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All Journal Jurnal Global Citizen : Jurnal Ilmiah Kajian Pendidikan Kewarganegaraan Jurnal Teknik Elektro dan Komputer TRIAC TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Penelitian Farmasi dan Herbal
Rahma Nur Azizah
FKIP UNEJ
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PERTAHANAN NEGARA KESATUAN REPUBLIK INDONESIA DI ERA GLOBALISASI Rahmawati, Andini; Azizah, Rahma Nur; Trisiana, Anita
Jurnal Global Citizen : Jurnal Ilmiah Kajian Pendidikan Kewarganegaraan Volume 10 Nomor 1 Tahun 2021
Publisher : Prodi PPkn Universitas Slamet Riyadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (230.802 KB) | DOI: 10.33061/jgz.v10i1.4719

Abstract

Situasi global dunia yang didukung oleh perkembangan teknologi komunikasi telah menciptakan gejala umum bahwa masyarakat sangat mudah mendapatkan informasi dari media. Masuknya masa globalisasi dan masa millenium ke-3, perkembangan fenomena kehidupan yang sangat berkaitan erat dalam aturan serta logika merupakan transformasi dan perubahan dari semua aspek kehidupan. Pada proses awal tidak hanya terjadi perubahan, tetapi momentum reformasi nasional juga telah berubah melalui pelaksanaan Propenas (Rencana Pembangunan Nasional) untuk mengatasi krisis multidimensi dapat bangkit kembali dan memperkuat kemampuannya untuk mencapai cita-cita pembangunan bangsa. Pelaksanaan kegiatan tersebut menegaskan landasan yang ideal adalah Pancasila, dan landasan konstitusinya adalah UUD 1945. Pembangunan pertahanan nasional pada bidang pembangunan nasional memegang peranan penting guna mengamankan pembangunan nasional dari berbagai tantangan, gangguan, ancaman dan berbagai kendala yang ada. Pembangunan pada sektor pertahanan bertujuan untuk membangun kemampuan negara dalam menghadapi berbagai tantangan dari dalam ataupun dari luar.
Implementasi Arsitektur Visual Geometry Group 16 (VGG16) untuk Deteksi Cardiomegaly pada Chest X-Ray Azizah, Rahma Nur; Huda, Muhamat Maariful; Tricahyo, Vion Age; Septarina, Amalia Agung
Jurnal Teknik Elektro dan Komputer TRIAC Vol 11, No 1 (2024): Mei 2024
Publisher : Jurusan Teknik Elektro Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/triac.v11i1.24371

Abstract

Abstract— Penelitian ini ditujukan untuk pengembanganmetode deteksi cardiomegaly menggunakan foto toraks yangmenghasilkan dua klasifikasi yakni kelas cardiomegaly dannon cardiomegaly. Cardiomegaly adalah pembengkakanjantung dimana jantung memiliki berat yang tidak normaldaripada jantung pada umumnya. Deteksi dini cardiomegalyperlu dilakukan, karena hal ini merupakan faktor pentingdalam penyakit jantung yang parah. Selain itu, pentingnyadeteksi dini juga dapat mengurangi risiko komplikasi akibatcardiomegaly. Pemanfaatan teknologi kecerdasan buatandalam sistem pendukung pakar medis dengan data medismemberikan kontribusi dalam bidang kedokteran. Olehkarena itu, teknik hasil analisis dari sistem medis menjadifaktor penting dalam pengembangan dan implementasi yangefektif. Pendekatan yang digunakan dalam penelitian inimelibatkan model Convolutional Neural Network arsitekturVGG16 dengan tahap preprocessing dan penggunaan layeraugmentasi dalam menganalisis citra. Melalui implementasiVGG16, hasil penelitian ini mencapai tingkat akurasi 78% danROC AUC terdefinisi sebagai good classification dengan nilaisebesar 0,83. (Abstract)
HUBUNGAN PENGETAHUAN DAN SIKAP MASYARAKAT KECAMATAN CAKUNG JAKARTA TIMUR TERHADAP PENGGUNAAN DAN RESISTENSI ANTIBIOTIK Rusdi, Numlil Khaira; Hastuti, Septianita Hastuti; Maifitrianti, Maifitrianti; Nurhasnah, Nurhasnah; Azizah, Rahma Nur
Jurnal Penelitian Farmasi Dan Herbal Vol 6 No 2 (2024): Jurnal Penelitian Farmasi & Herbal
Publisher : Fakultas Farmasi Institut Kesehatan DELI HUSADA Deli Tua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36656/jpfh.v6i2.1748

Abstract

Antibiotic resistance is one of the serious problems that are being faced today. Low levels of knowledge and poor public attitudes about antibiotic use can trigger resistance. This study aims to determine the level of knowledge, attitudes, and relationships between the level of knowledge and attitudes of the community about antibiotic use and resistance in Cakung District, East Jakarta for the July-August 2023 period. The design of this study was descriptive with cross sectional method. The sampling technique uses purposive sampling. The source of data in this study is primary data in the form of knowledge questionnaires and attitudes about antibiotics. Knowledge is categorized with high and low, while attitude is categorized with positive and negative. The results showed that as many as 400 respondents met the inclusion and exclusion criteria. The characteristics of public knowledge about antibiotics showed that 65.3% of respondents had high knowledge and 34.7% had low knowledge. As many as 61.0% of respondents had a positive attitude and 39% had a negative attitude towards the use of antibiotics and resistance. The results of the bivariate analysis showed that there was a significant relationship between the level of knowledge and people's attitudes towards antibiotic use and resistance (P<0.000). The higher the level of knowledge of the community, the more positive the attitude of the community towards the wise use of antibiotics.
Implementasi Convolutional Neural Network Untuk Pengenalan Tulisan Tangan Akasara Sunda Ngalangéna Azizah, Rahma Nur; Avianto, Donny
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8703

Abstract

Efforts to preserve the Sundanese script as a cultural heritage face challenges in the digital era, one of which is the limited resources for pattern recognition. This research aims to develop an effective custom Convolutional Neural Network (CNN) model for the classification of handwritten Sundanese script. Facing the constraint of no available public dataset, this study utilizes a primary dataset (Swaraksara Dataset) created by the author, consisting of 6,500 handwritten images evenly distributed across 13 classes (combinations of the "Na" script with rarangkén). The methodology applied includes a comprehensive data preprocessing stage, covering grayscale conversion, resizing to 200x200 pixels, normalization, and data augmentation techniques to prevent overfitting. The custom CNN architecture was designed with five convolutional layers (filters 32 to 512) and the Adam optimizer. The experimental results show that the optimal configuration was achieved with a learning rate of 0.001 and 50 training epochs, resulting in very high model performance. In the evaluation using test data, the model achieved an accuracy of 99.54% with a loss value of 0.0175. The optimal performance of this model is driven by the quality of the primary dataset supported by comprehensive image preprocessing stages, thus ensuring clean, uniform, and significantly noise-free data input. Analysis of the confusion matrix and learning curves also confirmed the model's excellent generalization ability with no indications of overfitting. This model has been successfully implemented in the "Swaraksara" web application as a Sundanese script recognition system.
Co-Authors Anita Trisiana, Anita Donny Avianto Hastuti, Septianita Hastuti Huda, Muhamat Maariful Maifitrianti Maifitrianti, Maifitrianti Numlil Khaira Rusdi, Numlil Khaira Nurhasnah Nurhasnah P Pujiastuti Rahmawati, Andini Septarina, Amalia Agung Slamet Hariyadi Tricahyo, Vion Age