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Journal : Jurnal Mantik

Design and development of skin disease detection application in humans using computer vision Krisogonus Wiero Baba Kaju; Nizirwan Anwar; Agung Mulyo Widodo; Binastya Anggara Sekti
Jurnal Mantik Vol. 7 No. 4 (2024): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i4.4681

Abstract

Skin diseases are abnormal conditions affecting the outer layer of the human body. The prevalence of skin infections worldwide reaches 300 million cases per year, with Indonesia contributing significantly, mainly due to the tropical climate and dense population. Factors such as air temperature, environmental cleanliness, personal hygiene, and the lack of public knowledge about skin hygiene can trigger various types of skin diseases. Skin diseases are often considered trivial as they do not cause death, yet if not promptly and accurately addressed, they can lead to spreading and difficulties in treatment. Analyzing skin diseases requires a high level of knowledge, and accurate diagnosis often presents a challenge. The success of diagnosis heavily relies on the experience of doctors, with some limitations involving subjective assessments and variations among experts. This research aims to design an artificial intelligence (AI)-based application that can quickly and accurately diagnose various types of skin diseases in humans. The application utilizes Deep Learning technology, employing the MobileNet model in Computer Vision to identify skin disease types based on images provided by the user. The system development method used is the AI Project Cycle, encompassing stages such as problem scoping, data acquisition, data exploration, modeling, evaluation, and deployment. Model evaluation results demonstrate good performance with an accuracy rate of 96%, precision of 96%, an f1 score of 95%, and a recall of 95%. The resulting application not only provides diagnoses but also offers information about symptoms, causes, and methods of handling the identified skin diseases
Co-Authors Ady Sutjahyono Ahmad, Ahluddin Saiful Alfiana, Rita Andri Kurnia Maulana Angga Novita Prasetyo Ningrum Annisa Fitria Antara, Nyoman Putra Anton Nurfendi Aulia Ilham Zukri Badie Uddin Bere, Emilianto Sefri Budi Tjahjono Darlan, Muhamad Davies Tandianto Dita Chandra Samsiya Dwi Rio Aryanto Euis Sadeli Evi Martaseli Evi Martaseli Fadhil Ezar Rahman Fathur Andre Fadilah Fatwa Arrevi Fatwa Arriva Freddy Harris, Freddy Gusti Muhamad Sardana Gusti, Aldo Prima Hani Dewi Ariessanti Hasanah, Diannur Haziro Ulfa Hendry Gunawan Hendry Gunawan Hendry Gunawawan Ibnu Hadi Ichwani, Arief Ilham Adi Maulana Ilham Banuaji Irma Tiara Irsyad Taufiq Ilham Supardi Iwan Setiawan Iwan Setiawan Julius Jerry Nolasco Kalagi, Richard Kevin Maruli Krisogonus Wiero Baba Kaju Laksono, Mohamad Iqbal Ajie Lim Jong Su Lisasih, Nin Yasmine Lista Meria Mahatma, Yudi Marwan, Rudi Heri Mohamad Iqbal Ajie Laksono Mohammad Norman Gaza Laksono Muhamad Bahrul Ulum Muhammad Hadi Arfian Muhammad Kaisar Stevan Priadi Mulyana, Imam Nicholas Patrick Varian Nisa Aulia Nixon Erzed Nizirwan Anwar Prabowo, Ary Prianto Roito Siregar Putri Adella Cahyaningtyas Putri Jelita Syifa Eraydya Rafli Al Ihsan Rahaman, Mosiur Rahmahani, Adhining Prabawati Ramadhan, Akmil Maulana Ricky Rivandy A’oetpah Rizki Dwi Sanjaya Rizky Nur Azizah Roesfiansjah Rasjidin Ryan Putra Laksana Shefia Anggraeni Siti Nur Kholifah Siti Nur Kholifah Suherman, Reza Bintang Sutjahyono, Ady Syifa Maulida Akmalia Tandianto, Davies Tri Ismardiko Ulfa, Haziro Ulum, Muhamad Bahrul Ummanah Ummanah, Ummanah Utami, Aliph Putri Vanessa, Delivia Vincent Laurensius Hambaya Wahyudi, Endik Wasahua, Idris Widodo, Agung Mulyo Widyawan, Tri Ismardiko Yanathifal Salsabila Anggraeni Yulfitri, Alivia Yulhendri Yulhendri Zhafira Anindya Tiaraputri