Claim Missing Document
Check
Articles

Found 30 Documents
Search

Analisis Kadar Aseton pada Gas Buang Pernafasan Penderita Diabetes Mellitus dan Normal Menggunakan Sensor MQ-135 Nuryani, Siska; Maesyaroh, Uhty; Sumarti, Heni
Jurnal Fisika Vol 11, No 2 (2021)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v11i2.32249

Abstract

Diabetes Mellitus merupakan salah satu penyakit utama yang menimbulkan ancaman terhadap kesehatan manusia dan telah menjadi epidemik secara universal. Kadar aseton pada penderita Diabetes Mellitus sangat tinggi jika dibandingkan dengan orang tanpa indikasi Diabetes Mellitus. Penelitian ini bertujuan untuk menganalis kadar aseton dalam gas buang pernafasan penderita Diabetes Mellitus dan normal menggunakan sensor MQ-135. Metode penelitian yang dilakukan meliputi perancangan alat, pembuatan alat, kalibrasi, uji coba alat dan analisis. Subjek penelitian terdiri dari 6 responden tanpa indikasi Diabetes Mellitus dan 6 responden dengan indikasi Diabetes Mellitus. Akurasi alat pada responden tanpa indikasi Diabetes Mellitus sebesar 88,01% dan pada responden dengan indikasi Diabetes Mellitus sebesar 95,35%. Alat ini layak digunakan sebagai alat deteksi kadar gula darah mandiri bagi pasien dengan indikasi Diabetes Mellitus. Sesuai dengan dengan ketentuan BPFK (Balai Pengamanan Fasilitas Kesehatan) bahwa batas ambang nilai error yang diizinkan yaitu 5%.
Development of Non- Invasive Cholesterol Monitoring System Using TCRT5000 Sensor with Android Compatibilty Rahmawati, Tika; Tasyakuranti, Alvania Nabila; Sumarti, Heni; Kusuma, Hamdan Hadi
Jurnal Fisika Vol 13, No 2 (2023)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v13i2.45044

Abstract

High cholesterol levels cause several diseases, such as atherosclerosis (narrowing of the arteries), coronary heart disease, high blood pressure, obesity, thyroid disorders, diabetes mellitus, liver disease, and kidney disease. Generally, such checking is carried out invasively in clinical laboratories or hospitals. The checking can be done individually at a lower cost by using non invasive cholesterol measuring devices. This study aims to design and implement an android-based non-invasive cholesterol monitoring device using the TCRT5000 sensor. The tool developed was tested to measure cholesterol levels in 15 respondents aged 20-30 years. The research procedure consisted of several stages, starting with the design stage of the tool, which was carried out by assembling the components; the second stage was the tool coefficient of determination test, the third stage was the accuracy test, and the last stage was the data transfer speed test. The average accuracy of the tool is 83.18%, and the avarage of delay is 8.8 ms. This tool has considerable potential to be used in a telemedicine system that can be accessed remotely regularly to determine the estimated value of cholesterol levels in the blood.
Identification of COVID-19 Based on Features Texture Histogram and Gray Level Co-Occurrence Matrix (GLCM) Using K-Means Clustering Methods in Chest X-Ray Digital Images Sumarti, Heni; Sabrina, Qolby; Triana, Devi; Septiani, Fahira; Rahmani, Tara Puri Ducha
Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Vol. 13 No. 1 (2023)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jpfa.v13n1.p51-66

Abstract

Since the last five years of the COVID-19 outbreak, radiological images, such as CT-Scan and Chest X-Ray (CXR), have become essential in diagnosing this disease. However, limited access to facilities such as CT-Scanners and RT-PCR makes CXR images the primary method for COVID-19 testing. This research aims to improve the accuracy of CXR images in identifying COVID-19 patients based on the texture features: histogram and Gray Level Co-occurrence Matrix (GLCM), using the K-Means Clustering method. This study utilized 150 CXR images, including 75 COVID-19 patients confirmed by RT-PCR tests, and 75 patients with negative cases. The method used were consisted of pre-processing, and texture feature extraction with the seven most influential attributes based on gained information (histogram: standard deviation, entropy, skewness, kurtosis, and GLCM: correlation, energy, homogeneity), as well as classification using K-Means clustering methods. The results showed that the classification’s accuracy, sensitivity, and specification are 92%, 91%, and 93%, respectively. This image processing technique is a promising as well as a complementary tool in diagnosing COVID-19 cases, based on CXR images with lower costs and more reliable results.
Alpha Wave Activity on Think Hard and Dhikr Condition Using Electroencephalographic (EEG) Huwaidah, Indah Rifdah; Kholidah, Kholidah; Sumarti, Heni
Physics Education Research Journal Vol 6, No 1 (2024)
Publisher : Faculty of Science and Education, UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/perj.2024.6.1.15200

Abstract

Emotions are very important in thinking, making decisions, and a person's personality. This research was conducted to know the activity of alpha waves using an electroencephalographic (EEG) instrument, using an experimental method given the treatment of thinking hard and dhikr of istighfar. The brain waves analyzed in this study are alpha waves with a frequency between 8-12 Hz. The analysis shows that the alpha wave mean result is 11.89 Hz when thinking hard, and the mean result is 10.89 Hz during dhikr. The statistical test results show a significance of p = 0.000323 (p 0.05), showing that dhikr can volunteer from a state of hard thinking to a relaxed state. The istighfar dhikr (astaghfirullah hal adzim) by the volunteer is a response to ask for forgiveness and reassure the heart.
Effect of Molarity on Double Layer Photocatalytic Activity ZnO/ZnO:Ag for Metanil Yellow Degradation Anggita, Sheilla Rully; Kusuma, Hamdan Hadi; Sumarti, Heni; Teke, Sosiawati
Physics Education Research Journal Vol 5, No 1 (2023)
Publisher : Faculty of Science and Education, UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/perj.2023.5.1.13301

Abstract

Double layer (DL) ZnO/ZnO:Ag has been synthesized with variations in molarity of 0.1, 0.3, 0.5,  and 0.7 M and its application as a degrading agent for methanil yellow dye. This study aims to determine the effect of the molarity of the DL ZnO/ZnO:Ag on crystallinity and photocatalytic activity for methanil yellow degradation. DL ZnO/ZnO:Ag was synthesized using sol-gel technique and deposited with spray coating technique. The results of DL ZnO/ZnO:Ag were characterized by XRD to determine the crystallinity and particle size. The photocatalytic activity was carried out by immersing the DL ZnO/ZnO:Ag layer in 10 ppm methanil yellow solution and irradiating it with UV light for 4 hours and then tested using UV-Vis spectroscopy to get the percentage of methanil yellow degradation. The results showed that the crystallinity of the DL ZnO/ZnO:Ag for all molarity variations had a hexagonal wurtzite structure. Grains size increase as molarity increases from 0.1 to 0.5 M. However, if the concentration continues to be increased to 0.7M, the grain size decreases. Photocatalytic activity is increasing every hour, as indicated by the increasing percentage of degradation. Precursor in 0.5 M has the maximum percentage of degradation is 25.32%.
EEG Classification while Listening to Murottal Al-Quran and Classical Music using Random Forest Method Sumarti, Heni; Septiani, Fahira; Sudarmanto, Agus; Caesarendra, Wahyu; Edison, Rizki Edmi
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/um018v6i22023p157-169

Abstract

This study is aimed to classify the brain activity of adolescents associated with audio stimuli; murottal Al-Quran and classical music.  The raw data were filtered using Independent Component Analisys (ICA) and followed by band-pass filter in Python on the Google Colab Extraction was processed with Power Spectral Density (PSD) and the Random Forest Method in Weka Machine Learning was used for classification.  The research results showed the same results between the two types of stimulation, namely the order of brain waves from highest to lowest were delta, alpha, theta and beta. The average brain waves of teenagers when given murottal al-Quran stimulation were 45.32% delta, 31.60% alpha, 17.02 theta and 6.05% beta. Meanwhile, the average brain waves of teenagers when given classical music stimulation were 46.54% delta, 28.64% alpha, 19.21% theta and 5.50% beta. Classification is obtained with the best value that frequently appears (mode) from the prediction results for each sample using random forest methods. The accuracy, precision, and recall of classifying adolescent brain waves when given murottal and classical music stimuli using the Random Forest method with cross-validation technique (optimum at k-fold=5) were 65.38%, 76.92%, and 70.00%, respectively.  The results of this study show that stimulation using murottal al-Quran and classical music effectively improves adolescent relaxation conditions.
Comparison of friction coefficient of static and sliding determination methods: conventional, video tracking and IoT-based Gideon, Samuel; Sumarti, Heni
Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Vol 10, No 2 (2024)
Publisher : Universitas Sultan Ageng Tirtayasa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30870/gravity.v10i2.27940

Abstract

The prevalent physics parameter in the concepts of friction are the friction coefficient of static and sliding. The objective of this research is to determine the friction coefficient of static and sliding by means of conventional measurement, video-tracking as well as proposed IoT-based measurement likewise to compare the results of each methods correspondingly theoretical references. Two universal systems in determining friction coefficient of static and sliding are reproduced, involves both conventional and IoT-based measuring instruments: flat block against flat runway and flat block against inclined runway. Video-tracking is the most precise between conventional and IoT-based method as its %RSD mean value of interval reading and angle of inclination respectively 6.22% and 0.88%. In case determination of friction coefficient of static three methods have equal %TE mean value of 22.85% for oak-based block on cast iron plank excluded slightly 0.49% of differences than assumed %TE value of video-tracking. Each methods are considerably accurate since each friction coefficient of sliding are theoretical values required range of 0.300 – 0.500. for oak-based block on cast iron plank IoT-based measurement has the smallest mean value of %TE indicating most accurate between two other methods.
Perbandingan Aktivasi Otot Trisep pada Kondisi Kontraksi dan Relaksasi Menggunakan Elektromiografi (EMG) Portabel Berbasis Android Hani Nur Endah; Heni Sumarti; Hamdan Hadi Kusuma
Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Vol. 2 No. 5 (2024): September : Polygon : Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/polygon.v2i5.234

Abstract

EMG is a method widely used to estimate muscle activity and can help understand how muscles interact with each other that affects human movement control. In this study to detect muscle interaction during contraction and relaxation of the triceps elbow muscle. Non-invasive techniques are used in this study to characterize muscle electrical activity. In this study, additional loads were added to the contraction movement to observe whether there was a relationship between changes in muscle activity and the load carried by the muscle in male and female subjects. Signal changes can be read by the microcontroller ADC and then sent to Blynk. This study shows that during the relaxation movement, the subject has an average Vpp value of 0.007 V. When performing the contraction movement, the average Vpp value increases to 0.024 V. When a 2 kg load is added, the average Vpp value increases to 0.027 V. The heavier the load carried, the Vpp value of muscle activity also increases.
Effect of Molarity on Double Layer Photocatalytic Activity ZnO/ZnO:Ag for Metanil Yellow Degradation Anggita, Sheilla Rully; Kusuma, Hamdan Hadi; Sumarti, Heni; Teke, Sosiawati
Physics Education Research Journal Vol. 5 No. 1 (2023)
Publisher : Faculty of Science and Education, UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/perj.2023.5.1.13301

Abstract

Double layer (DL) ZnO/ZnO:Ag has been synthesized with variations in molarity of 0.1, 0.3, 0.5,  and 0.7 M and its application as a degrading agent for methanil yellow dye. This study aims to determine the effect of the molarity of the DL ZnO/ZnO:Ag on crystallinity and photocatalytic activity for methanil yellow degradation. DL ZnO/ZnO:Ag was synthesized using sol-gel technique and deposited with spray coating technique. The results of DL ZnO/ZnO:Ag were characterized by XRD to determine the crystallinity and particle size. The photocatalytic activity was carried out by immersing the DL ZnO/ZnO:Ag layer in 10 ppm methanil yellow solution and irradiating it with UV light for 4 hours and then tested using UV-Vis spectroscopy to get the percentage of methanil yellow degradation. The results showed that the crystallinity of the DL ZnO/ZnO:Ag for all molarity variations had a hexagonal wurtzite structure. Grains size increase as molarity increases from 0.1 to 0.5 M. However, if the concentration continues to be increased to 0.7M, the grain size decreases. Photocatalytic activity is increasing every hour, as indicated by the increasing percentage of degradation. Precursor in 0.5 M has the maximum percentage of degradation is 25.32%.
Alpha Wave Activity on Think Hard and Dhikr Condition Using Electroencephalographic (EEG) Huwaidah, Indah Rifdah; Kholidah, Kholidah; Sumarti, Heni
Physics Education Research Journal Vol. 6 No. 1 (2024)
Publisher : Faculty of Science and Education, UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/perj.2024.6.1.15200

Abstract

Emotions are very important in thinking, making decisions, and a person's personality. This research was conducted to know the activity of alpha waves using an electroencephalographic (EEG) instrument, using an experimental method given the treatment of thinking hard and dhikr of istighfar. The brain waves analyzed in this study are alpha waves with a frequency between 8-12 Hz. The analysis shows that the alpha wave mean result is 11.89 Hz when thinking hard, and the mean result is 10.89 Hz during dhikr. The statistical test results show a significance of p = 0.000323 (p < 0.05), showing that dhikr can volunteer from a state of hard thinking to a relaxed state. The istighfar dhikr (astaghfirullah hal adzim) by the volunteer is a response to ask for forgiveness and reassure the heart.