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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Telematika Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Jurnal Teknik Elektro dan Komputer TRIAC Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) JURNAL ABDIKARYASAKTI RENATA Jurnal Pengabdian Masyarakat Kita Semua
Retno Supriyanti
Jenderal Soedirman University
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Other

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Morphological characteristics of X-ray thorax images of COVID-19 patients using the Bradley thresholding segmentation Retno Supriyanti; Muhammad Alqaaf; Yogi Ramadhani; Haris B. Widodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1074-1083

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has made test screening much needed. Currently, the most commonly used is the swab type. Although in fact, there is also a screening method with chest radiology. The purpose of this study is to develop a COVID-19 early detection system based on X-ray images of the patient's thorax in the form of a computer-aided diagnosis. This case is based on the fact that X-ray modalities are available in several health care centers in Indonesia, compared to other modalities such as computed tomography (CT) scan or magnetic resonance imaging (MRI). In this paper, we emphasize the X-ray thorax image segmentation process to explore the morphological information of the thorax. We use the Bradley thresholding segmentation method. The results obtained are promising to be further developed with a performance percentage of 73.33% for the thorax for COVID-19 patients and 54% for the thorax for normal patients.
Calculating the area of white spots on the lungs of patients with COVID-19 using the Sauvola thresholding method Retno Supriyanti; Muhammad Rifqi Kurniawan; Yogi Ramadhani; Haris Budi Widodo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp315-324

Abstract

COVID-19 is a pandemic that has occurred in the world since 2019. Researchers have carried out various ways in dealing with this disease, starting from the screening stage to the stage of treatment and therapy for COVID-19 patients. As the gateway to the COVID-19 problem, screening has an essential role in a diagnosis that leads to appropriate treatment. In this paper, we will focus on the screening stage using digital image processing techniques, namely in calculating the area of white spots in the lungs of COVID-19 patients. The white patches are an early indication of how badly COVID-19 is attacking the patient. We use X-Ray Thorax image objects as research data in this paper. Although the current experimental results show that this method has a successful performance of 71.11%, it is pretty promising for further development due to its simplicity.
Morphological features of lung white spots based on the Otsu and Phansalkar thresholding method Retno Supriyanti; Syadzwina Luke Dzihniza; Muhammad Alqaaf; Muhammad Rifqi Kurniawan; Yogi Ramadhani; Haris Budi Widodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp530-539

Abstract

COVID-19 is a disease that causes respiratory system disorders, so various tests are needed. One of them uses a chest X-ray or thorax. A chest X-ray will depict the lungs as a whole so that patches like white shadows will be visible. In this study, the number of lung areas and white spots can be observed and detected using segmentation techniques in image processing. But before entering the segmentation stage, the image will go through the preprocessing stage using the tri-threshold fuzzy intensification operators (fuzzy IO) method. It then segmented the lungs using the Otsu method by changing the digital image from grey to black and white based on comparing the threshold value with the pixel colour value of the digital image. Then, further segmentation was carried out using the Phansalkar method to detect and simultaneously count the number of white spots. Referring to the experiments we have carried out, Otsu Phansalkar's segmentation performance promises to be developed further.
Support vector machine method for classifying severity of Alzheimer's based on hippocampus object using magnetic resonance imaging modalities Supriyanti, Retno; Riyanto, Arif Pujo; Ramadhani, Yogi; Aliim, Muhammad Syaiful; Akbar, Muhammad Irham; Widodo, Haris Budi; Alqaaf, Muhammad
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6322-6331

Abstract

Alzheimer's disease is a degenerative brain condition that causes progressive decline in several aspects. Starting from memory, cognitive or thinking abilities, speaking abilities, and behavior. Currently, Alzheimer's diagnosis uses some methods, such as blood tests, scanning with computerized tomography scan (CT scan), or magnetic resonance imaging (MRI). As a reference for determining the level of severity, doctors usually use clinical dementia rating (CDR). CDR is a numerical scale used to measure the severity of dementia symptoms. The doctor will manually compare the patient's condition with those stated on the CDR. This condition will take quite a long time, and sometimes human error will occur. As technology and science develop, doctors can assist in manually detecting Alzheimer's using classification algorithms. Many methods can be used to classify, including the CDR support vector machine (SVM) method. Unfortunately, this method is usually only used to classify two classes. This technology allows the classification process to be carried out automatically and quickly. On the other hand, when using CDR to classify Alzheimer's severity, there are several scales, not just two classes. So, in this research, we modified the use of SVM to classify three levels of severity, namely scale 0 for normal, scale 1 for mild conditions, and scale 2 for moderate conditions. The experiments we carried out provided an accuracy of 90.9%.
The effect of features combination on coloscopy images of cervical cancer using the support vector machine method Supriyanti, Retno; Aryanto, Andreas S.; Akbar, Mohammad Irham; Sutrisna, Eman; Alqaaf, Muhammad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2614-2622

Abstract

Cervical cancer is cancer that grows in cells in the cervix. This cancer generally develops slowly and only shows symptoms when it has entered an advanced stage. Therefore, it is crucial to detect cervical cancer early before serious complications arise. One way to detect cervical cancer early is to use colposcopy, which is to look closely at the condition of the cervix to find changes in cells in the cervix that have the potential to become cancer. However, this method requires the expertise of an obstetrician. This research proposes the use of image processing techniques to create automatic early detection of cervical cancer based on coloscopy images. In this paper, we will discuss image selection using an approach in the form of comparing the weights of feature vectors and then using a data distribution threshold, features that are not too influential can be eliminated. Image classification uses the Support Vector Machine (SVM) method, which makes it possible to distinguish normal images from abnormal images. Classification with feature selection and merging results can improve the consistency of SVM model performance evenly across all four SVM kernels.
PPM Penerangan Tenaga Surya Untuk Fasilitas Umum Bagi Warga Desa Blater Dan Desa Sidakangen Kalimanah Purbalingga Ramadhani, Yogi; Supriyanti, Retno; Aliim, Muhammad Syaiful
RENATA: Jurnal Pengabdian Masyarakat Kita Semua Vol. 1 No. 2 (2023): Renata - Agustus 2023
Publisher : PT Berkah Tematik Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61124/1.renata.8

Abstract

Mobilitas warga di daerah pedesaan bergantung pada kondisi jalan sebagai sarana transportasi. Salah satu kondisi jalan yang dimaksud adalah ketersediaan penerangan di fasilitas umum warga. Fasilitas umum yang dimaksud antara lain bisa berupa jalan desa, jalan pertanian, lapangan, dan lainnya. Penerangan jalan yang baik akan mendukung banyak hal, terutama keamanan dan kenyamanan ketika warga masyarakat menggunakan fasilitas tersebut. Sebagai salah satu bentuk penerapan tridharma perguruan tinggi, perlu dilakukan kegiatan Pengabdian Pada Masyarakat (PPM) untuk membantu warga desa dalam mengatasi masalah tersebut. Dalam kegiatan kali ini, dilakukan kegiatan penerapan ilmu pengetahuan dan teknologi dalam bentuk implementasi pembangkit listrik surya sebagai sumber energi penerangan. Lokasi tujuan program PPM adalah jalan pertanian Desa Blater dan Sidakangen, Kecamatan Kalimanah, Kabupaten Purbalingga sebagai tindak lanjut dari kegiatan PPM sebelumnya. Hasil kegiatan menunjukkan adanya meningkatnya pengetahuan warga tentang pembangkit listrik tenaga surya, ketrampilan warga dalam proses instalasi tenaga surya beserta perawatannya. Selain itu, mobilitas warga pun lebih terbantu karena jalan lebih terang dari sebelumnya (gelap)
ANALISIS STRATEGI PENGELOLAAN USAHA MIKRO BERBASIS APLIKASI TEKNOLOGI TEPAT GUNA HASIL INOVASI RISET DALAM UPAYA MENINGKATKAN EKSISTENSI PRODUK YOGHURT (STUDI KASUS PADA USAHA MIKRO YOGHURT SEHATI) Naufalin, Rifda; Wicaksono, Rumpoko; Bawono, Icuk Rangga; Supriyanti, Retno
JURNAL ABDIKARYASAKTI Vol. 4 No. 1 (2024): April
Publisher : Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/ja.v4i1.18316

Abstract

Pengabdian masyarakat merupakan salah satu Tri Dharma Perguruan Tinggi yang dilakukan untuk memberikan kontribusi kepada masyarakat luas. Program pengabdian kepada masyarakat ini bertujuan untuk membantu melakukan dan menentukan strategi pengelolaan dan pengembangan Usaha Mikro Kecil dan Menengah (UMKM) yang mandiri secara ekonomi dan sosial melalui penerapan aplikasi teknologi tepat guna hasil dari inovasi riset yang telah dilakukan. Permasalahan yang menjadi fokus dalam penerapan program pengabdian masyarakat ini adalah bagaimana cara kelompok usaha yoghurt drink dapat menerapkan teknologi diversifikasi yoghurt drink, bagaimana penggunaan kemasan produk yoghurt drink yang bagus, dan bagaimana cara meningkatkan kapasitas pengelolaan usaha melalui kapasitas pemasaran produk secara offline dan online. Untuk meningkatkan keberlanjutan usaha melalui eksistensi produk di pasaran dilakukan dengan metode penerapan teknologi tepat guna modern berskala sedang dalam proses produksi, penerapan teknologi diversifikasi produk melalui yoghurt drink rempah dari ekstrak bunga kecombrang dan berbagai varian rasa teh bunga kecombrang yang mana produk tersebut merupakan hasil-hasil riset dari riset yang telah dilakukan sebelumnya sekaligus penerapan kemasan produk yang lebih bagus untuk menjaga kualitas dari produk yoghurt yang dikemas sekalian sebagai ajang untuk menarik lebih banyak konsumen. Selain itu, dilakukan pula pelatihan dan penyuluhan mengenai proses pengolahan yoghurt kecombrang, Good Manufacturing Practice (GMP) tentang produk olahan yoghurt kecombrang, strategi pemasaran produk yang efektif secara offline dan online sehingga dapat menjangkau market yang lebih luas, dan pencatatan keuangan yang efisien melalui preferensi konsumen. Hasil dari program pengabdian masyarakat ini mampu meningkatkan manajemen pengelolaan usaha mikro UMKM Yoghurt Sehati secara lebih efektif dan efisien untuk jangka waktu yang panjang dalam upaya untuk meningkatkan nilai ekonomi atau daya jual dari produk yoghurt drink kecombrang melalui kapasitas pemasaran produk dengan metode pemasaran online dan offline secara lebih efektif dan kompetitif dengan produk lain di pasaran.
IMPLEMENTATION OF THE RANDOM FOREST METHOD FOR CLASSIFYING LUNG X-RAY IMAGE ABNORMALITIES Supriyanti, Retno; Fadlola, M. Gus Solhan; Aliim, M. Syaiful; Ramadhani, Yogi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4323

Abstract

The Covid-19 pandemic has caused a severe global health crisis. Rapid and accurate diagnostics are essential in combating this disease. In this regard, lung X-ray images have become critical for identifying Covid-19 infections. The method used in this study is random forest, a classification method based on ensemble modeling of decision trees. The lung X-ray images used in this study were taken from a datasheet containing images from COVID-19 patients and images from non-Covid-19 patients. The data pre-processing process involves extracting features from the images using image processing techniques and statistical analysis. The random forest model is trained using the processed datasheet to classify the lung X-ray images. The model's performance is evaluated using accuracy, sensitivity, and specificity metrics. In addition, cross-validation is used to measure the reliability and generalization of the model. The study results showed that the random forest method achieved good classification performance in distinguishing COVID-19 lung X-ray images from normal ones. The resulting model provided high accuracy and good sensitivity in identifying Covid-19 cases. These results show the potential of the random forest method in supporting early diagnosis and treatment of COVID-19 disease.
Aplikasi Bot Telegram Pada Sistem Presensi dan Pengukuran Suhu Tubuh Berbasis IoT Trishardian, Rachmat; Fadli, Ari; Aliim, Muhammad Syaiful; Supriyanti, Retno; Ramadhani, Yogi
Jurnal Teknik Elektro dan Komputer TRIAC Vol 9, No 2 (2022): Special Edition
Publisher : Jurusan Teknik Elektro Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/triac.v9i3.15752

Abstract

Coronavirus atau virus Covid-19 merupakan virus berbahaya dan sangat menular. Berdasarkan data dari worldometers.info per tanggal 30 Januari 2022 terdapat 375,001,247 kasus virus Covid-19 di seluruh dunia. Mengingat masih tingginya kasus virus Covid-19, maka diperlukan upaya untuk mencegah penyebaran virus Covid-19. Selain menerapkan perilaku hidup sehat, upaya pencegahan penyebaran virus Covid-19 juga dapat dilakukan dengan menciptakan inovasi teknologi. Salah satu inovasi teknologi tersebut adalah pemanfaatan bot Telegram pada sistem presensi dan pengukuran suhu tubuh berbasis internet of things (IoT) sebagai media pemantauan data, media pelaporan, dan media notifikasi. Bot Telegram ini berfungsi untuk menjalankan perintah dan memberikan pesan balasan sesuai dengan permintaan pengguna. Dalam penelitian ini, bot Telegram dibuat dengan menggunakan bahasa pemrograman PHP yang dikombinasikan dengan sebuah framework agnostic BotMan. Adapun metode pertukaran informasi pada bot Telegram dibangun dengan menggunakan metode webhook sehingga proses pertukaran informasi dapat dilakukan secara real time tanpa membutuhkan jeda waktu tertentu. Bot Telegram yang telah dibuat kemudian diuji dengan menggunakan black box testing berbasis equivalence partitions. Dari hasil pengujian, bot Telegram mampu menjalankan perintah pengguna sesuai dengan harapan sebanyak 20 dari 20 kali pengujian. Selain menguji kemampuan bot Telegram dalam menjalankan fungsinya, kemampuan bot Telegram dalam menanggapi perintah pengguna juga turut diuji. Dari 15 kali pengujian response time, bot telegram memiliki total rata – rata response time keseluruhan sebesar 0,9 detik yaitu termasuk ke dalam kategori cepat
Study of parallel operation single phase H-bridge CSI and H-bridge VSI Suroso, Suroso; Winasis, Winasis; Supriyanti, Retno
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i3.pp1721-1730

Abstract

In some applications, parallel operation of some single-phase inverters with different characteristics is a necessity, such as in a photovoltaic power conversion system. Each power inverter with its power source works, delivering power to a common load which cannot be supplied by a single power inverter. This paper proposed a novel parallel operation of two different power inverter circuit types. H-bridge voltage source inverter (HB VSI) and H-bridge current source inverter (HB-CSI), supplying AC power to a common load. The proposed inverter system was examined and its operation characteristics were analyzed using computer simulation. Moreover, a laboratory prototype of the inverter system was made and examined to validate some principal characteristics of the inverter system experimentally. Test results showed that by combining the HB-VSI and HB CSI, a lower distortion of load current was achieved, specifically, total harmonic distortion (THD) of Iload was less than 1%. This phenomenon happens even the THD of AC currents generated by HB-VSI and HB-CSI at 6.95% and 6.18%, respectively.
Co-Authors Ahmad Fariz Akbar, Mohammad Irham Akbar, Muhammad Irham Alfin Chrisanty Aliim, M. Syaiful Alqaaf, Muhammad Anugerah Kevin Marchel Ari Fadli Ariep Soelaiman Setiadi Aryanto, Andreas S. Dita Dayu AW Eko Murdyantoro Elvin Pranata Eman Sutrisna Fadlola, M. Gus Solhan Fibra R. Firmanda Hari Siswantoro, Hari Haris B. Widodo Haris Budi Widodo Haris Budi Widodo Haris Budi Widodo Icuk Rangga Bawono, Icuk Rangga Muhammad Alqaaf Muhammad Alqaaf Muhammad Rifqi Kurniawan Muhammad Syaiful Aliim Pangestu F. Wibowo Rifda Naufalin Riyanto, Arif Pujo Rumpoko Wicaksono Subkhi Adhi Priyono Suroso Suroso Suwitno Suwitno Syadzwina Luke Dzihniza Teddy Septiana Trishardian, Rachmat Tutik Ida Rosanti Wahyu Siswandari Winasis Winasis Yogi Ramadhani Yogi Ramadhani Yogi Ramadhani