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Journal : NERO (Networking Engineering Research Operation)

PENERAPAN ALGORITMA LINEAR SEARCH DI APLIKASI SECONDHAND Agustin, Nely Dwi; Cobantoro, Adi Fajaryanto; Setyawan, Mohammad Bhanu; Nurfitri, Khoiru
Networking Engineering Research Operation Vol 8, No 2 (2023): Nero - November 2023
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v8i2.21089

Abstract

Inflation in Indonesia has been increasing year by year. The high inflation rate has an impact on the increasing production costs of finished goods, resulting in higher prices which this is not balanced by good sales of new products. This has led to a plan to create a secondhand e-commerce platform. This research aims to implement a search feature that facilitates the search for used goods based on keywords. The implementation process involves the use of the Linear/Sequential Search algorithm in the JavaScript programming language and PostgreSQL as the data storage used. In practice, when the keyword matches the data in the database, the search results will be displayed. If there is no data match, the search will not find any relevant products. The result of this research is the availability of the SecondHand application, with a search feature using the Linear/Sequential Search algorithm, which helps facilitate the interaction between sellers and buyers. The results of white box and postman/grey box testing show that the search feature and its functions work well, producing valid outputs, and have a short execution time of around 613.5 ms or 0.6135 seconds based on the results of five tests.Keywords : Linear/Sequential Search Algorithm, Used Goods, SecondHand.
KLASIFIKASI CITRA PNEUMONIA MENGGUNAKAN ARSITEKTUR CONVOLUTIONAL NEURAL NETWORK (CNN) Pratama, Aan Rachmatullah; Cobantoro, Adi Fajaryanto
Networking Engineering Research Operation Vol 8, No 2 (2023): Nero - November 2023
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v8i2.18992

Abstract

Pneumonia adalah infeksi atau peradangan akut pada bagian jaringan paru yang disebabkan oleh berbagai mikroorganisme seperti bakteri, virus, parasit, jamur, kerusakan fisik paru ataupun bahan kimia. Pneumonia dapat menyerang orang dewasa maupun anak-anak, banyak kasus yang terjadi, terutama pada Negara berkembang dimana kebanyakan mengandalkan energi yang berpontensi menyebabkan polusi udara yang akan berdampak pada pernafasan manusia. Klasifikasi citra Pneumonia dari hasil rontgen dengan algoritma Convolutional Neural Network yang memiliki metode alur pemecahan masalah yang menyerupai pola pikir manusia. Pada program ini melakukan penelitian tentang membandingkan performa dari kedua model arsitektur Convolutional Neural Network arsitektur AlexNet dengan GoogleNet. Pada hasil confusion matrix mendapatkan hasil tingkat akurasi 0,79 untuk arsitektur Alexnet dan untuk arsitektur GoogLeNet mendapatkan hasil akurasi 0,78. Umumnya akurasi dari GoogLeNet lebih tinggi namun pada penelitian ini AlexNet mendapatkan akurasi yang lebih tinggi, namun GoogLeNet memiliki loss yang lebih rendah, loss dan Accuracy diperngaruhi callback yang didalamanya terdapat epoch. Pada hasil implementasi kedua model dari web app menggunakan flask dan Google colab, dari jumlah masukan 16 citra 15 prediksi dilakukan benar dan 1 salah mendapatkan hasil akurasi 0,94.Kata kunci : AlexNet, CNN, GoogLeNet, Pneumonia
Implementation of RSA Algorithm For Securing Patient Data using QR Code Technology Cobantoro, Adi Fajaryanto; Wicahyono, Fadhlullah Yoga; Zulkarnain, Ismail Abdurrozzaq
NERO (Networking Engineering Research Operation) Vol 10, No 1 (2025): Nero - 2025
Publisher : Jurusan Teknik Informatika Fakultas Teknik Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/nero.v10i1.30052

Abstract

The advancement of digital technology demands improved security systems, especially in protecting users’ personal data. One sector that heavily relies on data confidentiality is the healthcare sector, where patient information must be safeguarded from potential leaks and misuse. This study aims to implement the RSA (Rivest-Shamir-Adleman) cryptographic algorithm in the patient registration system at the dental clinic of Regunawati Cahyaningsih. RSA was chosen for its asymmetric nature and its ability to ensure data security through the use of public and private key pairs. Additionally, this study integrates QR Code technology as a medium for accessing encrypted data, streamlining and accelerating the data authorization process. The encryption process is applied to important information such as NIK, name, address, phone number, and medical records before being stored in the database. Based on the testing results, the system demonstrated excellent performance in terms of functionality, algorithm accuracy, and display speed. Whitebox testing confirmed the accuracy of the RSA algorithm implementation with 100% accuracy. Performance testing using the Largest Contentful Paint (LCP) metric showed very fast load times, ranging from 0.5 to 2.3 milliseconds, with a performance score of 100, making the system highly responsive and optimal in terms of user experience. Therefore, RSA is proven to be effective in enhancing patient data security and maintaining confidentiality within a web-based clinical information system.Keywords: Rivest-Shamir-Adleman Algorithm, Patient Data Security, Whitebox Testing, QR Code