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Ainayya Halifah
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Physics

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Deteksi Fitur Wajah pada Hasil Usg 3D Janin dengan Algoritma Viola-Jones Hikmatul Wilda; Kholifah, Nurul; Desy Fitri Wulandari; Ainayya Halifah
Journal of Electronics and Instrumentation Vol. 1 No. 2 (2024)
Publisher : Fakultas MIPA, Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jei.v1i2.703

Abstract

Ultrasound (Ultrasonography) is a medical imaging technology used for monitoring fetal development during pregnancy. It produces visual images that support the process of medical diagnosis and pregnancy monitoring. Image processing is used to process and analyze digital images, providing valuable additional information. One of the methods used in image processing is the Viola-Jones algorithm. The Viola-Jones algorithm is commonly used to detect objects in image processing and computer vision, especially human faces. Face detection using the Viola-Jones algorithm can be implemented using software such as Matlab and Python. However, in this experiment, there were difficulties in using the Viola-Jones algorithm to detect baby ultrasound images. This is caused by the position seen from the side in the baby's ultrasound image and the uniformity of color throughout the face. In fact, some features such as eyebrows and eyes are difficult to recognize clearly. In addition, the resulting training files may not provide consistent results on other samples due to complex variations in infant ultrasound images.
Model Regresi untuk Estimasi Suhu Oral Berdasarkan Pengukuran Suhu Dahi Menggunakan Thermogun Fahreza, Rafi Achmad; Zainatul Khasanah; Atika Azizah; Risqillah Ayu Puspita; Ainayya Halifah
Journal of Electronics and Instrumentation Vol. 1 No. 3 (2024)
Publisher : Fakultas MIPA, Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jei.v1i3.689

Abstract

Semenjak pandemi Covid-19, terjadi revolusi di dalam dunia medis mengenai cara pengukuran suhu tubuh asli manusia. Suhu tubuh asli manusia sebelumnya banyak diukur menggunakan termometer digital yang diletakkan di ketiak. Namun, sejak terjadinya pandemi Covid-19 dokter dan tenaga medis dituntut untuk dapat melakukan pengukuran suhu tubuh secara lebih cepat dan dengan metode tanpa kontak dengan anggota tubuh. Hal tersebut membuat banyak dokter dan tenaga medis menggunakan thermogun yang dapat mengukur suhu tubuh manusia dengan cepat dan tanpa menyentuh anggota tubuh. Namun, permasalahan mengenai ketidakakuratan thermogun dan titik pengukuran di dahi membuat hasil pembacaan suhu tidak sesuai dengan suhu asli tubuh sebenarnya. Selain itu, pengukuran suhu tubuh menggunakan thermogun memiliki banyak faktor yang dapat mempengaruhi hasil yang didapatkan baik faktor internal maupun eksternal. Penelitian ini berfokus pada faktor internal yaitu titik pengukuran suhu. Tujuan dari penelitian ini yaitu untuk mengatasi ketidakakuratan pengukuran suhu tubuh dengan cara memberikan prediksi suhu oral (titik yang dapat merepresentasikan suhu tubuh sebenarnya) berdasarkan pengukuran suhu di dahi (titik paling efisien untuk pengukuran). Metode analisis data yang digunakan yaitu regresi linear sederhana di mana suhu dahi akan menjadi prediktor dan dapat memprediksi suhu oral yang menjadi respons. Analisis mengenai hubungan antara variabel dengan mencari nilai muliple R, koefisien determinasi, dan standart error of estimate (SEE). Setelah dilakukan analisis regresi, dilanjutkan dengan uji F menggunakan analisist of variable (Anova). Hasil persamaan garis regresi linear yang didapatkan yaitu , dengan . Hal tersebut membuat suhu dahi memiliki kesesuaian dengan suhu oral sebesar .
Klasifikasi Tangisan Bayi Menggunakan Parameter Pitch Dengan K-Nearest Neighbors Ainayya Halifah; Agung Tjahjo Nugroho; Wenny Maulina
Journal of Electronics and Instrumentation Vol. 1 No. 2 (2024)
Publisher : Fakultas MIPA, Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jei.v1i2.880

Abstract

Baby crying is a basic and important thing for mothers or caregivers to understand. In general, young mothers who do not receive guidance from experienced people, usually interpret baby crying as a sign of hunger only, even though crying in babies has different meanings or types of crying depending on the trigger/cause of crying. This study was conducted to establish the characteristics of the cause of infant crying through pitch parameters formed in the Bag of Features and determine the accuracy of the resulting classification. The feature extraction and classification methods used in this research are pitch, Bag of Features and K-Nearest Neighbor. Pitch feature extraction is done by changing the range parameters and methods in estimating the fundamental frequency. The range and method used in this research are (70,170) and PEF. The baby cries used for this study were taken in two ways, namely downloading Dunstan Baby Language and field measurements based on the perception of mothers and medical personnel. The types of infant cries used in this study were burpme, hungry, lower wind pain, tired, uncomfortable and pain. The results of this study show that the sequence of DBL baby cry labels that have a high average fundamental frequency probability value based on the Bag of Features histogram are tired (0.290), lower wind pain (0.207), hungry (0.206), burpme (0.182) and uncomfortable (0.090) while the sequence of baby cry labels from measurement data shows that the sick label has a higher average fundamental frequency, which is 0.200 when compared to the hungry label whose average fundamental frequency is 0.064. The classification accuracy results obtained between the DBL database test and the measurement database using K-Nearest Neighbor look optimal, which is 92% and 98%.
Co-Authors Agung Tjahjo Nugroho Atika Azizah Desy Fitri Wulandari Fahreza, Rafi Achmad Hikmatul Wilda Nurul Kholifah, Nurul Risqillah Ayu Puspita Wenny Maulina Zainatul Khasanah