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All Journal Transformasi: Jurnal Pengabdian Masyarakat JURNAL PENGABDI ILKOM Jurnal Ilmiah Journal of Information System, Applied, Management, Accounting and Research Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Informasi dan Multimedia Journal of Information Systems and Informatics TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian UNDIKMA ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Riset, Ekonomi, Akuntansi dan Perpajakan (REKAN) International Journal of Electronics and Communications Systems Bakti Sekawan : Jurnal Pengabdian Masyarakat Jurnal Ilmiah Pengabdian dan Inovasi Seminar Nasional Aplikasi Iptek (SINAPTEK) Explore ORAHUA : Jurnal Pengabdian Kepada Masyarakat Edu Elektrika Journal
Kartarina, Kartarina
Universitas Bumigora
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Sistem Informasi Antrean Pada Pusat Layanan Kesehatan Masyarakat Dengan Electronic Kartu Tanda Penduduk Menggunakan Radio Frequency Identification Anwar, Riky Adbul Gani; Kartarina, Kartarina; Madani, Miftahul
Jurnal Bumigora Information Technology (BITe) Vol. 3 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v3i1.1304

Abstract

Guna mendapatkan pelayanan Kesehatan di Pusat Pelayanan Kesehatan masyarakat (Puskesmas) biasanya diawali dengan antrean, antrean merupakan aktivitas menunggu untuk dilayani oleh satu orang atau lebih guna mendapatkan pelayanan yang diinginkan. Pasien yang melakukan kunjungan Puskesmas, biasanya akan mendaftar terlebih dahulu ke loket dan kemudian diberikan nomor antrian manual dan petugas mencatat kedalam buku kunjungan dan buku tersebut sebagai rekam kunjungan sehingga setiap kali kunjungan, staf akan mencari buku pasien dan memastikan apakah pasien terdaftar atau tidak, yang menyebabkan proses pelayanan menghabiskan waktu lebih banyak. Dari permasalahan tersebut maka dilakukan penelitian untuk sistem antrean, antrean dengan memanfaatkan teknologi IoT (Internet of Things) yaitu RFID (Radio Frequency Identification) dengan obkjek e-KTP (electronic Kartu Tanda Penduduk). Pada penelitian dengan menggunakan e-KTP yang di tempelkan pada alat RFID perekaman informasi pengunjung puskesmas cukup satu kali pendataan saja dan untuk kunjungan berikutnya pengunjung tidak perlu dicatat lagi ientitasnya, pengunjung puskesmas hanya mendaftar ke bagian/ poli yang ingin didatangi, seingga dapat memudahkan petugas / staf Puskesmas. Proses identifikasi menggunakan RFID dengan objek e-KTP dapat terjadi dengan menggunakan gelombang elektromagnetik, proses identifikasi RFID membutuhkan dua perangkat yaitu tag dan reader agar dapat berfungsi dengan baik. Penelitian ini menggunakan metode Guidelines for Rapid Application Engineering (GRAPPLE) agar dapat menghasilkan luaran dari sistem ringkas namun tidak mengurangi kualitas sistem yang dibangun. Penelitian ini bertujuan untuk memudahkan pelayanan Puskesmas salah satunya pada proses antrean. Sistem Informasi Pusat Layanan Kesehatan Masyarakat Menggunakan RFID dan objek e-KTP dapat dibuat dan dioperasikan dengan mikrokontroler ESP8266 sebagai pusat kendali rangkaian dan fitur Multi Database yang memudahkan dalam sinkronisasi dengan sistem Rekam Medis, sehingga sistem informasi yang di buat dapat diimplementasikan pada Puskesmas
Image Classification of Medicinal Plants Using Inception V3 and CNN: A Novel Implementation Kartarina, Kartarina; Islamiah, Nuratun; Supatmiwati, Diah; Zulfiqri, Muhammad; Triwijoyo, Bambang Krismono; Amrullah, Rahayun
International Journal of Electronics and Communications Systems Vol. 5 No. 2 (2025): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042//ijecs.v5i2.27930

Abstract

Indonesia is recognized as one of the world's biodiversity hotspots, with around 30,000 of the 40,000 global medicinal plant species found in its territory. This biological wealth is a strategic asset for health innovation and digital preservation. In areas with limited access to healthcare services, medicinal plants are the primary source of treatment, but their use is still hampered by the lack of a technology-based identification and documentation system. This study aims to develop and test a classification model for medicinal plants using a Convolutional Neural Network with Inception V3 architecture. The study uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework, which ensures systematic stages of business understanding, data preparation, modeling, and evaluation. The dataset used consists of 2,750 leaf images in 25 classes, compiled from previous research and independent collections. The data was divided into 1,921 images for training and 823 images for testing using a 70:30 ratio. The model was evaluated using accuracy, precision, recall, and F1 score. The results showed that the Inception V3-based CNN achieved a training accuracy of 96%, which increased to 97% with optimized weights, while maintaining strong precision, recall, and F1 scores. This proves that the Inception V3-based approach is capable of providing high and stable classification performance for the identification of Indonesian medicinal plants. These findings highlight the effectiveness of the model in identifying Indonesian medicinal plants from leaf images, providing a promising foundation for the development of knowledge and potential real-world applications
Klasifikasi Gizi Lansia Menggunakan Metode Naïve Bayes Classifier Kartarina Kartarina; Adelia Azzahrah Hatina; Ria Rismayati; Baiq Fitria Rahmiati; Fatimatuzzahra Fatimatuzzahra; Rahayun Amrullah Husaini
Jurnal Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2024): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v6i2.502

Abstract

Elderly people are a group that is vulnerable to experiencing various problems in terms of nutrition and health caused by changes in eating patterns. Nutritional status affects the independence of an elderly person, where good nutritional status means less dependence on other people and vice versa. It is necessary to treat malnutrition or malnutrition as early as possible, one of which is by having an elderly posyandu. Posyandu for the elderly as a community service provides services and assistance in special health for the elderly, by regularly recording, controlling and reviewing the medical records of the elderly in a document. The data processing method in this research uses the Naïve Bayes method, where the data used comes from the medical records of the elderly and then used as a reference as to whether the elderly have good nutrition or are malnourished and require further action. Medical record documents play an important role in posyandu services for the elderly, so that medical record documents should be digitally based and systematic in recommending the nutritional status of the elderly. The Naïve Bayes algorithm is an algorithm that can help in classifying data in diagnosis using criteria for the condition of elderly patients. Naïve Bayes also has precise accuracy when implemented in applications that have databases with large data and makes it easier for users to interpret the results. This is proven by this research which produces an accuracy value of 91% with the data used as a sample of 110 elderly patients. The system design aims to help users as posyandu cadres in knowing whether the condition of the elderly is good, whether the elderly are at risk of malnutrition and provide treatment that is appropriate to the condition of elderly patients as well as assisting the Posbindu PTM in transforming documents into computerized ones.
Co-Authors Adelia Azzahrah Hatina Amrullah, Rahayun Andi Sofyan Anas Anwar, Riky Adbul Gani Apriani Apriani Apriliansyah Apriliansyah Asgap Putra Zulian, Asgap Ayu Dasriani, Ni Gusti Cahyablindar, Ayu Cristofer Satria Cristofer Satria Diah Supatmawati Diah Supatmiwati Dian Syafitri Chani Saputri Dyah Supatmiwati Dyah Susilowati Fadli, M. Najmul Fatimatuzzahra Fatimatuzzahra Gayatri Ramadhani Hairul Imam Hammad, Rifqi Hilda Hastuti I Made Yadi Dharma Ibjan Syarif Hidayatullah Indah Puji Lestari Islamiah, Nuratun Ismarmiaty Ismarmiaty, Ismarmiaty Kurniadin Abd Latif Lalu Erwin Lalu Ganda Rady Putra Lalu Naufal Azmi M. Hidayatullah Made Nugraha Dwitama Mardedi, Lalu Zazuli Azhar Melati Rosanensi Miftahul Jihad Miftahul Madani Muhammad Haris Nasri Muhammad Jayadi Ni Ketut Sri Winarti, Ni Ketut Sri Ni Ketut Sriwinarti Ni luh Putu Juniarti Okta Travelian Pahrul Irfan Rahayun Amrullah Husaini Rahmiati, Baiq Fitria Regina Aprilia Riberu Regina Aprilia Riberu Ria Rismayati Rini Anggriani Satria, Cristofer Setiawan, Pandu Dwi Syahrir, Moch. Triwijoyo, Bambang Krismono Wahyu Kamil Syarifaturrahman Wahyu Kamil Syarifaturrahman, Wahyu Kamil Widia Febriana Wisnu Yunanda Wiya Suktiningsih Zainuddin Zulfiqri, Muhammad