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Journal of Informatics and Advanced Computing
Published by Universitas Pancasila
ISSN : -     EISSN : 27220346     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Informatics and Advanced Computing is a leading scientific publication platform that presents the latest and innovative research in the field of informatics and computing. This journal highlights the latest developments, practical applications, and significant impacts of computing technology across various disciplines. We invite researchers, academics, and practitioners to share their findings that contribute to the advancement of science and technology. The Journal of Informatics and Advanced Computing is committed to publishing research that is relevant to real-world challenges. This journal presents innovative computational-based solutions for problems faced by society, industry, and government. We strive to be the primary reference for practitioners who want to apply the latest technology in their work.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 14 Documents
 1   2 
Search results for , issue "Vol 4 No 2 (2023): Journal of Informatics and Advanced Computing (JIAC)" : 14 Documents clear
Analisis Gambar MRI Otak Untuk Mendeteksi Tumor Otak Menggunakan Algoritma CNN: Analisis Gambar MRI Otak Untuk Mendeteksi Tumor Otak Menggunakan Algoritma CNN Valliant Benvenuto Gianzurriell; Husnal, Ferdi; Fiky Ari Wijaya; Fahmi Fauzi; Iman Paryudi; Ionia Veritawati; Sri Rezeki Candra Nursari
Journal of Informatics and Advanced Computing (JIAC) Vol 4 No 2 (2023): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v4i2.6289

Abstract

Brain tumor disease is one of the deadliest diseases that can attack anyone without exception. This disease is characterized by the development of abnormal cells in human brain tissue is a sign of this disease. A digital image technology called Magnetic Resonance Imaging (MRI) can be used to detect these brain tumors. This technology is meant to help doctors identify and classify different types of brain tumors. An effective and accurate method is needed to perform MRI image classification as manual classification takes a long time and carries a high risk. One effective solution to this problem is Convolutional Neural Network (CNN). CNN is an algorithm that can learn itself from previous cases. The deep learning method, CNN with the VGG16 model, can be implemented as a solution to the problem. The process of making this system with the stages of making Image Detection, namely image acquisition, preprocessing, extraction, classification, and identification of image data. This study uses 3 datasets where each dataset has 1311 images of patient MRI results. The dataset is separated into 3 different data, namely train data, validation data, and test data. The results of testing these three datasets are able to identify the images tested into the system with a percentage accuracy of 99%.
Prediksi Harga Smartphone berdasarkan Spesifikasi menggunakan K-Nearest Neighbors: Prediksi Harga Smartphone berdasarkan Spesifikasi menggunakan K-Nearest Neighbors Fitra Ningrum, Dea; Putri Ramadhani, Shabrina; Paryudi, Iman; Veritawati, Ionia; Rezeki Candra Nursari, Sri
Journal of Informatics and Advanced Computing (JIAC) Vol 4 No 2 (2023): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v4i2.6293

Abstract

Di era teknologi informasi yang terus berkembang, pasar ponsel pintar menjadi salah satu pasar konsumen yang paling dinamis dan beragam. Pembeli seringkali dihadapkan pada banyak pilihan dalam memilih smartphone baru yang sesuai dengan kebutuhan dan budgetnya. Penelitian ini bertujuan untuk memprediksi harga smartphone berdasarkan spesifikasi. Metodologi yang digunakan adalah algoritma K-Nearest Neighbor dengan menggunakan Euclidean distance, membagi dataset menjadi 70% data latih dan 30% data uji. Model ini telah diuji sebanyak 2 kali, pengujian pertama menggunakan k sebesar 1 dan menghasilkan akurasi sebesar 57%, sedangkan pengujian kedua menggunakan nilai k sebesar 3 dan memperoleh akurasi sebesar 65%.
Sistem Informasi Tempat Wisata Pada Aplikasi Berbasis Android Pribadi, Adi Wahyu; Salsabila, Daniza
Journal of Informatics and Advanced Computing (JIAC) Vol 4 No 2 (2023): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v4i2.6329

Abstract

The government provides encouragement for tourism actors to develop their businesses in order to maintain the tourism sector which has succeeded in exceeding the target. However, tourism actors lack the management knowledge to take advantage of opportunities that affect the image of tourist attractions. Therefore, this research is based on the results of a literature study and a questionnaire that focuses on the purpose of providing an Android-based platform for tourism owners and tourists called PergiJalan. According to the results of the system development evaluation using the SDLC Waterfall research method, it can be concluded that this application has succeeded in providing a very good experience and service for tourism actors.
Implementasi Security Sistem Black Arch Linux: Implementasi Security Sistem Black Arch Linux Kusuma, Gregorius Hendita Artha
Journal of Informatics and Advanced Computing (JIAC) Vol 4 No 2 (2023): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v4i2.6424

Abstract

Dalam era digital yang semakin berkembang, keamanan sistem dan data menjadi fokus utama dalam dunia teknologi informasi. Ancaman seperti kejahatan siber, pencurian data, dan peretasan situs web semakin merajalela, memaksa organisasi dan individu untuk menghadapinya. Jurnal ini menjelaskan penggunaan security sistem menggunakan dua alat penting dalam keamanan siber, yaitu SQLMap dan John The Ripper, dalam lingkungan BlackArch Linux. SQLMap digunakan untuk mendeteksi dan mengeksploitasi kerentanan SQL injection dalam aplikasi web, sementara John The Ripper digunakan untuk melihat nilai dari password yang terenkripsi. Penelitian ini mengikuti metode Action Research yang melibatkan langkah-langkah untuk mengevaluasi kerentanan SQL injection pada situs web target, mengakses data sensitif dari database, dan mencoba melihat nilai password yang terenkripsi. Hasil penelitian mengungkapkan bahwa SQLMap efektif dalam mendeteksi dan mengeksploitasi kerentanan, sementara John The Ripper membantu dalam menguji kekuatan password. Sebagai rekomendasi, para profesional keamanan siber dan administrator sistem sebaiknya memahami penggunaan alat-alat ini untuk mengidentifikasi kerentanan dan meningkatkan keamanan sistem. Pengujian keamanan secara berkala dan etika dalam penggunaan alat-alat keamanan siber juga penting. Dengan penerapan yang bijak, kita dapat menciptakan dunia siber yang lebih aman dan terlindungi.

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