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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 178 Documents
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Perancangan Sistem Informasi Penjualan Pada Skin of Mylife : Perancangan Sistem Informasi Penjualan Pada Skin of Mylife Nursari, Sri Rezeki Candra; Fadila, Muhammad Aurellio
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.v4i2.6287

Abstract

Abstract—Perkembangan dalam dunia usaha pada saat ini sangat kompetitif. Hal ini dikarenakan dengan perkembangan teknologi dan informasi yang begitu pesatsebuah penjualan dapat menjamin keberlangsungan sebuah perusahaan tersebut, Internet pada saat ini menjadi kebutuhan wajib bagi masyarakat, apalagi dengan adanya revolusi industri kebutuhan internet sangat penting dan sangat dibutuhkan oleh masyarakat di semua kalangan. Dengan internet ini masyarakat lebih mudah untuk mencari produk–produk yang mereka butuhkan. Dalam persaingan di dunia bisnis kini hampir semua perusahan menggunakan teknologi informasi dalam bisnisnya. Skin of MyLife ini merupakan sebuah merek perawatan kulit, saat ini dalam pengelolaannya sering mengalami kesalahan pencatatan pada proses jual, jumlah stok fisik dan arsip yang berbeda, terjadi kesalahan pada saat menanggapi keluhan pelanggan dan terhadap pengiriman. Penelitian menggunakan metode waterfall dengan perancangan berorientasi objek (UML) dalam membangun sistem. Sistem mengelola penjualan produk, pembuatan produk, stok produk, pengiriman dan komplain. Perancangan Penjualan Skin of MyLife memberikan kemudahan dalam mengelola data pada Skin of MyLife menjadi lebih tertata dan tersimpan dengan baik, memperluas pemasaran pada penjualan produk, dan mempermudah pelacakan posisi pengiriman barang.
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.
Klasifikasi Penyakit Ginjal Kronis (CKD) dengan Algoritma KNN dan Decision Tree ID3 Abdi, Nabil Fahlevi; Maulana Fikri Ahmadi
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 2 (2024): Journal of Informatics and Advanced Computing
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v5i2.7189

Abstract

Chronic Kidney Disease is a global health problem that requires diagnosis to prevent complications.According to the Director of Non-Communicable Disease Prevention and Control of the IndonesianMinistry of Health, in Indonesia, Chronic Kidney Failure is the 10th leading cause of death with more than42,000 deaths per year. Chronic kidney disease is a condition in which kidney function gradually declines.Chronic kidney disease can occur due to various factors, including hypertension, diabetes, autoimmunediseases, kidney infections, and kidney stones that are not treated properly. A step that can be used forprevention is to identify the disease with data mining classification. Many methods have been used topredict chronic kidney disease, including the K-Nearest Neighbor (KNN) & ID3 Decision Tree methods. Inthis study, classification was carried out using the KNN and ID3 methods by testing data with variouspercentages of test data, namely 10%, 20%, 30% and 40%. After testing, the highest calculation result ofthe KNN method is in the 30% percentage test data with a value of k = 3, the accuracy obtained reaches99.16%. While in the ID3 Decision tree method, the highest accuracy value is found in the 30% percentageof test data with an accuracy value of 98.33%.Keywords: Chronic Kidney Disease; Classification; K-Nearest Neighbor; Decision Tree ID3
Perbandingan Metode Decision Tree dan Naive Bayes untuk Memprediksi Thyroid Cancer Recurrence Hafizd, Fidya; Julyani, Dian Rizky; Yuliza, Hasna; Agustine, Emely Nemy; Surbakti, Kessya Immanuella; Paryudi, Iman
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 1 (2024): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v5i1.7198

Abstract

Abstract – This study aims to predict thyroid cancer recurrence by comparing two data mining methods, namely Decision Tree and Naive Bayes. The data used is classification data that has gone through preprocessing and modeling processes, then tested using test and score tests on analysis software called Orange. By using Orange as an analysis tool, experiments were conducted to determine which method gave the best accuracy. The results show that the two methods have different accuracy comparisons in predicting thyroid cancer recurrence. This research is expected to help in identifying symptoms that are at high risk of causing thyroid cancer recurrence and provide valuable insights in data analysis.
Implementasi Failover Router MikroTik Untuk Meningkatkan Ketersediaan Jaringan Pada Fakultas Teknik Universitas Pancasila Zidan, Husein; Arnecia, Zahra Jane; Oktaviani, Leni; Anisa, Gina; Arsad, Bambang Riono
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 1 (2024): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v5i1.7271

Abstract

Technology can help manage connectivity that can support data exchange in the network. Using a well-designed topology can improve network performance optimally. The use of computer networks in agencies can enable data exchange via hardware and software that are connected to each other in a network. Topology implementation can be adjusted to user needs. In this research, the author used the Informatics Engineering Study Program building at Pancasila University as an object. Please be aware that the network can experience problems, such as stopping system performance which can hinder the data exchange process that is taking place. The solution provided can be in the form of implementing failover using a MikroTik router. MikroTik routers can be used as backup routers in server infrastructure and failover is an automatic or manual process for switching from a system or component that is failing to a backup system or component that is functioning properly. This can be a strategy and factor in increasing network availability in the Pancasila University engineering faculty building. The final result of the analysis carried out is a MikroTik failover design that will be used in the Pancasila University Faculty of Engineering building.
Sistem Informasi Manajemen Inventori Berbasis Website Untuk Proses Operasional PT Bumi Bara Sakti: Bahasa Indonesia Asfian, Faeqal Hafidh Muhammad; Desti Fitriati
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 1 (2024): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v5i1.7291

Abstract

Inventory plays a crucial role in the operational management of companies, ensuring smooth supply chains and business continuity. Bumi Bara Sakti (BBS), a coal trading company, relies on accurate inventory management. But, BBS faces difficulties in managing inventory data due to a high volume of transactions, leading to heavy workloads and information delays. Additionally, limited Excel proficiency among BBS executives and employees deepens these issues. This study aims to create a web-based Inventory Management Information System using the waterfall method, MySQL for database management, and CodeIgniter4 as the framework. The research mainly focuses on recording coal sales and purchases, total stock, and truck movements to stockpiles based on data obtained from BBS. The system is expected to facilitate real-time recording of purchases, sales, and stock updates while maintaining information accuracy. Furthermore, it provides data visualization and easily understandable reports. Evaluation results indicate that the Inventory Management Information System simplifies inventory data management and data interpretation for BBS executives and employees.
English English: English Muhammad Rafly
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 1 (2024): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v5i1.7404

Abstract

Scholarship is an assistance program in the form of educational funding in the form of being given to assist students in obtaining proper education. SMA Negeri 8 Bogor City as an educational unit that organizes formal education, participates in providing scholarships for its students. The scholarship program at SMA Negeri 8 Bogor City has not used an effective and efficient method in determining the eligibility of students to receive scholarships so that errors often occur such as scholarships that are not on target. To overcome this, a website-based scholarship prediction application was created to predict the eligibility status of students to receive scholarships. Prediction is done using the classification method with the Support Vector Machine model. The results in the composition of 70% training data and 30% testing data get the highest evaluation results with Accuracy 89%, Precision 91%, Recall 95%.

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