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All Journal ComEngApp : Computer Engineering and Applications Journal Journal of Intelligent Decision Support System (IDSS) JK Unila (Jurnal Kedokteran Universitas Lampung)
Idris, Mohamad
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Agriculture, Biological Sciences & Forestry Computer Science & IT Dentistry Engineering Environmental Science Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Public Health

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Parking System Optimization Based on IoT using Face and Vehicle Plat Recognition via Amazon Web Service and ESP-32 CAM (Case Study: Institut Teknologi Sumatera) Ashari, Ilham Firman; Satria, Mahesa Darma; Idris, Mohamad
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 2 (2022)
Publisher : Universitas Sriwijaya

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

Abstract

Today's technology has developed rapidly. One application of technology is in the parking lot. Most parking lots in Indonesia can already recognize the vehicle plate image, but it is hoped that it can be even better by applying Internet of Things (IoT) technology that is integrated with facial recognition images. One of the parking problems is in the parking lot at the Sumatran Institute of Technology, where checking is still done manually by security officers. This of course will take time and the level of security is also not good, because when you enter there is no checking. Checks are only carried out at the time of exit and the officer who checks is not necessarily the same and memorized as the owner of the vehicle. The addition of this facial image recognition feature is expected to increase the security of the parking system. Facial image recognition can be assisted by Cloud services from Amazon Image Recognition. With this service, no training data is required. The system developed is only a prototype. The developed parking system can recognize facial images and vehicle license plates with 2 cameras using the ESP32-Cam when entering and exiting the parking lot. The use of the ESP32-cam can recognize facial images both during the day and at night. The results obtained by the system can work effectively with an increase of 21%.
Pemanfaatan Kecerdasan Buatan sebagai Alat Bantu Diagnosis di Bidang Kesehatan : Literatur Review: Mohamad Idris, Angga Wijaya, Linda Septiani, Terza Aflika Happy, Risti Graharti Idris, Mohamad; Wijaya, Angga; Septiani, Linda; Happy, Terza Aflika; Graharti, Risti
Jurnal Kedokteran Universitas Lampung Vol. 9 No. 1 (2025): JK UNILA
Publisher : Fakultas Kedokteran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jkunila.v9i1.pp117-121

Abstract

Kemajuan teknologi kecerdasan buatan (Artificial Intelligence/AI) telah memberikan dampak besar dalam sektor kesehatan, khususnya dalam membantu proses diagnosis penyakit. AI mampu mengolah data medis dalam jumlah besar, seperti gambar radiologi, rekam medis elektronik, hingga data genomik, dengan tingkat efisiensi dan akurasi yang tinggi. Sejumlah penelitian membuktikan bahwa penggunaan algoritma machine learning dan deep learning dalam diagnosis mampu mengidentifikasi penyakit kronis seperti COVID-19, kulit, dan periodontal dengan akurasi yang sangat tinggi. Beberapa kondisi dapat melampaui kinerja tenaga medis manusia dari segi kecepatan dan akurasi. Selain mempercepat proses penegakan diagnosis, AI dapat meminimalkan risiko kesalahan manusia serta meningkatkan mutu pelayanan kesehatan. Di bidang radiologi, teknologi seperti convolutional neural networks (CNN) telah digunakan secara efektif untuk mendeteksi kelainan jaringan melalui CT scan dan MRI dengan hasil yang lebih presisi. AI juga berperan penting dalam sistem pendukung keputusan klinis (Clinical Decision Support System/CDSS), yang mendorong implementasi pengobatan berbasis data dan pendekatan yang dipersonalisasi. Namun, penerapan AI di negara berkembang seperti Indonesia masih dihadapkan pada berbagai tantangan, antara lain terbatasnya data lokal, ketimpangan infrastruktur digital, serta permasalahan etika dan regulasi. Kajian literatur ini bertujuan untuk meninjau manfaat AI dalam bidang diagnosis medis, serta mengidentifikasi hambatan yang perlu diatasi agar teknologi ini dapat diimplementasikan secara optimal dan berkelanjutan dalam sistem layanan kesehatan yang beragam. Kata kunci: Clinical Decision Support System, Deep Learning, Diagnosis Medis, Kecerdasan Buatan, Machine Learning
Web-based application development for the digitalization of badminton court reservation and scheduling using scrum methodology Ichwani, Arief; Idris, Mohamad; Afriansyah, Aidil
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 3 (2025): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i3.310

Abstract

The primary challenge in managing badminton court reservations and scheduling lies in the absence of an integrated system that supports booking, payment flexibility, and efficient schedule management. This study addresses these issues by developing a badminton court reservation information system equipped with user registration, login, court booking, schedule management, payment reporting, and member schedule search features. System evaluation was conducted through a User Acceptance Test (UAT), which confirmed that all core features functioned effectively and met user requirements. To further assess user experience, a Mean Opinion Score (MOS) evaluation involving five respondents and ten questions was carried out, yielding an average score of 3.8 on a four-point scale, categorized as very good. Respondents indicated that the system is easy to use, offers intuitive navigation, has an attractive interface, and provides stable performance while accelerating the booking process. These findings demonstrate that the system is both functionally reliable and well-received by users, thereby contributing to improved administrative efficiency, payment transparency, and overall user convenience.
Co-Authors Afriansyah, Aidil Angga Wijaya, Angga Happy, Terza Aflika Ichwani, Arief Ilham Firman Ashari Risti Graharti Satria, Mahesa Darma Septiani, Linda