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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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Klasifikasi Tumor Payudara Berbasis Ciri Tekstur pada Citra Mammografi Menggunakan Metode Naive Bayes BELLA JULIA; HENI SUMARTI; HAMDAN HADI KUSUMA
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 7, No 2 (2022): MIND Journal
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v7i2.165-176

Abstract

ABSTRAKKanker payudara adalah jenis kanker yang terjadi pada sebagian besar wanita. Kanker payudara terjadi akibat pertumbuhan berlebih atau perkembangan sel jaringan payudara yang tidak terkendali. Mammografi merupakan metode terbaik untuk deteksi dini kanker payudara karena dapat menunjukkan lesi secara dini. Namun, analisis terhadap mammogram ini masih dilakukan secara manual oleh ahli medis, sehingga perlu perangkat tambahan. Telah banyak penelitian tentang olah citra untuk deteksi kanker secara otomatis. Pada penelitian ini digunakan metode Naive Bayes untuk klasifikasi citra tumor jinak dan tumor ganas. Tujuan dari penelitian ini untuk mengklasifikasi citra mammografi berdasarkan dua kelas yaitu tumor jinak dan tumor ganas dengan berbasis ciri tekstur menggunakan histogram dan Gray Level Co-occurrence Matrix  (GLCM). Penelitian ini menunjukkan hasil akurasi sebesar 80%, sensitivitas sebesar 90%, dan spesifitas sebesar 70%. Oleh karena itu, penelitian ini bisa dijadikan perangkat tambahan untuk klasifikasi tumor payudara ganas dan jinak.Kata kunci: Tumor Payudara, Mammografi, Klasifikasi Naive Bayes.ABSTRACTBreast cancer is a type of cancer that occurs in most women. Breast cancer occurs due to overgrowth or uncontrolled development of breast tissue cells. Mammography is the best method for early detection of breast cancer because it can show lesions early. However, the analysis of this mammogram is still done manually by medical experts, so additional devices are needed. There have been many studies on image processing for automatic detection. In this study, the Naive Bayes method was used to classify images of benign tumors and malignant tumors. The purpose of this study is to classify mammographic images based on two classes, namely benign and malignant tumors based on histogram textures and Gray Level Co-occurrence Matrix (GLCM). This study showed an accuracy of 80%, sensitivity of 90%, and specificity of 70%. Therefore, this study can be used as an additional tool to classify malignant and benign tumors.Keywords: Breast Cancer, Mammografi, Naive Bayes Classification
Klasifikasi Kasus COVID-19 dan SARS Berbasis Ciri Tekstur Menggunakan Metode Multi-Layer Perceptron Azzahra, Jannatul Firdausa; Sumarti, Heni; Kusuma, Hamdan Hadi
Jurnal Fisika Vol 12, No 1 (2022)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v12i1.35685

Abstract

Corona Virus Disease 2019 (COVID-19) merupakan penyakit infeksi akut yang disebabkan oleh virus corona sebagai sindrom pernafasan akut parah. SARS (Severe Acute Respiratoty Syndrome) merupakan gangguan saluran pernapasan yang disertai gejala saluran perncernaan disebabkan oleh corona virus. Penelitian ini bertujuan untuk membedakan pasien COVID-19 dan SARS berdasarkan ciri tekstur dengan metode Multi-Layer Perceptron (MLP). Metode yang digunakan dalam penelitain ini terdiri dari tiga tahap, tahap pertama adalah pre-processing, tahap kedua adalah ekstraksi ciri tekstur menggunakan histogram dan GLCM (Gray Level Co-occurrence Matrix), dan tahap ketiga adalah klasifikasi data menggunakan metode Multi-Layer Perceptron (MLP). Hasil penelitian menunjukkan bahwa citra pasien SARS memiliki rerata kecerahan lebih tinggi, memiliki kontras lebih tajam, dan tingkat penyebaran data dalam piksel citra rontgen toraks lebih acak dibandingkan dengan citra pasien COVID-19. Metode yang digunakan dalam penelitian ini menghasilkan akurasi, sensitivitas, dan spesifisitas yang sama, yaitu sebesar 91,67%. Penelitian ini menunjukkan bahwa ciri tekstur mampu membedakan citra rontgen toraks pasien COVID-19 dan SARS secara akurat, sehingga dapat menjadi perangkat tambahan untuk memudahkan tenaga kesehatan.
Development of Chobmons Prototype: Cholesterol and Blood Sugar Level Monitoring System Based on Internet of Things (IoT) using Blynk Application Heni Sumarti; Tria Nurmar’atin; Hamdan Hadi Kusuma; Istikomah Istikomah; Irman Said Prastyo
Jurnal Fisika dan Aplikasinya Vol 18, No 3 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, LPPM-ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24604682.v18i3.12532

Abstract

In the era of the industrial revolution 4.0, we need remote technology and products that d not created new medical waste piles. An unhealthy lifestyle can cause many diseases, either degenerative diseases, namely over rate cholesterol and blood sugar level. High cholesterol and blood sugar levels are causes of major influence on atherosclerosis, stroke, micro-vascular, and cardiovascular complications. We offer a non-invasive cholesterol and blood sugar monitoring device based on red LED and infrared light absorption using the Nellcor DS-100A sensor. This technology can help reduce cumulative medical waste and help health workers to monitor patients remotely. This study used ten random samples to calibrate cholesterol and blood sugar levels. The coefficient of determination values were 0.9580 and 0.9581, respectively, which gave excellent values so that the study is continued by collecting data. Data retrieval use 20 random sample data to measure cholesterol and blood sugar levels, the average accuracy prototype is 90.26% and 91.16%, respectively. It shows great potential in determining estimation value at cholesterol and blood sugar levels. The monitoring system can show the data on the LCD display in Blynk Application with the average time required of 1.07 s.
Profil Kadar Gula Darah, Asam Urat dan Kolesterol Warga Beringin Forest Park dengan Metode Non-invasif dan Prinsip Zero Waste Heni Sumarti; Istikomah Istikomah; Affa Ardhi Saputri; Susilawati Susilawati; Fahira Septiani; Alvnia Nabila Tasyakuranti; Qisthi Fariyani
Parta: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 2 (2022)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/parta.v3i2.4125

Abstract

Pemeriksaan kesehatan merupakan pemeriksaan yang berfokus pada pencegahan primer dan sekunder, dengan melihat secara holistik berbagai faktor kesehatan yang dapat menyebabkan penyakit tertentu di masa depan. Pemeriksaaan yang dilakukan dengan menggunakan metode non-invasif sesuai dengan salah satu prinsip zero waste yaitu mengurangi limbah medis. Tujuan kegiatan pengabdian ini adalah untuk mendapatkan profil kadar gula darah, kolesterol dan asam urat menggunakan metode non-invasif berbasis prinsip zero waste dan mencegah berbagai resiko penyakit akibat kadar yang melebihi ambang normal. Metode penerapan dalam pengabdian masyarakat ini terdiri dari tiga tahap, yakni persiapan, pelaksanaan dan evaluasi. Persiapan berupa persiapan tempat, alat dan perangkat tambahan. Pelaksanaan berupa penjelasan alat dan pemeriksaan kesehatan. Evaluasi berupa wawancara dengan warga terkait kesan saat menggunakan alat dan feedback terkait hasil pemeriksaan. Hasil pemeriksaan kesehatan pada 29 warga menunjukkan rata-rata profil kadar gula darah 148.93 mg/dl, kadar kolesterol 102.24 mg/dl, dan kadar asam urat 3.17 mg/dl. Hal ini menunjukan bahwa rata-rata kadar gula darah sedikit di atas ambang normal, sedangkan kadar kolesterol dan asam urat berada pada ambang normal. Warga merasa sangat nyaman dengan pemeriksaan non-invasif karena tidak perlu melukai jari untuk mengambil sampel.
Utilizing Appropriate Technology for Non-Invasive Examination of Blood Sugar, Cholesterol, and Uric Acid Levels Alvania Nabila Tasyakuranti; Fahira Septiani; Heni Sumarti; Istikomah Istikomah; Qisthi Fariyani; Sheilla Rully Anggita; Affa Ardhi Saputri; Susilawati Susilawati; Irman Said Prastyo; Hartono Hartono; Fachrizal Rian Pratama
Madani: Jurnal Pengabdian Masyarakat dan Kewirausahaan Vol 1 No 4 (2023): Juli 2023
Publisher : LPPM Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/madani.v1i4.7619

Abstract

High blood sugar, cholesterol and uric acid are non-communicable diseases and are one of the causes of death in the world. Generally, this disease is very susceptible to be suffered by the elderly. One of the tests to monitor blood sugar, cholesterol, and uric acid levels is with an invasive disposable test kit. This method is inefficient because it causes the risk of infection, increases medical waste and is quite expensive. Real work students from Walisongo State Islamic University Semarang group 53 held a free examination in Krandon Village as an effort to carry out community service through appropriate technology in the health sector. Examination tools are made by lecturers and students using non-invasive methods (without injuring the body). Based on the results of student interviews with the community and health workers, this work program received a good response because the examination did not cause pain and helped reduce medical waste in the environment.
Mini Research: Analyzing the Relationship between Listening to Murottal Al Qur’an Surah Al Baqarah Verses 1-10 to Beta Waves with Learning Concentration Heni Sumarti; Muhammad Syafiul Huda; Fahira Septiani; Affa Ardhi Saputri; Arifah Riana
Jurnal Fisika dan Aplikasinya Vol 19, No 2 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat, LPPM-ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24604682.v19i2.16145

Abstract

Concentration in learning has a big impact on determining learning outcomes. Some of the conditions experienced by students who find it difficult to maintain concentration during the learning process are caused by many factors. Among them is the atmosphere of a noisy learning environment. One way to determine the learning concentration condition is by measuring beta brain waves using Electroencephalography (EEG). This study aims to analyze the effect of the murottal stimulus of Al Baqarah verses 1-10 on beta brain wave activity and its relationship with learning concentration. The research method used is experimental. Subjects in this study were 6 students of UIN Walisongo Semarang, with inclusion criteria ranging from 20-23 years old, Muslim, not hearing impaired, physically and mentally healthy, and not using drugs. The stages of research consisted of 4 stages; first, the research subjects carried out the pre-test without stimulus; second subject measured their brain waves without stimulus; third, subjects measured brain waves with stimulus; and finally, the research subjects carried out the pre-test with stimulus. The analysis results using the T-test, which stated that the average comparison of beta brain waves in the two groups before and after being given the murottal Al-Qur’an stimulus showed a p-value of 0.0003 (p<0.05). While the results of the pre-test and post-test T-test showed a p-value of 0.017 (p<0.05). It shows that the murottal stimulus of Al Baqarah verses 1-10 effects changes in beta waves and the level of learning concentration.
Klasifikasi tumor payudara jinak dan ganas pada citra ultrasonografi (USG) berdasarkan karakteristik tekstur menggunakan metode random forest Rahmawati, Aida; Sari, Ice Uliya; Sumarti, Heni
Jurnal Teras Fisika: Teori, Modeling, dan Aplikasi Fisika Vol 7 No 1 (2024): Jurnal Teras Fisika: Teori, Modeling, dan Aplikasi Fisika
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jtf.2024.7.1.10997

Abstract

The incidence of breast cancer is steadily increasing each year in Indonesia. Currently, breast cancer is not only prevalent in the elderly population but also among younger individuals. Several studies indicate that breast cancer classification can be performed using ultrasonography. The aim of this research is to explore the use of the Random Forest method for classifying breast tumors in ultrasonography images based on texture characteristics. Although the model achieved 100% accuracy on the training data, testing with various folds showed a decrease in accuracy ranging from 51% to 54%, with varying precision and recall. Despite not being optimal, Random Forest demonstrates potential as a classification algorithm, providing a foundation for further development to enhance the accuracy of breast tumor diagnosis. Factors such as feature selection, dataset quality, and model parameters are crucial considerations for future research to support more accurate diagnoses by healthcare professionals.
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.
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