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All Journal JIKA (Jurnal Informatika) Jurnal Sisfotek Global
Ardilla, Veronica Yose
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Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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RANCANG BANGUN APLIKASI PEMANTAUAN TUMBUH KEMBANG DAN IMUNISASI ANAK DENGAN FRAMEWORK QUASAR Ardilla, Veronica Yose; Warsito, Ary Budi
Jurnal Informatika Vol 9, No 1 (2025): JIKA (Jurnal Informatika)
Publisher : University of Muhammadiyah Tangerang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31000/jika.v9i1.12423

Abstract

Siklus kehidupan manusia meliputi berbagai tahap dari masa kehamilan hingga usia lanjut, di mana pertumbuhan dan perkembangan terjadi secara bertahap. Penelitian ini bertujuan untuk mengidentifikasi isu-isu utama dalam pencatatan tumbuh kembang dan riwayat imunisasi anak, serta mengembangkan solusi untuk mengatasi kendala yang ada. Dengan menggunakan pendekatan yang berbasis pada Kartu Kembang Anak, Buku Kesehatan Ibu dan Anak, dan Peraturan Menteri Kesehatan No 2 tahun 2020 tentang standar antropometri anak. Aplikasi ini dirancang untuk memudahkan orang tua dalam mencatat dan memantau tumbuh kembang dan riwayat imunisasi anak, mengetahui status pertumbuhan anak, serta mengingatkan jadwal imunisasi sesuai dengan pedoman Ikatan Dokter Anak Indonesia (IDAI). Metode yang digunakan dalam pengembangan aplikasi adalah metode waterfall dengan framework Quasar untuk frontend, Flask untuk backend, dan pengujian menggunakan black box testing. Aplikasi ini juga dilengkapi dengan fitur push notification melalui Firebase Cloud Messaging untuk pengingat pencatatan. Hasil pengujian menunjukkan bahwa aplikasi berhasil dalam memfasilitasi pencatatan dan pemantauan tumbuh kembang anak serta riwayat imunisasi, sambil memberikan notifikasi yang efektif kepada orang tua.
Differentiate the Varieties of Plants Using Leaf Images with YOLOv4 Widjaja, Prya Artha; Ardilla, Veronica Yose; Amelia, Sabrina Yose
JURNAL SISFOTEK GLOBAL Vol 14, No 1 (2024): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v14i1.10864

Abstract

There are many types of plant, not all recognized by people. Indonesia has many varieties of plants across the country, from Sabang to Merauke. Often, we find some fruits or plants that grow in different areas called by different names. The goal of this research is to create an application that can recognize plant types from their characteristics. These characteristics can be leaves, fruit, flowers or roots. Current research focuses on distinguishing several types of plants including their varieties using leaf images. It is hoped that apart from being able to determine the mango plant, we can also determine the type of mango, such as manalagi, harum manis, as well as guava and orange. To be able to recognize these types of plants, an object recognition algorithm based on CNN (Convolutional Neural Network) will be used. The algorithm that will be used is YOLO (You Only Look Once) version 4. Method in this research includes data collection, all data was taken using webcam or mobile phone camera. The next step is data preparation and creating a bounding box. Next step is creating model using training data and the last step was compare model with testing data, The result we got is really encouraging with almost 100 percent accuracy. The lowest accuracy is 98 percent for jambu air. This research show us that YOLOv4 can be used to differentiate varieties of plants.
Co-Authors Amelia, Sabrina Yose Ary Budi Warsito, Ary Budi Prya Artha Widjaja