuan penelitian iniadalah menentukan kandungan mineral yang terdapat pada batu kemih menggunakan metode analisa spektrum inframerah dan nilai hounsfield unit (HU) yang terdapat pada citra yang dihasilkan dari modality mCT-Scan. Hasil karakterisasi fourier transform infrared spectroscopy (FTIR) memperlihatkan kandungan mineral batu kemih terdiri dari batu kemih calcium oxlate monohydrate, uric acid, batu campuran calcium oxalate dengan phosphate dan batu campuran cystine dengan phosphate sedangkan hasil dari scanning mCT memperlihatkan adanya kandungan mineral batu kemih campuran seperti batu campuran calcium oxalate dan cystine, batu campuran calcium oxalate, struvite, dan cystine, dan batu campuran calciumoxalate dan uric acid.Dari hasil penelitian ini dapat disimpulkan bahwa kedua modaliti tersebut mampu memperlihatkan kandungan mineral batu kemih dengan baik. Hal ini terlihat adanya spektrum serapan karakteristik dari FTIR setiap sampel berbeda-beda dan dari hasil citra mCT-Scan memperlihatkan nilai HU yang bervariasi sehingga mengindikasikan kandungan mineral pada sampel batu kemih yang diamati juga memiliki jenis yang berbeda-beda. Abstract. Urinary stones are a disease with a high prevalence rate in Indonesia. Knowledge of the composition of the urinary stone is an essential part to determine suitable treatments for patients. The aim of this research is to determine the mineral contained in urinary stones using the infrared spectrum and the value of HU (hounsfield unit) from the image mCT-Scan. The results of FTIR characterization showed that the mineral content of urinary stones consisted of calcium oxlate monohydrate, uric acid, calcium oxalate and phosphate mixed stones and cystine-phosphate mixed stones. mCT-Scan results showed the mineral content of urinary stones such as calcium oxalate and cystine mixed stone, calcium oxalate, struvite, and cystine mixed stones, and calcium oxalate and uric acid mixed stones. This show that the two modalities are be able to determine the mineral content of urinary stones. It can be seen that the characteristic absorption spectrum of the FTIR for each sample is different and from the mCT-Scan image results, the HU value varies so that it indicates the mineral content of the observed urine stone sample are different.
Analysis of Image Fusion Effect in Image Quality of Kidney Stone Fadhila Ulfa Jhora; Freddy Haryanto; Leni Aziyus Fitri; Fourier Dzar Eljabbar Latief
Jurnal Penelitian Pendidikan IPA Vol 8 No 4 (2022): October
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v8i4.2208

Abstract

Kidney stones are a disease due to the buildup of substances that are not needed in the urinary system. Knowledge of the composition and type of stone is required in the treatment of action. Micro CT is one of the modalities that can be used in determining the composition of kidney stones. However, there are limitations when using single-energy micro-CT. Stone attenuation has almost the same value when using single energy, therefore it is necessary to use dual-energy CT to determine the difference in stone attenuation more precisely. The image of the dual-energy CT micro-energy stone needs to be processed before analyzing and determining the rock composition. Image fusion is one of the image processing techniques that can be used. The purpose of this study was to determine the effect of image fusion on the image quality of five kidney stones. The stages in the research carried out are collecting high energy and low energy projection image data, and performing image fusion on the two projected image data. The results obtained are first, the dual-energy CT image fusion affects the image quality which can be seen from the increase in the signal to noise ratio (SNR) value. A high SNR value provides the best image quality information
Analisis Kebutuhan Pengembangan Bahan Ajar Berbasis TIK Konsep Kalor Terintegrasi Joyfull Learning untuk Meningkatkan Keterampilan Berfikir Kreatif dan Komunikasi Siswa Putri, Zikra Mulyadi; Asrizal, Asrizal; Amir, Harman; Fitri, Leni Aziyus
Jurnal Pendidikan Tambusai Vol. 9 No. 3 (2025): Desember
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Siswa harus mempelajari 4C berpikir kritis, berpikir kreatif, komunikasi, dan kolaborasi karena pendidikan abad ke-21 ditandai oleh globalisasi dan persaingan yang semakin ketat, yang berarti bahwa setiap orang harus mampu menghadapi berbagai tantangan kompleks agar dapat berhasil. Untuk meningkatkan kemampuan berpikir kreatif dan komunikasi siswa tentang konsep kalor di SMA Negeri 1 Lengayang, proyek ini bertujuan untuk menyediakan materi ajar berbasis teknologi informasi dan komunikasi (TIK) yang terhubung dengan strategi pembelajaran yang menyenangkan. Subjek penelitian deskriptif kuantitatif ini adalah guru dan siswa kelas sebelas. Dengan skor rata-rata masing-masing 48 dan 27, analisis kebutuhan menunjukkan bahwa siswa kesulitan memahami konsep kalor dan memiliki kemampuan komunikasi serta kreativitas yang buruk. Penelitian ini menyimpulkan bahwa integrasi pembelajaran yang menyenangkan ke dalam proses pembelajaran masih belum optimal dan bahan ajar yang digunakan belum memenuhi standar ideal. Oleh karena itu, untuk meningkatkan motivasi dan hasil belajar siswa, bahan ajar kreatif yang mudah dipahami dan menggabungkan strategi pembelajaran yang menyenangkan perlu dikembangkan. Studi ini menganjurkan adaptasi materi pengajaran agar lebih selaras dengan standar optimal dan menekankan peningkatan praktik pembelajaran yang menyenangkan untuk secara efektif mempersiapkan siswa menghadapi tantangan pendidikan abad ke-21.
MRI Image Classification of Brain Tumors Using VGG16-Based Transfer Learning and Data Augmentation as a Medical Diagnosis Support System Nadia Sri Aulia Noprianti Noprianti; Leni Aziyus Fitri
Jurnal Penelitian Pendidikan IPA Vol 12 No 1 (2026)
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i1.14218

Abstract

Brain tumors are diseases that require early detection and accurate diagnosis. Various studies have applied deep learning methods to classify MRI images of brain tumors, but they still face dataset limitations and imbalanced class distributions that impact model performance. This study aims to evaluate the performance of the transfer learning-based VGG16 model in classifying brain tumors using MRI images. The study used 7,023 MRI images, including glioma, meningioma, pituitary, and no tumor, with a balanced training data distribution. Pre-processing included resizing, data splitting, and augmentation in the form of rotation, width shift, height shift, and zoom to increase data diversity and reduce the impact of class imbalance. The model was trained using several training-validation data splits (70:30, 80:20, and 90:10) with variations of the Adam, RMSprop, and AdamW optimizers and learning rates between 0.1 and 0.0001. The best configuration was obtained in the 80:20 scenario with the Adam optimizer and a learning rate of 0.0001, which was used in the final testing stage using test data that were never used during training and validation. The results showed the highest validation accuracy of 99.89% and a testing accuracy of 98.00%. Confusion matrix analysis showed that all classes could be classified well without prediction bias.
A Smart Health Device to Measure Stress Levels Based on the Internet of Things Using the K-Nearest Neighbor Algorithm Tiara Ayunda; Asrizal; Leni Aziyus Fitri
Research on Instrumentation Vol. 3 No. 1 (2026): Research on Instrumentation
Publisher : RESSTECH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66926/rins.2026.1.32

Abstract

Mental health plays an important role in daily life. However, many factors can affect mental health, one of which is stress. Students are one group that is prone to stress. Academic stress is common among students. Currently, physiological stress screening devices are available, but most of them still work separately and are quite expensive. Therefore, this study aims to design an IoT-based stress detection device with a KNN algorithm that can measure physiological symptoms to detect stress levels in a practical and economical manner. This research is a type of engineering research, which involves the process of designing hardware and software for the system in an IoT-based stress level detection tool. The tool is designed to measure three physiological parameters, namely skin conductance, heart rate, and body temperature. Sensor data is processed using the KNN algorithm to classify stress levels into four categories, namely normal, mild, moderate, and severe. The results are displayed on an OLED and ThingSpeak platform so that they can be accessed remotely through IoT integration. Testing was carried out by collecting stress condition data from several subjects. The test results show that the device has an average accuracy and precision value of 83.33% to 99.82%. In addition, the average prediction computation time produced by the system was only 0.44 seconds, this computation time falls within an acceptable range for real-time applications. Thus, this stress level detection tool is expected to be an alternative solution and facilitate remote condition monitoring through the IoT feature.
Co-Authors Asrizal Asrizal Fadhila Ulfa Jhora Fourier Dzar Eljabbar Latief Freddy Haryanto Freddy Haryanto Harman Amir Nadia Sri Aulia Noprianti Noprianti Nanda Fitri Ayu Muningrat Putri, Zikra Mulyadi Taufik Ridwan Tiara Ayunda Vepy Asyana