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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Science and Applicative Technology Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Terpadu
Nova Resfita
Department Of Biomedical Engineering, Institut Teknologi Sumatera
Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Deteksi Malaria Berbasis Segmentasi Warna Citra dan Pembelajaran Mesin Agung W. Setiawan; Yusuf A. Rahman; Amir Faisal; Marsudi Siburian; Nova Resfita; Muhammad W. Gifari; Rudi Setiawan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021844377

Abstract

Di beberapa daerah di Indonesia, malaria masih merupakan salah satu penyakit endemik dan termasuk ke dalam kategori penyakit menular dengan vektor nyamuk Anopheles. Penurunan jumlah mortalitas penderita malaria ini telah menjadi program Pemerintah Indonesia dan World Health Organization. Salah satu hal penting yang dapat dilakukan adalah menyediakan alat diagnosis malaria yang cepat dan akurat berbantukan komputer. Oleh karena itu, pada studi ini dikembangkan sebuah metode deteksi malaria berbasis segmentasi warna citra yang dikombinasikan dengan metode pencacahan objek citra dan pembelajaran mesin berbasis Convolutional Neural Network. Pada studi ini, segmentasi citra dilakukan dengan menetapkan suatu nilai ambas batas tertentu (thresholding) pada model warna HSV. Nilai ambang batas untuk masing-masing kanal warna ditetapkan sebagai berikut: H = 100-175, S = 100-250, dan V = 60-190. Terdapat tiga skema pembelajaran mesin yang digunakan, yaitu citra asli menggunakan RMSProp optimizer, citra tersegmentasi menggunakan RMSProp dan Adam optimizer. Akurasi pelatihan dan validasi CNN tertinggi diperoleh dengan skema citra tersegmentasi menggunakan RMSProp optimizer, yaitu sebesar 92,77% dan 94,38%. Sementara, deteksi malaria berbasis pencacahan objek memiliki akurasi sebesar 93,78%. Meskipun deteksi malaria berbasis pencacahan objek memiliki akurasi 93,78%, tetapi sumber daya komputasi dan waktu yang diperlukan jauh lebih rendah.AbstractMalaria is still one of the endemic diseases in several regions of Indonesia. Reducing the malaria mortality rate has become a notable programme, not only does the Government of the Republic of Indonesia project it, but also the World Health Organization has a similar plan to tackle this disease. One of the prominent concerns to properly promote this programme is providing a rapid and accurate malaria diagnosis tool by applying the computer-aided diagnostics to minimize human errors. The aim of this study is to develop a colour microscopic image-based malaria detection using object counting and CNN-based machine learning. In this research, the HSV colour model with threshold values of H: 100-175, S: 100-250, and V: 60-190 was used to remove the image background. There are three machine learning schemes implemented in this study, i.e. original image using RMSProp optimizer, segmented image using RMSProp and Adam optimizer. The highest training and validation accuracy of CNN were obtained using a segmented image scheme by the RMSProp optimizer, 0.9277 and 0.9438. On the contrary, object-based malaria detection has an accuracy of 93.78%. Furthermore, there are several considerations to determine the malaria detection method, i.e. accuracy, computational resources, and time. Even though malaria detection using object counting has an accuracy of 93.78%, lower than the accuracy of CNN validation, the computational resources and time required are much lower and faster. Therefore, this detection method is suitable for smartphone-based devices with low-middle end specifications.
Implementasi Penghitung Laju Respirasi pada Sistem Polisomnografi menggunakan Mikrofon dan Arduino Nano Martin Clinton Tosima Manullang; Nova Resfita
Jurnal Teknologi Terpadu Vol. 7 No. 1: Juli, 2021
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v7i1.295

Abstract

Sleep apnea is a severe sleep disorder leading to severe threats such as heart attacks, strokes, diabetes, kidney failure, hypertension, etc. Not only is the diagnosis of sleep apnea a challenging measure, but it also requires a high cost of equipment, the limitations of available tools, and becomes a complicated diagnosis operated personally at home. Using the microphone embedded in the Arduino Nano, a system to measure the respiratory rate develops as a minor part of the sleep apnea diagnostic system using polysomnography. A filtering system is attached to eliminate noise and environmental consequences around the observation site. This prototype evaluates by comparing the output value with the manual calculation of the respiratory rate. Of the trials executed, the achieved system accuracy in counting the respiratory rate is above 93%, meaning that this prototype system is ideal as a method of measuring the respiratory rate.
The Implementation of Multilevel Colour Thresholding on a Prototype Coffee Machine Nova Resfita; Rahmadi Kurnia; Fitrilina Fitrilina
Journal of Science and Applicative Technology Vol 4 No 2 (2020): Journal of Science and Applicative Technology December Chapter
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM), Institut Teknologi Sumatera, Lampung Selatan, Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35472/jsat.v4i2.344

Abstract

The development of computer vision has expanded widely as there is a vast number of its applications in various aspects of daily life. One of its implementations is integrating the image processing technique on a prototype coffee machine based on the speech recognition system. This study aims to detect the requested coffee colour spoken by users which are black, middle and light. The sensor used in this research is a digital PC camera and the applied method is Multilevel Colour Thresholding. Of all experiments conducted, the image processing technique can work perfectly as the camera is able to identify the requested colour of the coffee solution. Furthermore, the system might be developed by improving the multilevel colour thresholding technique as well as advancing the hardware design in order to establish more robust coffee machine based on the requested colour.
Edukasi Penggunaan Media Pembelajaran Alternatif untuk Eksplorasi Sensorik dan Motorik ABK Rudi Setiawan; Nova Resfita; Putri Kholida; Raditia Fath Kharomatudzaky; Sekar Ambarsari Sujatmiko Putri; Sepiah Dwi Cahyani; Erdyvania Apritrycia; Nur Aida Wassi`atu Sakdiah; Denis Pramudia Putra; Pingki Novita Berliana
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 6 (2023): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v7i6.11512

Abstract

Augmented dan Virtual Reality merupakan media pembelajaran yang interaktif dan menarik yang mengkombinasikan konten dunia nyata dan virtual. Selain itu, media pembelajaran ini dapat menjadi modalitas untuk eksplorasi stimulasi sensorik dan motorik Anak Berkebutuhan Khusus (ABK). Edukasi yang diadakan di SLB Negeri PKK Provinsi Lampung oleh tim PKM ITERA bertujuan untuk mengenalkan pada guru-guru manfaat dan fungsi Augmented dan Virtual Reality ke pada siswa. Metode yang digunakan berupa teknik ceramah dan peragaan sebagai sosialisasi kepada guru guru dengan beberapa tahapan, yang diawali dengan persiapan kegiatan, pelaksanaan kegiatan, dan evaluasi kegiatan. Berdasarkan hasil evaluasi didapatkan bahwa terdapat peningkatan signifikan pengetahuan dan kemampuan 23 orang guru pada persentase skor capaian dari yang sebelumnya rerata ≤50% menjadi ≥76%. Pada interpretasi juga meningkat yang rerata sebelumnya “tidak baik” menjadi “sangat baik”. Hasil analisis diperoleh dari rerata perbedaan di lima indikator penilaian pada masing-masing materi Augmented dan Virtual Reality. Jadi, potensi siswa terfasilitasi pada sarana eksplorasi semakin tinggi.
Co-Authors Agung W. Setiawan Denis Pramudia Putra Erdyvania Apritrycia Faisal, Amir Fitrilina Fitrilina Martin Clinton Tosima Manullang Muhammad W. Gifari Nur Aida Wassi`atu Sakdiah Pingki Novita Berliana Putri Kholida Raditia Fath Kharomatudzaky Rahmadi Kurnia Rudi Setiawan Rudi Setiawan S. Marsudi Sekar Ambarsari Sujatmiko Putri Sepiah Dwi Cahyani Yusuf A. Rahman