cover
Contact Name
Asep Erlan Maulana
Contact Email
dosen02716@unpam.ac.id
Phone
+6281299366151
Journal Mail Official
jiup@unpam.ac.id
Editorial Address
Ruang Gugus Mutu Fakultas Ilmu Komputer Universitas Pamulang - Kampus Viktor Lt. 3 Jalan Raya Puspitek No. 46 Buaran, Serpong, Tangerang Selatan, Banten, Indonesia
Location
Kota tangerang selatan,
Banten
INDONESIA
Jurnal Informatika Universitas Pamulang
Published by Universitas Pamulang
ISSN : 25411004     EISSN : 26224615     DOI : https://doi.org/10.32493
Core Subject : Science,
Jurnal Informatika Universitas Pamulang is a periodical scientific journal that contains research results in the field of computer science from all aspects of theory, practice and application. Papers can be in the form of technical papers or surveys of recent developments research (state-of-the-art). Topics cover the following areas (but are not limited to): Artificial Intelligence Big Data Business Intelligence Data mining Decision Support Systems Intelligent Systems Machine Learning Network and Computer Security Optimization Pattern Recognition Soft Computing Software Engineering
Articles 630 Documents
Implementasi Perangkat Next Generation Firewall untuk Melindungi Aplikasi dari Serangan Malware Herika Andini Putri; Rohmat Tulloh; Nazel Djibran
Jurnal Informatika Universitas Pamulang Vol 8, No 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i2.33656

Abstract

Based on the rapid development of technology, which has positive and negative impacts, one of the negative impacts is data leakage, called cybercrime. This is very dangerous and causes huge losses. In addition, the most commonly found cybercrimes are malware threats, phishing, DDoS, and others. In this study, the implementation of the Paloalto firewall is carried out by configuring the firewall, as is the attack testing stage using malware such as Eicar, ransomware, Trojans, Dos, and web filtering. The results of this test aim to prevent the risk of data loss, material loss, and the paralysis of public services. And to be efficient and effective in scanning for a variety of attacks without affecting network performance. The implications of the results found are expected to solve the problem at hand perfectly. NGFW performs prevention by blocking access to malware that enters its network traffic. This research also implements NGFW, where firewall configuration is carried out, namely by creating a rule policy on the firewall. In this study, an evaluation of network performance was carried out after the implementation of NGFW and firewall configuration. The results show that the use of NGFW and rule policies on firewalls can improve network security efficiently and effectively. It is hoped that these results can overcome the paralysis of public services due to malware attacks and improve network performance.
Sistem Klasifikasi Berita Menggunakan Metode Text Mining pada Website Pusat Kegiatan Belajar Masyarakat Budi Santoso; Daniel Alfa Puryono
Jurnal Informatika Universitas Pamulang Vol 8, No 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i2.24788

Abstract

The use of information systems via websites is not uncommon in this current era. This is because the importance of information quality can affect trust, credibility of an organization, and often used as a promotional media. However, the problem arises when there are increasing numbers of news to be informed, which becomes a problem for web managers. Therefore, a faster method and proper news classification system is needed to avoid future problems. Thus, this research uses the text mining method and pure Term Frequency algorithm to calculate the weight of each word, in order to determine which category the news belongs to automatically. To simplify the system design process, Unified Modeling Language (UML) and PIECES analysis are used to analyze the impact factors that will arise later. Based on the results of the classification system testing, it has been able to provide solutions to categorize information in PKBM, even though there are many news articles with different categories.
Design and Development Early Detection of Neurodegenerative Disease Using IoT Technology Safira Faizah; Dian Nugraha; M. N. Mohammed; Muhammad Irsyad Abdullah
Jurnal Informatika Universitas Pamulang Vol 8, No 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i2.32842

Abstract

Parkinson's disease (PD) stands as one of the most prevalent conditions, impacting approximately 6.3 million individuals globally. This disorder becomes even more complex due to commonly associated non-motor symptoms like depression, cognitive impairments, and disruptions in sleep patterns. The root of PD remains largely unclear as a significant portion of cases lack a specific cause. In the initial phases of the illness, prominent indicators encompass tremors, rigidity, slowed motion, and difficulties in mobility. Presently, patients are obligated to have appointments with their medical practitioner at intervals of six months to a year, typically for brief consultations. The visit to the medical facility offers a limited glimpse into the patient's state, frequently failing to capture the day-to-day obstacles they encounter. The current evaluation methods are insufficient in comprehending this matter. This highlights the significance of promptly identifying PD, as it allows for the early implementation of treatment measures and management tactics. Additionally, this suggested approach contributes to the enhancement of human life within the healthcare framework and holds the potential to identify Parkinson’s disease swiftly and precisely.
Implementasi Anti-DDOS Menggunakan Intrusion Prevention System (IPS) terhadap Serangan DDOS Kevin Jorenta Surbakti; Rohmat Tulloh; Muhammad Nazel Djibran
Jurnal Informatika Universitas Pamulang Vol 8, No 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i2.33685

Abstract

Distributed Denial of Service (DDoS) is a type of attack that can exhaust server resources. This attack results in a decrease in server quality so that it cannot be accessed by authorized users. Servers that are commonly victimized by this attack belong to companies from various sectors. PT Datacomm Diangraha provides solutions to these problems. As PT Datacomm Diangraha will do to Company X, which is to implement an Intrusion Prevention System (IPS) device as Anti-DDoS on its customers according to the customer's needs. This paper will test IPS devices in preventing DDoS attacks such as TCP Flood, UDP Flood, and ICMP Flood. The test is conducted by connecting the attacker and victim to the IPS device in the local network. The analysis will be done by comparing the network traffic and throughput of the victim when the attack is carried out when protected by IPS, no protection, and when traffic is normal. Experiments were conducted by performing a one-minute attack. The results of the experiments show that the traffic when protected by an IPS is similar to that during normal traffic. In addition, tests were conducted to prevent XSS malware to prove that IPS can prevent other attacks besides DDoS. From the test results, it was found that IPS can prevent DDoS attacks with 100% accuracy. The throughput data obtained when a DDoS attack occurs without IPS protection is 260978.9 - 1080732.32 bps. Throughput data when a DDoS attack occurs with IPS protection of 42.55 - 49.95 bps, which shows similarity in value with throughput during normal traffic which is 43.43 bps.
Perancangan Sistem Informasi Akademik Pada SMK Sumbangsih Untuk Mendukung Pembuatan Laporan Data Dapodik Prasojo, Pasojo; Hustinawati, Hustinawati
Jurnal Informatika Universitas Pamulang Vol 8 No 4 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i4.18963

Abstract

Perkembangan sistem informasi bertujuan untuk membantu pekerjaan manusia, sehingga bisa diterapkan secara tersistem dan terstruktur serta dapat menunjang kebijakan dalam pengambilan keputusan secara cepat. Pada SMK Sumbangsih mengalami kesulitan dalam pembuatan laporan data Dapodik karena sistem informasi akademik dalam pengelolaan data siswa, data guru dan data raport belum mengacu pada laporan data Dapodik. Untuk mengatasi masalah-masalah tersebut penulis merancang sistem informasi menggunakan bahasa pemrograman PHP dan databasenya menggunakan MySQL untuk mengelola data akademik. Konsep perancangan sistem menggunakan diagram konteks dan UML. Dengan adanya sistem informasi akademik berbasis web pada SMK Sumbangsih dapat mempermudah melakukan pengelolaan data akademik seperti data siswa, data guru, data nila dan data raport.
Deteksi Tumor Otak Melalui Gambar MRI Berdasarkan Vision Transformers dengan Tensorflow dan Keras Supriadi, Oki Akbar; Utami, Ema; Ariatmanto, Dhani
Jurnal Informatika Universitas Pamulang Vol 8 No 3 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i3.32707

Abstract

Brain tumor disease is a serious and complex health problem worldwide. Early and accurate detection of brain tumors has a major impact on patient care and prognosis. Magnetic Resonance Imaging (MRI) has become one of the main diagnostic tools in detecting brain tumors, manual interpretation of MRI images requires high clinical expertise and requires a long time. In recent years, advances in deep learning techniques and image processing have opened up new opportunities in the detection of brain tumors via MRI images. Deep learning techniques, especially the use of Vision Transformers (ViTs) models, have been successful in various complex pattern recognition tasks in images. The Vision Transformers model was chosen due to the performance improvements shown in many image recognition tasks, outperforming convolutional neural networks (CNN) based methods. Tensorflow and Keras are used as frameworks for development and training models, which have been proven effective and efficient in various previous studies. This study focuses on the performance of the Vision Transformer (ViT) in detecting brain tumors through two Magnetic Resonance Imaging (MRI) image datasets, with different numbers of datasets, as well as the maximum accuracy value that can be achieved from the ViT architecture. From several experimental parameters on ViT, the number of datasets and iterations, the results obtained from the first dataset with 253 image data obtained an accuracy value of 88%, and in the second study by combining the two datasets, with 3.123 data images obtained an accuracy of 97.9%.
Principal Component Analysis and Regional Coordinates on Face Recognition in Mobile-Based Attendance Systems Handayani, Indah Puspasari; Pradana, Rizky
Jurnal Informatika Universitas Pamulang Vol 9 No 1 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v9i1.33362

Abstract

The pattern of attendance in the world of work after the Covid-19 outbreak that hit the world, has apparently brought quite big changes, due to the taboo on gathering and using shared media which is considered a medium for the spread of bacteria/viruses. The way out of this is to use facial recognition and collaborate with location coordinates using a mobile application that can be used on each smartphone to authenticate workers in changing the characteristics of presence data, so that the presence process cannot be represented. The method used for face recognition in this research is Principal Component Analysis (PCA) by linearly transforming eigenvalues ​​and eigenvectors from extraction and reduction of faces captured from the mobile presence application. Based on the trials carried out, the success rate reached 78,667% for testing the functionality and strength of facial recognition.
Rancang Bangun Aplikasi Augmented Reality untuk Pembelajaran Materi Bangun Ruang Sekolah Dasar Antonio, Marcel; Bata, Julius
Jurnal Informatika Universitas Pamulang Vol 8 No 3 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i3.33379

Abstract

Geometry has emerged as a challenging topic in elementary mathematics due to its demand for solid cognitive capacities and spatial ability. Students struggle to understand geometry topics, particularly in solid space and three-dimensional objects. The students need help comprehending various three-dimensional shapes and understanding the formulas and definitions related to geometry. This paper aims to design and develop an application for learning solid space topics. The application provides explanations of solid space concepts, interactive exercises, and assessments to enhance students' understanding. The development process follows the ADDIE method, which includes Analysis, Design, Development, Implementation, and Evaluation. The application was evaluated by a mathematics teacher. We also conduct black-box testing. The result shows that all the functionality was valid and the application can be used by students. Future research will focus on implementing the application in actual mathematic classes and evaluating the impact on student learning.
Klasifikasi Status Stunting Balita Menggunakan Metode Naïve Bayes Gaussian Berbasis Web Mulyono, Makmur; Budianita, Elvia; Nazir, Alwis; Syafria, Fadhilah
Jurnal Informatika Universitas Pamulang Vol 8 No 3 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i3.33399

Abstract

The growth and development of toddlers must get attention from parents because toddlerhood is a golden period in shaping the growth and development and intelligence of children. Stunting is  a state of malnutrition in which stunted growth and development of children and this is included in chronic nutritional problems, the incidence of stunting  can be seen from height that is not in accordance with age. In preventing toddlers from stunting, it is necessary to anticipate early prevention by conducting examinations at the nearest posyandu which is measured using anthropometric methods. The calculation  of stunting or normal status based on anthropometric data is generally processed manually so that there is a high possibility of errors in calculating and entering data. Data mining can make classifications or predictions on the stunting status  of toddlers by studying previous data patterns. Naïve bayes is one classification method that has the advantage of high accuracy with little training data as for the attributes used in this study, namely age, gender, Early Initiation of Breastfeeding (IMD), weight, height. Based on the test results, the best average accuracy was obtained on numerical data types for age, weight, height and nominal gender attributes, Early Breastfeeding Initiation (IMD) with the highest accuracy in the 80:20 data comparison, which is 80.34% with a total of 1172 data.
Sistem Informasi Manajemen Praktek Kerja Lapangan Dengan Fitur Location Base Service (LBS) Nada, Noora Qotrun
Jurnal Informatika Universitas Pamulang Vol 8 No 3 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v8i3.33711

Abstract

Permasalahannya adalah belum adanya Sistem Informasi Manajemen Praktek Kerja Lapangan (PKL) pada Program Studi Informatika Universitas PGRI Semarang yang masih menggunakan sistem manual sehingga menyebabkan banyak kesalahan administrasi, kehilangan data dan jalur birokrasi yang panjang dalam setiap pelaksanaan PKL. Tujuan dari penelitian ini adalah membangun Sistem Informasi Manajemen PKL pada Program Studi Informatika Universitas PGRI Semarang dengan menggunakan metode penelitian Research and Development (R&D) dengan metode pengembangan System Development Life Cycle (SDLC) dengan model Iteratif yang merupakan gabungan model Waterfall dan Iterative pada model Prototype. Tahapan awal dari metode ini yaitu tahap Analisis dan Perancangan telah dilakukan pada penelitian pendahuluan yang berjudul Perancangan Sistem Informasi Manajemen Praktek Kerja Lapangan Program Studi Informatika Universitas PGRI Semarang dengan keluaran pemodelan Use Case Diagram, Activity Diagram, Sequence Diagram , Diagram Kelas dan Kamus Data. Pada penelitian ini melanjutkan dua tahap yang tersisa yaitu tahap Implementasi dan Evaluasi. Pada tahap implementasi, peneliti membangun sistem dengan menggunakan bahasa pemrograman PHP, MySQL Database Management System dan Sistem Informasi Manajemen Praktek Kerja Lapangan (PKL) yang terintegrasi dengan Location Based Service (LBS) untuk menentukan lokasi PKL mahasiswa. Selama tahap evaluasi (pengujian), metodologi pengujian black-box digunakan, sehingga semua pengujian dan skenario diterima 100%. Ini berarti sistem Anda bekerja seperti yang diharapkan. Pengujian Kotak Putih Setelah menghitung kompleksitas siklomatik, menentukan jalur independen, dan menjalankan uji nilai untuk menguji uji kode, kita menemukan bahwa kompleksitas siklomatik yang dihasilkan adalah 3. Artinya juga terdapat 3 lintasan independen, dan 3 lintasan nilai lintasan. keluaran yang diharapkan.

Filter by Year

2016 2025


Filter By Issues
All Issue Vol 10 No 4 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 10 No 3 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 10 No 2 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 10 No 1 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 9 No 4 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 9 No 3 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 9 No 2 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 9 No 1 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 8 No 4 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 8 No 3 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 8 No 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 8, No 2 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 8, No 1 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 8 No 1 (2023): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 7, No 4 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 7, No 3 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 7 No 2 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 7, No 2 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 7, No 1 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 7 No 1 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 6 No 4 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 6, No 4 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 6, No 3 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 6, No 2 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 6, No 1 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 5, No 4 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 5, No 2 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 5, No 1 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 4, No 4 (2019): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 4, No 3 (2019): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 4, No 2 (2019): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 4, No 1 (2019): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 3, No 4 (2018): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 3, No 3 (2018): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 3, No 2 (2018): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 3, No 1 (2018): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 2, No 4 (2017): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 2, No 3 (2017): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 2, No 2 (2017): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 2, No 1 (2017): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 1, No 2 (2016): JURNAL INFORMATIKA UNIVERSITAS PAMULANG Vol 1, No 1 (2016): JURNAL INFORMATIKA UNIVERSITAS PAMULANG More Issue