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All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Jurnal Neutrino : jurnal fisika dan aplikasinya JURNAL FISIKA JFA (Jurnal Fisika dan Aplikasinya) Jurnal Imejing Diagnostik Journal of Natural Sciences and Mathematics Research Gravity : Jurnal Ilmiah Penelitian dan Pembelajaran Fisika Jurnal Inovasi dan Pembelajaran Fisika Knowledge Engineering and Data Science Prosiding SNFA (Seminar Nasional Fisika dan Aplikasinya) Journal of Physics and Its Applications MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal Teras Fisika : Teori, Modeling, dan Aplikasi Fisika Physics Education Research Journal Jurnal Fisika dan Terapannya Parta: Jurnal Pengabdian Kepada Masyarakat Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Jurnal Teknik Elektro Journal of Holistic Medical Technologies Community Research and Application Journal (CRAJ)
Sumarti, Heni
Universitas Islam Negeri Walisongo Semarang
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Medicine & Pharmacology Neuroscience Physics Social Sciences Other

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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.
SCALAR INTERACTIONS IN THE MODIFIED LEFT-RIGHT SYMMETRY MODEL Istikomah, Istikomah; Isnawati, Nurul Embun; Sumarti, Heni; Anggita, Sheilla Rully
Jurnal Neutrino:Jurnal Fisika dan Aplikasinya Vol 16, No 1 (2023): October
Publisher : Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/neu.v16i1.20518

Abstract

The Standard Model is a model of particle physics in which one Higgs particle has been confirmed with a mass of 126 GeV. In 2016 some discoveries made it possible to have other scalar particles similar to the Higgs. The modified left-right symmetric model extends the standard model with an expanded scalar sector. There are ϕ_L and Δ_L left sector scalar particles, ϕ_L and Δ_L right sector scalar particles and two singlet η and ξ scalar particles. Therefore, this research objective is to analyze of the possibility of a Higgs interaction with other scalar particles. The method of this research is using a Feynman diagram to describe the interaction terms at the Higgs Potential. The interaction probability is sought using the Feynman rule for Toy Theory. The decay rate uses the Golden Rule. When the universe's temperature reaches the mass of η, the scalar becomes non-relativistic and decays into ϕ_L and ϕ_R. The scalar ξ is scattered into ϕ_L through the η scalar propagator and into ϕ_R. The scalars Δ_L and Δ_R do not decay, they only scatter into ϕ_L and ϕ_R. The η and ξ scalars have transformed into ϕ_L in the left sector and ϕ_R in the right sector, and only ϕ_L in the sectors are likely to be detected as the Higgs Standard Model.
Classification of CT Scan Images of Stroke Patients and Normal Brain Based on Histogram, GLCM, and GLRLM Texture Features using K-Nearest Neighbor Azizah, Fitria Kholbi; Putri, Diana Salsabila; Permana, Riyan; Sumarti, Heni; Darma, Panji Nursetia
Journal of Physics and Its Applications Vol 7, No 4 (2025): November 2025
Publisher : Diponegoro University Semarang Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jpa.v7i4.27259

Abstract

Stroke is a major neurological disorder requiring rapid and accurate diagnosis for effective treatment. Computerized Tomography (CT) scanning provides detailed brain imaging but requires expert interpretation. This study aims to develop an automated classification system to distinguish between normal and stroke-affected brain CT scan images using texture feature analysis, providing enhanced accuracy and robustness compared to existing single-feature approaches. A total of 200 CT scan images (100 normal, 100 stroke cases) from the Kaggle database were analyzed. Texture features were extracted using Histogram, Gray Level Co-occurrence Matrix (GLCM), and Gray Level Run Length Matrix (GLRLM) analysis. The KNN algorithm was evaluated using percentage split validation, with the training set ranging from 50% to 70% of the data. The KNN classifier achieved optimal performance with 93% accuracy, 91% precision, and 96% recall using a 50% training set, demonstrating its potential as a diagnostic support tool for healthcare professionals to facilitate faster diagnosis and treatment decisions. The integration of multiple texture analysis methods showed superior performance compared to individual feature extraction techniques. Histogram features contributed significantly to classification accuracy by enhancing the detection of tissue heterogeneity. Texture analysis revealed significant differences between normal and stroke images in entropy, contrast, and correlation parameters. The proposed method successfully classifies CT scan images of normal and stroke-affected brains with high accuracy, demonstrating potential for clinical implementation in automated stroke screening and diagnostic support.
Pilot Study: Portable Non-Invasive Blood Sugar, Cholesterol, Uric Acid Monitoring System Sumarti, Heni; Alvania Nabila Tasyakuranti; Qolby Sabrina
Jurnal Teknik Elektro Vol. 16 No. 1 (2024)
Publisher : LPPM Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jte.v16i1.8204

Abstract

Degenerative diseases commonly associated with abnormal blood sugar, cholesterol, and uric acid levels require regular monitoring. Remote health monitoring technology enables children to monitor their parents' health conditions from a distance. This research presents a prototype development through Research and Development (R&D) methodology. This study developed a portable, low-cost, non-invasive detection system for blood sugar, cholesterol, and uric acid levels using the TCRT5000 sensor with Telegram integration. The compact device offers real-time monitoring advantages without blood sampling. The development followed the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model. The research results show the prototype's coefficient of determination for blood sugar is 0.9733, cholesterol is 0.9411, and uric acid is 0.9610. The non-invasive prototype demonstrates measurement errors of 7.41% for blood sugar, 15.83% for cholesterol, and 14.69% for uric acid. These error rates currently exceed medical measurement standards. The system successfully integrates with the Telegram application for remote monitoring. Future research should incorporate artificial intelligence algorithms to minimize error values.
Co-Authors Adrial, Rico Affa Ardhi Saputri Agus Sudarmanto Alvania Nabila Tasyakuranti Alvania Nabila Tasyakuranti Alvania Nabila Tasyakuranti Alvnia Nabila Tasyakuranti Arifah Riana AYU WULANDARI Ayu Wulandari Azizah, Fitria Kholbi Azzahra, Jannatul Firdausa Baehaqi BELLA JULIA Cahyawati, Rina Susi Darma, Panji Nursetia Edi Daenuri Anwar, Edi Daenuri Edison, Rizki Edmi Fachrizal Rian Pratama Fahira Septiani Fahira Septiani Farah Alfiana Na’ila Fariyani, Qisthi Firman Hardianto Frida Agung Rakhmadi, Frida Agung Gideon, Samuel Hadi Kusuma, Hamdan HAMDAN HADI KUSUMA Hamdan Hadi Kusuma Hamdan Hadi Kusuma Hani Nur Endah Hani Nur Endah Hardianto, Firman Hartono Hartono Huwaidah, Indah Rifdah Ice Uliya Sari Isnawati, Nurul Embun Istikomah Kholidah Kholidah, Kholidah Laelatul Munawaroh Lailiyatu Latifah Latifatul Istianah Maesyaroh, Uhty Marlin Ramadhan Baidillah Melany Puspa Damayanti Mohammad Candra Malindo Muhammad Ghozali Muhammad Ghozali Muhammad Labib Muhammad Syafiul Huda Mushoffa, Fina Nuryani, Siska Permana, Riyan Prastyo, Irman Said Putri Diah Pitaloka Putri Zulfikah Putri, Diana Salsabila Qolby Sabrina Qolby Sabrina, Qolby Rahmani, Tara Puri Ducha Rahmawati, Aida Ramadhani, Bintang Rizal Krisdiyanto Samuel Gideon Sari, Ice Uliya Septiani, Fahira Sheilla Rully Anggita Shofani, Maya Siska Nuryani Susilawati Susilawati Syntia Anggraeni Syukrotus Sa’diati Tasyakuranti, Alvania Nabila Tika Rahmawati Tria Nurmar’atin Triana, Devi Uhty Maesyaroh Wahyu Caesarendra Yuniati, Anis