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The Implementation of Channel Area Thresholding in Early Detection System of Acute Respiratory Infection (ARI) Fitri, Zilvanhisna Emka; Imron, Arizal Mujibtamana Nanda
Indonesian Applied Physics Letters Vol. 5 No. 1 (2024): June 2024
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v5i1.55626

Abstract

Acute respiratory infections (ARI) are infectious diseases that affect both children and adults, particularly in the context of climate change. Bacteria are one of the causes of ARI. According to the government, the discovery of the bacteria that cause ARI is an indicator of successful management of infectious diseases. The current obstacle is the limited number of medical analysts, which results in longer microscopic examination times and requires a high level of objectivity. Therefore, a system for the early detection of ARI-causing bacteria was developed using digital image processing techniques, specifically channel area thresholding as one of the segmentation methods. This research employs four shape features for bacterial classification: the number of bacterial colonies, area, perimeter, and shape. The Naí¯ve Bayes intelligent system method is used for the classification process. The system had an accuracy rate of 86.84% in the classification of four types of bacteria: S. aureus, S. pneumoniae, C. diphteriae and M. tuberculosis
PELATIHAN PENGENALAN HURUF MENGGUNAKAN WEBSITE ALPHABET DI POS PAUD ALAMANDA 105 JEMBER Fitri, Zilvanhisna Emka; Hasan, Baharuddin; Madjid, Abdul; Imron, Arizal Mujibtamana Nanda
Science and Technology: Jurnal Pengabdian Masyarakat Vol. 1 No. 2 (2024): Juni
Publisher : CV. Science Tech Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69930/scitech.v1i2.32

Abstract

Perkembangan anak usia dini dapat dilihat dari proses pengembangan bahasa baik bahasa lisan maupun bahasa tulis. Aspek pengembangan bahasa anak meliputi pengenalan huruf, kata serta merangkai kata menjadi kalimat sederhana untuk menambah kosakata. Indikator dalam menganalisis kesulitan membaca anak terdiri dari kemampuan anak dalam membaca huruf vocal dan huruf konsonan, serta kelancaran anak dalam menirukan bunyi huruf. Website ALPHABET menjadi media pembelajaran alternatif pengenalan huruf yang menyenangkan serta membantu sekolah paud yang memiliki keterbatasan staf pengajar dan media pembelajaran. Terjadi peningkatan kemampuan siswa setelah pelatihan tersebut namun perlu adanya kegiatan pelatihan keberlanjutan untuk meningkatkan daya ingat anak mengingat konsentrasi anak mudah terganggu oleh kondisi di lingkungannya.
Application of Computer Vision for Digital Encyclopedia of Chili Varieties (Capsicum spp.) Zamzami, Muhammad Viqih; Fitri, Zilvanhisna Emka; Madjid, Abdul; Imron, Arizal Mujibtamana Nanda
Journal of Educational Engineering and Environment Vol. 3 No. 1 (2024): Journal of Educational Engineering and Environment
Publisher : Fakultas Teknik Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/jeee.v3i1.3831

Abstract

Chili is a vegetable commodity that has high economic value so that its production always increases every year. Several types of chilies are cultivated in Indonesia, namely cayenne pepper (Capsicum frutescens), curly red chili (Capsicum annuum L. var. longum), large red chili (Capsicum annuum L.) and paprika (Capsicum annuum var. grossum). Indonesia is a country that continues to develop innovation to produce many superior varieties, especially chilli plants. The problem arises that variations of other superior chili varieties can only be accessed through the official website of the ministry of agriculture, however, the data that can be accessed is limited (in the form of descriptions of chili varieties without physical appearance such as photos) so that it is quite difficult for the community and farmers to cultivate or utilize these varieties. This made researchers develop a digital encyclopedia of chili types using computer vision. This study uses a combination of digital image processing and intelligent systems. The image processing used is preprocessing such as cropping and splitting of RGB components, image segmentation and shape feature extraction. The features used are area, perimeter, major axis length, minor axis length and eccentricity. This feature is the input of the Naïve Bayes method which produces a system accuracy rate of 92%.