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I Gede Surya Rahayuda
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Sekretariat JNATIA Gedung FMIPA Lantai 1, Program Studi Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana
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Jurnal Nasional Teknologi Informasi dan Aplikasinya
Published by Universitas Udayana
ISSN : 29863929     EISSN : 30321948     DOI : -
Core Subject : Science,
Computer Science & IT
JNATIA (Jurnal Nasional Teknologi Informasi dan Aplikasinya) merupakan jurnal yang berfokus pada teori, praktik dan metodologi seluruh aspek teknologi di bidang ilmu dan teknik komputer serta ide-ide produktif dan inovatif terkait teknologi baru dan sistem informasi. Jurnal ini memuat makalah penelitian asli yang belum pernah dipublikasikan dan telah melalui jurnal double-blind review. JNATIA (Jurnal Teknologi Informasi dan Penerapannya) diterbitkan empat kali setahun (Februari, Mei, Agustus, November).
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 255 Documents
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Perancangan Aplikasi Crowdfunding Berbasis Website Nararia Ningrat, Putu Vidi; Raharja, Made Agung
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

In this modern era many technology have been created to help human do their work. One of them is Crowdfunding, where is this app or website that can funding easily. Crowdfunding make it easy for businessman that really need funds for theire business while development. User can also giving funds to various project that being development by businessman. This Crowdfunding sites create by JavaScript Framework with Database from GraphQl.
Analisis Celah Keamanan Jaringan WPA dan WPA2 dengan Menggunakan Metode Penetration Testing Okario, Albert; Hendra Suputra, I Putu Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 4 (2023): JNATIA Vol. 1, No. 4, Agustus 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

With the rapid development of communication and information technology, wireless local area network (WLAN) security has become crucial and a major concern, as data traffic is transmitted without the need for cables. Internet-connected network devices are inherently insecure and can be exploited by crackers or hackers. When data communicates or connects in the data traffic, where data is sent and passes through a series of terminals to reach its destination, an irresponsible user has the opportunity to modify or intercept the data. Therefore, designing a WLAN network connected to the internet must be carefully planned to minimize undesirable incidents. The weakness of the IEEE 802.11 network that uses WEP encryption tends to make the encryption code more easily discoverable by hackers. Based on the aforementioned background, we conducted this research to identify vulnerabilities or security flaws in WPA and WPA2-PSK networks using penetration testing methods. Keywords: WPA2-PSK Network Security Analysis, Penetration Testing
Penerapan User Centered Design (UCD) pada Website Hai Doc Krishna Aryawan, Anak Agung Gde; Mahendra, Ida Bagus Made
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

This study aims to apply User Centered Design in the development of user interface design and user experience on the HaiDoc website. In website development, user interface and user experience (UI/UX) design is a very important initial stage in website creation. Then this UI/UX will provide an initial overview of a system that is created and provide an image for users to use and interact on this website. The UI/UX is designed on this website using a user centered design (UCD) approach. In user-centered design, there are 4 (four) stages in the UI/UX approach: analysis, planning, implementation, and testing. Users will be involved in evaluating the designs made, so the designs formed are expected to be by the users' wishes.
Analisis Performa Write/Read Kompresi Delta Encoding pada Data Logging Menggunakan Go Benchmark Mahardika Adi Putra, I Putu Gede; Suhartana, I Ketut Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 3 (2023): JNATIA Vol. 1, No. 3, Mei 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Compression for data logging in environmental health monitoring is a serious concern. Recording of environmental health history is carried out by monitoring the fluctuations of the physical parameters. The record stored in a warehouse from the logging system will increase over time. So, that’s the reason why compression on time-series data logging is needed. But, the addition of compression algorithm like delta encoding allows for increased latency. Therefore, the performance of write/read of delta encoding must be analyzed. One method to analyze is the Go Benchmark. The test parameter used in this paper is the number of iterations and times per iteration taken from the Go Benchmark’s output. The other test parameter is compression ratio and storage saving taken from the size of data before and after compression. There are 4 tests case used: single data write, single data read, multiple data write, and multiple data read. As the result, single data write/read and multiple data read work optimally in delta compression with the similar test result with baseline. But multiple data write not working optimally with times per iteration 10,254 times higher than baseline. Keywords: Data Compression, Go Benchmark, Delta Encoding, Data Logging, Performance.
Aplikasi Keamanan E-Commerece Berbasis Web Menggunakan Metode Algoritma Blowfish Hairul, Hairullah; Pramartha, Cokorda Rai Adi; Putra, Ida Ayu Gde Suwiprabayanti
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Seiring dengan perkembangan informasi yang terus meningkat salah satunya penggunaan komputerisasi dalam berbagai bidang. Hal ini erat kaitannya dengan penggunaan password dalam area komputerisasi. Rawannya manupulasi password dinilai sebagai hal yang perlu dicegah menggunakan data hiding. Salah satu teknik dalam data hiding yaitu Kriptografi. Dalam kriptografi terdapat banyak algoritma, salah satnya yang memiliki kehandalan yaitu algoritma blowfish. Sampai saat ini algoritma Blowfish belum ditemukan kelemahan yang berarti hanya adanya weak key dimana dua entri dari S-box mempunyai nilai yang sama. Belum ada cara untuk mengecek weak key sebelum melakukan key expansion, tetapi hal ini tidak berpengaruh terhadap hasil enkripsi. Hasil enkripsi dengan algoritma Blowfish sangat tidak mungkin dan tidak praktis untuk di terjemahkan tanpa bantuan kunci. Sampai kini belum ada Cryptanalysis yang dapat membongkar pesan tanpa kunci yang enkripsi oleh Blowfish. Hasil pengujian menunjukkan bahwa aplikasi bisa menjalankan fungsi-fungsi untuk melakukan proses enkripsi dan dekripsi data dengan baik. Waktu proses untuk enkripsi dan dekripsi untuk masing-masing file mempunyai sedikit perbedaan dikarenakan ukuran antara plainteks dan cipherteks juga berbeda, sedangkan waktu yang diperlukan juga lebih lama. Penelitian ini telah menghasilkan aplikasi enkripsi password yang telah diuji coba dan algoritma blowfish terbukti handal dalam mengamankan password.
Analisis Sentimen Twitter Pengaruh Tokoh Politik dengan Menggunakan Metode K-Nearest Neighbor Palguna, I Made Surya Adi; Sanjaya ER, Ngurah Agus
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 2 No 2 (2024): JNATIA Vol. 2, No. 2, Februari 2024
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Understanding public sentiment towards political figures is crucial for gauging their influence and impact. This study employs sentiment analysis to analyze Twitter data and assess the influence of political figures. Sentiment analysis, a computational exploration of expressed opinions, emotions, and sentience, allows insights into public perception on a large scale. This work leverages the K-Nearest Neighbor (KNN) algorithm, which classifies data based on its similarity to existing data points. Tweets undergo preprocessing, followed by TF-IDF weighting for keyword importance and cosine similarity calculations for comparing tweets to a labeled training dataset. By analyzing the nearest neighbors, sentiment values are assigned. The KNN model achieved an accuracy of 89%, a precision of 85%, and a recall of 88%, demonstrating its effectiveness in assessing sentiment and influence through Twitter data. This research contributes to the field of political communication by offering a robust method for analyzing public opinion and gauging the influence of political figures on social media platforms. Keywords: Sentiment Analysis, K-Nearest Neighbor, TF-IDF, Cosine Similarity
Perbandingan Random Forest, Decision Tree, Gradient Boosting, Logistic Regression untuk Klasifikasi Penyakit Jantung Dwipa Jaya, I Made Krisna; Arya Kadyanan, I Gusti Agung Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 2 No 1 (2023): JNATIA Vol. 2, No. 1, November 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Heart disease is a condition characterized by disorders affecting the heart. These heart disorders include infections, abnormalities in heart valves, blockages in the heart's blood vessels, irregular heartbeats, and so on. According to a report by the World Health Organization (WHO) in 2019, approximately 17.9 million people died from cardiovascular diseases, with 85% of them attributed to heart attacks and strokes. The shortage of doctors and specialists can lead to negligence and the overlooking of patients' symptoms, which can result in disabilities or even death for the patients. Therefore, the need for an expert system arises, which can be utilized as a tool to classify or detect heart diseases based on patients' medical records. Based on the results of the conducted research, random forest is a fairly effective algorithm for classifying heart diseases, with a recall value of 80.6% and ROC AUC of 76.3%. Keywords: Classification, Random Forest, Decision Tree, Gradient Boosting, Logistic Regression, Heart Disease
Aplikasi TSP Menggunakan Algoritma A star (Studi Kasus: Distributor Barang Br Sitepu, Rasita Natasya; Cahyadi Putra, I Gusti Ngurah Anom
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Distributor merupakan suatu kelompok usaha yang melakukan distribusi penyaluran produk ke suatu tempat ke tempat lain. Saluran distribusi sangat dipengaruhi faktor jalur pengiriman barang yang efisien sehingga bisa menghemat waktu dan biaya. Namun tidak jarang distributor mengalami kendala saat melakukan pengantaran barang, seperti waktu perjalanan yang terlalu lama dan bingung memilih tujuan mana yang terlebih dahulu dikunjungi. Salah satu penyebabnya karena luasnya wilayah yang harus ditempuh. Penyebab lainnya disebabkan karena banyaknya jalan raya terlebih lagi volume kendaraan yang banyak sering kali menyulitkan seseorang untuk mencari jalur terpendek ke tempat tujuan yang terdekat, baik dari segi jarak maupun waktu tempuh. Dari ranah bidang ilmu Informatika, penentuan rute distributor ini termasuk ke dalam permasalahan Travelling Salesman Problem. Permasalahan TSP dapat diselesaikan menggunakan beberapa algoritma, salah satunya adalah algoritma A Star. Algoritma A Star adalah salah satu algoritma pencarian graf dengan menggunakan fungsi jarak-plus-biaya untuk menentukan urutan titik yang akan dikunjungi. Dalam permasalahan ini yang harus dipecahkan adalah bagaimana cara agar bisa mengunjungi tempat yang dituju dengan jarak, waktu dan biaya yang minimum. Pada penelitian ini menggunakan data primer berupa 17 titik toko yang sudah ditentukan di wilayah kota Denpasar berupa lokasi sebagai vertex dan jarak antar toko.
Perancangan Aplikasi Sistem Keamanan Checkout Online Shop -, Viencent; Pramartha, Cokorda Rai Adi
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 4 (2023): JNATIA Vol. 1, No. 4, Agustus 2023
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Online shopping has become a preferred choice for many people to meet their consumer needs. However, security issues in online transactions remain a major concern, especially when unauthorized checkouts occur without the account owner’s knowledge. To address this problem, this research aims to design an online shop checkout security application. The application ensures that each checkout is performed by the account owner and not by unauthorized individuals, such as children without their parent’s knowledge. Advanced technology approaches and appropriate security methods will be employed in the design of this application, including the use of two-factor authentication and verification through unique security codes. It is expected that this application will provide additional protection to online shop users in maintaining the security and integrity of their transactions. Keywords: Online Shop, Checkout Security, Two-Factor Authentication, Unauthorized Transactions
Sistem Rekomendasi Anime dengan Metode Content Based Filtering Putra, I Dewa Agung Cahya; Suhartana, I Ketut Gede
Jurnal Nasional Teknologi Informasi dan Aplikasnya Vol 1 No 1 (2022): JNATIA Vol. 1, No. 1, November 2022
Publisher : Informatics Study Program, Faculty of Mathematics and Natural Sciences, Udayana University

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Abstract

Anime is a term for animated films or cartoons produced by the Japanese state. Currently the number of anime in circulation is very large, so anime lovers sometimes struggle to find an anime that suits their tastes. One of the reasons is the limited description and review translated from Japanese into other languages. Making an anime recommendation system with a content based filtering approach that utilizes TF-IDF and cosine similarity. The “genre” feature is used as a recommendation system parameter that will be processed by TF-IDF and cosine similarity. The training data uses data downloaded from Kaggle. Modeling begins by calculating the weight of the genre feature values ??using TF-IDF and looking for similarity values ??using cosine similarity. After that, the process carried out is sorting the similarity values ??on the recommendation system that will display the results of anime recommendations. There is an evaluation of the model, which results in a precision value of 88.1%

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