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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal EECCIS e-Jurnal Arus Elektro Indonesia ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika
Rahmadwati Rahmadwati
University of Brawijaya
Computer Science & IT Electrical & Electronics Engineering Engineering

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Identifikasi Sel Acute Lymphoblastic Leukemia (ALL) pada Citra Peripheral Blood Smear Berdasarkan Morfologi Sel Darah Putih Suratin, Muhammad Dzikrullah; Rahmadwati, Rahmadwati; Muslim, Aziz
e-Jurnal Arus Elektro Indonesia Vol 1, No 3 (2015)
Publisher : e-Jurnal Arus Elektro Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini mengajukan sebuah sistem untuk melakukan identifikasi sel Acute Lymphoblastic Leukemia (ALL) pada citra sediaan apus darah berdasarkan ciri morfologi. Agoritma yang digunakan meliputi beberapa langkah: pra-pengolahan, segmentasi citra, perhitungan fitur dan klasifikasi. Algoritma K-means Clustering berdasarkan segmentasi warna digunakan untuk memisahkan citra apus darah menjadi empat daerah: latar belakang, nukleus WBC, sitoplasma WBC dan RBC. Nukleus yang tumpang tindih kemudian dipisahkan dengan mengaplikasikan metode Watershed Transform. Berdasarkan lima fitur morfologi yaitu area, perimeter, diameter, roundness dan compactness, citra apus darah diklasifikasikan menggunakan metode Support Vector Machine. Hasil penelitian ini didapatkan akurasi pengenalan sel ALL dan sel darah putih normal sebesar 95.45%.
Identifikasi Penyakit Katarak berdasarkan Citra Fundus menggunakan Siamese Convolutional Neural Network RAHMADWATI, RAHMADWATI; IMRAN, AZZAM ZAHFRAN; ASWIN, MUHAMMAD; FERDIANA, KHAIRUNISA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 4: Published October 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i4.838

Abstract

ABSTRAKKatarak merupakan penyakit yang dipengaruhi oleh faktor-faktor tertentu seperti usia, aktivitas dan penderita penyakit genetik seperti diabetes, hipertensi, asam urat serta riwayat keluarga katarak. Diagnosis penyakit katarak ini dapat dipengaruhi oleh faktor subyektif seperti pengalaman dan keahlian dokter. Untuk mengatasi hal tersebut dan menurunkan tingkat subyektivitas diperlukan pendekatan yang akurat dan konsisten yaitu sistem identifikasi penyakit katarak terbantukan komputer. Penelitian ini bertujuan sebagai deteksi dini katarak. Metode SCNN digunakan untuk mengidentifikasi citra fundus mata katarak. Fine tuning parameter SCNN memberikan performa yang baik pada proses pelatihan dan pengujian yaitu 100 epoch, optimizer : RMS Prop dan loss function Binary Crossentropy. Performansi yang diberikan yaitu akurasi 91,25%, kepresisian 91%.Kata kunci: penyakit katarak, siamese convolutional neural network, citra fundus. ABSTRACTThe cataract is a disease that influenced by certain factors such as age, activity and people with genetic disease such as diabetes, hypertension, uric acid and family history of cataract. The diagnosis of cataracts based on opthamologist experience and expertise which signifies a level of a diagnostic subjectivities. In order to overcome that problem and reduce the level of subjectivity, the need for an accurate and consistent computer aided identification for cataract disease is inevitable. This research aims to as an early detection of cataracts. The SCNN is applied for identify the cataract disease based on eye fundus image. Fine tuning SCNN parameters which provide good performances in the training and testing process with 100 epochs, RMSProp optimizer, Binary Crossentropy Loss function.This system gives promising result with the accuracy 91,25% , precision level is 91%.Keywords: cataract disease, siamese convolutional neural network, fundus images
Perbandingan Metode Cost Sensitive pada Decision Tree dan Naïve Bayes untuk Klasifikasi Data Multiclass Febriantono, M Aldiki; Pramono, Sholeh Hadi; Rahmadwati, Rahmadwati
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 1 (2020)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i1.625

Abstract

Abstrak– Knowledge discovery is the method of extracting information from data in making informed decisions. Seeing as classifiers do have a lot of learning patterns in the data, testing an imbalanced dataset becomes a major classification issue. The cost-sensitive approach on the decision tree C4.5 and nave Bayes is used to solve the rule of misclassification. The glass, lympografi, vehicle, thyroid, and wine datasets were collected from the UCI Repository and included in this analysis. Preprocessing attribute selection with particle swarm optimization was used to process the data collection. Besides, the cost-sensitive decision tree C4.5  and the cost-sensitive naive Bayes method were used in the research. On the glass, lympografi, vehicle, thyroid, and wine datasets, the accuracy of the test results was 72.34 %, 68.22 %, 75.68 %, 93.82 %, and 93.95 %, respectively, using the cost-sensitive decision tree C4.5. While the cost-sensitive naive Bayes method outperforms the others by 32.24 %, 82.61 %, 25.53 %, 97.67 %, and 94.94 % on the dataset, respectively.
Sistem Monitoring Inkubator Bayi Multifungsi dengan Fototerapi dan Ayunan Mekanis Berbasis ESP32 Idhil, Andi Nurul Isri Indriany; Fadilla, Rafa Raihan; Anggraini, Monika Ayu Puji; Dewi, Ajeng Kusuma; Sanjaya, Mochamad Rofi; Nurrohman, Muhammad Yogi; Rahmadwati, Rahmadwati
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 14 No. 3 (2020)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v14i3.668

Abstract

Abstract— Many infant mortality rates are due to premature events. Premature babies are at high risk for hypothermia and hyperbilirubinemia. To overcome this, an incubator can be used as a warmer and light therapy as blue light therapy for yellow babies. However, both medical devices have still been found using manual control. If the health worker is tired of working and manually controlling both devices, it can put the baby at risk. Multifunctional infant incubator based on ESP32, which is an infant incubator equipped with phototherapy and a mechanical swing. This multifunctional baby incubator has the ability to warm the baby's body, the baby yellow light therapy, and can calm the baby when crying. This tool can be monitored remotely using the Internet of Things (IoT). The sensors used are the DHT22 sensor and the sound sensor. Multifunctional baby incubator can make it easier for hospital or basic health care facility level to monitor baby's health in real time without being at the device location and the resulting data can be stored neatly. Keywords— Internet of Things, Monitoring, Incubator, Phototherapy. Abstrak–- Angka kematian bayi banyak disebabkan oleh kejadian prematur. Bayi prematur berisiko tinggi terhadap hipotermia dan hiperbilirubinemia. Untuk mengatasinya dapat digunakan inkubator sebagai penghangat dan fototerapi sebagai terapi sinar biru bayi kuning. Akan tetapi, masih ditemukan kedua alat kesehatan tersebut menggunakan pengontrolan secara manual. Apabila petugas kesehatan kelelahan bekerja dan melakukan pengontrolan kedua alat secara manual dapat menempatkan bayi dalam bahaya. Inkubator bayi multifungsi berbasis ESP32 yaitu inkubator bayi yang dilengkapi dengan fototerapi dan ayunan mekanis. Inkubator bayi multifungsi ini memiliki kemampuan untuk menghangatkan tubuh bayi, terapi sinar bayi kuning, dan dapat menenangkan bayi ketika menangis. Alat ini dapat dipantau dari jarak jauh menggunakan Internet of Things (IoT). Adapun sensor yang digunakan yaitu sensor DHT22 dan sensor suara. Inkubator bayi multifungsi dapat mempermudah pihak rumah sakit ataupun tingkat fasilitas pelayanan kesehatan dasar untuk mengontrol kesehatan bayi secara real time tanpa ada di lokasi alat dan data yang dihasilkan dapat tersimpan dengan rapi.Kata Kunci— Internet of Things, Monitoring, Inkubator, Fototerapi.
Rancang Bangun Pengendali Suhu pada Fermentasi Kefir Berbasis Kontroler PI Rahmadwati, Rahmadwati; Habibi, Boby Yusuf
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 15 No. 1 (2021)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v15i1.1539

Abstract

Kefir merupakan susu fermentasi yang memiliki rasa, warna, dan konsistensi yang menyerupai yogurt dan memiliki aroma khas yeasty. Kefir memiliki kandungan gula susu (laktosa) yang relatif rendah dibandingkan susu murni dan cocok bagi penderita lactose intolerant atau tidak tahan terhadap laktosa. Fermentasi bahan pangan adalah hasil kegiatan dari beberapa spesies mikroba seperti bakteri, khamir dan kapang. Mikroba fermentasi mendatangkan hasil akhir yang dikehendaki. Proses fermentasi kefir berlangsung pada suhu 25-37°C. Pada umumnya fermentasi kefir masih dibuat dengan menggunakan proses manual dengan hanya meletakkannya di suatu tempat tertutup tanpa tahu berapa suhu yang ada pada proses tersebut.  Sehingga tidak jarang sebagian masyarakat mengalami kegagalan dalam proses pembuatannya. Pada penelitian ini dilakukan pengontrolan suhu berbasis Arduino Uno dengan kontroler PI pada box fermentasi kefir. Kontroler PI dipilih karena karakteristik respon yang diinginkan adalah respon yang cepat dan memiliki nilai error yang kecil.  Aktuator berupa elemen pemanas (heater) dan sensor suhu DS18B20 sebagai feedback system.  Proses perancangan kontroler PI menggunakan metode Ziegler-Nichols yang pertama dan didapatkan parameter kontroler PI dengan gain yaitu Kp = 26,45 dan Ki = 0,61. Nilai setpoint 32℃. Pada pengujian keseluruhan sistem tanpa gangguan didapatkan performansi respon settling time (ts) sebesar 954 s atau 15,9 menit dan error sebesar 0,593%. Pada pengujian keseluruhan sistem dengan gangguan didapatkan performansi respon settling time (ts) sebesar 960 s atau 16 menit, error sebesar 0,593% dan recovery time sebesar 165 s atau 2,75 menit.
Adaptive Traffic Light Signal Control Using Fuzzy Logic Based on Real-Time Vehicle Detection from Video Surveillance Fahrunnisa, Zulfa; Rahmadwati, Rahmadwati; Setyawan, Raden Arief
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 2 (2024): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i2.28712

Abstract

Intersections often become the focal points of congestion due to poor traffic signal management, reduced productivity, increased travel duration, gas emissions, and fuel consumption. Existing traffic light systems maintained constant signal duration regardless of traffic situations, resulting in green signals for lanes with no vehicle queues that increased waiting times in other lanes. Therefore, a real-time traffic signal optimization system using Fuzzy Logic control, utilizing vehicle queue and flow rate real-time data from video surveillance, is needed. This research used recorded video from surveillance cameras in Banten Province, Indonesia, during daylight conditions. Vehicle queues and flow rate data were used as parameters to determine traffic light signals. The YOLO algorithm obtained these parameter values, then served them as inputs for the Fuzzy Logic system to determine signal duration. The accuracy of the traffic situation estimation system fluctuated within a range of 40% to 100%. Simulation results showed an improvement of approximately 18% by evaluating the total number of vehicles that exited the queue and reduced vehicle waiting time by about 21% compared to the existing system on intersection efficiency. Consequently, the proposed system can reduce pollution and fuel consumption, contributing to urban sustainability and public well-being enhancement. Despite the improvements over the previous systems, the accuracy of the vehicle detection system may vary with traffic density based on the extent of occlusions present, which is an area that needs further refinement. This research's contributions include utilizing real-time video footage from surveillance cameras above traffic lights to obtain real traffic conditions and identify potential errors such as occlusion of overlapping vehicle due to very congested roads. Another contribution is the adjustment of the Fuzzy membership function based on the vehicle detection system's ability to ensure precise determination of green signal duration, even when the input data contains errors.
Co-Authors Anggraini, Monika Ayu Puji Dewi, Ajeng Kusuma Fadilla, Rafa Raihan Fahrunnisa, Zulfa Febriantono, M Aldiki FERDIANA, KHAIRUNISA Habibi, Boby Yusuf Idhil, Andi Nurul Isri Indriany IMRAN, AZZAM ZAHFRAN Muhammad Aswin Muhammad Aziz Muslim Muhammad Dzikrullah Suratin, Muhammad Dzikrullah Nugraha, Danang Aditya Nurrohman, Muhammad Yogi Raden Arief Setyawan Sanjaya, Mochamad Rofi