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All Journal Journal of Telematics and Informatics POSITIF Faktor Exacta Matrix : Jurnal Manajemen Teknologi dan Informatika JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Telematika Bulletin of Informatics and Data Science Jurnal Informatika: Jurnal Pengembangan IT
Kurniawan, Ade
Institut Teknologi Sains Bandung
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Social Sciences Other

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A Review of Blockchain: How Does It Work, Applications, and Challenges Ade Kurniawan; Winda Andrini Wulandari; Raymond Erz Saragih; Ihsan Verdian
Journal of Telematics and Informatics Vol 7, No 2: JUNE 2019
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v7i2.

Abstract

Behind Bitcoin’s, there is a technology that becomes its fundamental part, which is Blockchain. Bitcoin is the first cryptocurrency in the world. At present, blockchain technology is the subject of discussion and research among developers, business people and researchers. Basically, blockchain technology functions as a digital 'ledger' that records every transaction that occurs and what makes blockchain interesting is, data that has been recorded in it cannot be changed. Furthermore, various blockchain-based applications began to emerge, and are used in various fields, the first to implements blockchain technology is digital currency transactions, other fields, such as the Internet of Things, government, health services, education, and industries. However, like other emerging technologies, blockchain technology still faces several challenges such as scalability and security. To deepen the knowledge about blockchain technology, a literature study is needed using the Literature Review method. This research uses literature sources from Scopus reputable institutions, Thomson Reuters / Web of Science, Directory of Open Access Journals (DOAJ), EBSCO, and Google Scholar. The contribution of this paper is to convey how Blockchain technology works, the applications and challenges ahead that will be faced by blockchain technology.
Evolution, Challenges, Mobile Application Tools and Framework: A Literature Review Meilvin Wijaya; Ade Kurniawan
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 4 No 1 (2018): POSITIF : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v4i1.542

Abstract

Mobile apps have come in dramatically in various fields and have changed people's lives. Developing effective mobile applications has become a significant problem for companies today to expand services or generate, and build a direct relationship with customers. Developing a mobile app requires challenging and testing various aspects. To deepen the knowledge of mobile apps requires a literature review. This paper provides basic knowledge about mobile applications and then continued evolution of mobile applications and mobile application challenges continued testing strategies and tools and frameworks for automation of android testing
Meningkatkan Keterampilan Berpikir, Me-Manage Keuangan Pada Masyarakat Pesisir Pulau Setokok Kota Batam Suhardi Suhardi; Ade Kurniawan; Erma Yunita; Agung Bara Muli
JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 9, No 1 (2019): Juli 2019
Publisher : LPPM UNINUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (71.184 KB) | DOI: 10.30999/jpkm.v9i1.478

Abstract

Berdasarkan hasil survei dan wawancara dengan Bapak Muhammad Centung selaku ketua RT 01 RW 02 di pulau Setokok, bahwa permasalahan kehidupan masyarakatnya adalah selalu terjebak pada pemimjaman kepada rentenir/tengkulak yang membebani bunga yang relatif tinggi selama ini. Hal ini dikarenakan minimnya pengetahuan tentang bagaimana cara efektif mengelola keuangan. Oleh karena itu, para para penduduk di sina yang umumnya adalah nelayan anak-anaknya tidak pernah mengenyam sampai duduk di Perguruan Tinggi, menamatkan SLTA saja bisa dihitung dengan jari. Untuk itulah dilakukannnya Pengabdian kepada masyarakat ini melalui DPRM Program Kemitraan Masyarakat (PKM)  dengan tujuan untuk dapat menambah pengetahuan serta wawasan di masyarakat pesisir tentang bagaimana pegelolaan keuangan yang baik serta menambah pemahaman dan keterampilan berpikir. Sasaran yang menjadi obyek pengabdian adalah masyarakat pesisir Pulau Setokok Kecamatan Bulang, Kota Batam, Kepulauan Riau. Metode yang  digunakan  adalah observasi  ke  lokasi  mitra melakukan  wawancara, diskusi  dengan  ketua  Rukun Tetangga dan Ketua Warga  dan memperjelas  permasalahan  yang  dihadapi  mitra. Pendidikan diberikan melalui penyuluhan tentang topik yang berkaitan dengan materi dan melalui pelatihan dapat meningkatkan keterampilan masyarakat dalam me-manage keuangan yang baik serta evaluasi dan pemonitoran  keberhasilan program keberlanjutan  dilakukan. Luaran  hasil didapat adalah penerapan semua anggota mitra, dalam hal ini masyarakat pulau Setokok Kecamatan Bulang Kota Batam memahami pola berpikir kreatif, menggelola keuangan yang baik, serta menambah ilmu pengetahuan.
SEJARAH, CARA KERJA DAN MANFAAT INTERNET OF THINGS Wilianto Wilianto; Ade Kurniawan
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol 8 No 2 (2018): MATRIX - Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (448.042 KB) | DOI: 10.31940/matrix.v8i2.818

Abstract

Penelitian ini bertujuan untuk mengumpulkan dan meringkas beberapa sumber pustaka terbaru tentang Internet of Things (IoT) dengan tiga sudut pandang: Sejarah, Cara Kerja dan Manfaat IoT. Metode dalam penelitian ini adalah mengunakan metode Systematic Literature Review. Hasil dari penelitian adalah sejarah awal mula IoT pada tahun 2009 oleh Kevin Ashton dengan melakukan penelitian tentang komunikasi antara Machine to Machine (M2M). Ide dasar dari IoT adalah menghubungkan beberapa perangkat dan bertukar data dengan perangkat lainnya dalam satu jaringan. Saat ini perkembangan cara kerja IoT mengalami perkembangan pesat seperti penambahan fitur Security dan Blockchain. IoT membawa dampak yang sangat baik untuk institusi pemerintah, industri, pendidikan dan kesehatan.
Sejarah, Penerapan, dan Analisis Resiko dari Neural Network: Sebuah Tinjauan Pustaka Cristina Cristina; Ade Kurniawan
Jurnal Informatika: Jurnal Pengembangan IT Vol 3, No 2 (2018): JPIT, Mei 2018
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v3i2.890

Abstract

A neural network is a form of artificial intelligence that has the ability to learn, grow, and adapt in a dynamic environment. Neural network began since 1890 because a great American psychologist named William James created the book "Principles of Psycology". James was the first one publish a number of facts related to the structure and function of the brain. The history of neural network development is divided into 4 epochs, the Camelot era, the Depression, the Renaissance, and the Neoconnectiosm era. Neural networks used today are not 100 percent accurate. However, neural networks are still used because of better performance than alternative computing models. The use of neural network consists of pattern recognition, signal analysis, robotics, and expert systems. For risk analysis of the neural network, it is first performed using hazards and operability studies (HAZOPS). Determining the neural network requirements in a good way will help in determining its contribution to system hazards and validating the control or mitigation of any hazards. After completion of the first stage at HAZOPS and the second stage determines the requirements, the next stage is designing. Neural network underwent repeated design-train-test development. At the design stage, the hazard analysis should consider the design aspects of the development, which include neural network architecture, size, intended use, and so on. It will be continued at the implementation stage, test phase, installation and inspection phase, operation phase, and ends at the maintenance stage.
Sejarah, Teori Dasar dan Penerapan Reinforcement Learning: Sebuah Tinjauan Pustaka Andreanus, Jeky; Kurniawan, Ade
Jurnal Telematika Vol. 12 No. 2 (2017)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v12i2.193

Abstract

Today's research on the topic of Machine learning has increased sharply. Machine learning is the future of the world, in the future it will be a revolution in every computer-bound science. This paper examines the field of Reinforcement learning from a computer science perspective. Reinforcement learning is part of Machine learning. In general machine learning is divided into three categories, namely supervised learning, unsupervised learning, and reinforcement learning. Supervised learning requires labeled data to analyze data, training and make conclusions, which can be used for mapping new values. Otherwise, Unsupervised learning does not use labeled data, which is more suitable for relatively irregular problems. In contrast to Reinforcement learning that is based on trial and error, by experimenting on the environment then get a response that will improve its ability. This work is summarized based on the history of Reinforcement learning and the selection of current research. This paper discusses central issues in reinforcement learning, from history, Reinforcement learning models, multiinform Reinforcement learning, including comparison of exploration and exploitation. Ends with a Reinforcement learning implementation survey of several systems. Reinforcement learning is the most suitable Machine learning in learning new things from scratch without human intervention in learning, most of Reinforcement learning is used for in-game learning. But the learning may  takes a long time and is uncertain.Dewasa ini penelitian mengenai topik Machine learning telah meningkat tajam.  Machine learning adalah masa depan dunia, kedepannya ini akan menjadi revolusi dalam segalah ilmu yang terikat dengan komputerisasi. Paper ini meneliti bidang Reinforcement learning dari perspektif ilmu komputer. Reinforcement learning merupakan bagian dari Machine learning. Secara umum machine learning dibagi menjadi tiga kategori, yaitu supervised learning, unsupervised learning, dan reinforcement learning. Supervised learning memerlukan data berlabel untuk menganalisis data, pelatihan dan membuat kesimpulan, yang dapat digunakan untuk pemetaan nilai-nilai baru. Sebaliknya, Unsupervised learning tidak memenggunakan data berlabel, yang mana lebih cocok untuk masalah yang relatif tidak beraturan. Berbeda dengan Reinforcement learning yang berbasis trial and error, dengan mencoba-coba pada lingkungannya kemudian mendapatkan respon yang akan meningkatkan kemampuannya. Karya ini dirangkum berdasarkan sejarah bidang Reinforcement learning dan pemilihan riset saat ini. Paper ini membahas isu-isu sentral dalam reinforcement learning, mulai dari sejarah, model Reinforcement learning, multiagent Reinforcement learning termasuk melakukan perbandingan dari eksplorasi dan eksploitasi. Diakhiri dengan survei penerapan Reinforcement Learning terhadap beberapa sistem. Reinforcement learning merupakan Machine learning yang paling cocok dalam mempelajari hal baru dari nol tanpa campur tangan manusia dalam pembelajarannya, kebanyakan dari Reinforcement learning digunakan untuk belajar dalam game. Namun pembelajaran yang dilakukan membutuhkan waktu lama dan tidak pasti.
Penerapan Framework OWASP dan Network Forensics untuk Analisis, Deteksi, dan Pencegahan Serangan Injeksi di Sisi Host-Based Kurniawan, Ade
Jurnal Telematika Vol. 14 No. 1 (2019)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v14i1.267

Abstract

The Internet has changed the world. The penetration of internet users in 1995 is only 1 percent of the world population, while in 2018, the figure reached 70 percent or 4.5 billion users. Simultaneously, it was reported that eight of the top ten web sites in the world were at a critical point of vulnerability to attacks by injection methods, such as Cross-Site Scripting (XSS) and Structured Query Language Injection (SQLi). Furthermore, XSS and SQLi attacks can be used by certain parties to steal information or specific purposes. In this paper, we research by conducting attack simulations, analyzing packet data, and finally conducting prevention at host-based. Initial simulations of attacks using social engineering attack techniques by sending a phishing email. At this stage of attack simulation, the attack includes information gathering, webcam screenshots, keyloggers, and spoofers. Furthermore, at the stage of analysis, we do with the approach of network forensics with evidence collection techniques using live forensics acquisition. The final stage is prevent (patching) by creating an application or add-on on the browser side by name, XSSFilterAde. This research contribution offers a broad and in-depth study of how to do a simulation, analysis, and finally prevent. Furthermore, the method of protecting the user or host- based solution in the browser application functions to filter, disable plugins, notify, block, and reduce injection attacks.Internet telah mengubah dunia. Internet telah mengubah wajah dunia. Penetrasi pengguna internet di tahun 1995 hanya 1 persen dari populasi dunia, sedangkan di tahun 2018 angkanya telah mencapai 60 persen atau 4,5 miliar pengguna. Secara bersamaan, dilaporkan delapan dari sepuluh situs web teratas di dunia berada pada titik kritis kerentanan terhadap serangan dengan metode injeksi, seperti: Cross-Site Scripting (XSS) dan Structured Query Language Injection (SQLi). Selanjutnya, serangan XSS dan SQLi dapat digunakan oleh pihak tertentu untuk mencuri informasi atau untuk tujuan tertentu. Dalam makalah ini, penelitian dilakukan denganmensimulasikan serangan, analisis paket data, dan terakhir melakukan pencegahan di host-based atau di sisi pengguna. Simulasi awal serangan menggunakan social engineering attack dengan cara mengirim sebuah phishing email. Pada tahapan simulasi serangan ini, serangan meliputi pengumpulan informasi, screenshot webcam, keyloggers, dan spoofer. Selanjutnya, di tahapan analisis, kami melakukan pendekatan network forensics dengan teknik pengambilan barang bukti menggunakan metode live forensics acquisition. Tahapan terakhir adalah mencegah (menambal) dengan membuat sebuah aplikasi atau add-on di sisi browser dengan nama XSSFilterAde. Kontribusi penelitian ini menawarkan sebuah studi secara luas dan mendalam tentang bagaimana melakukan sebuah simulasi,analisis, dan, terahir, melakukan pencegahan (prevent). Lebih jauh, metode solusi perlindungan kepada pengguna atau host-based dalam aplikasi browser berfungsi untuk memfilter, menonaktifkan plugin, memberi tahu, memblokir, dan mengurangi serangan injeksi.
Analisis Unauthorized Access Point Menggunakan Teknik Network Forensics Paramita, Felicia; Madeline, Madeline; Alvina, Olga; Sentia, Rahel Esther; Kurniawan, Ade
Jurnal Telematika Vol. 14 No. 2 (2019)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v14i2.287

Abstract

In this era, free access points are found available in various places. But this freedom comes with a price, and only a few users really understand the risk. In a recent survey, 70% of tablet owners and 53% of smartphone owners stated that they use public wifi hotspots. The biggest threat to public wifi security is how a hacker positions himself as a liaison between victims and Authorized Access Points. To do this the hacker creates an Unauthorized Access Point (Fake Access Point). We took a pentester/attacker POV in this artikel for educational purposes, so that users may know the stages of Fake Access Point attack based on Kali Linux, Fluxion. For the digital evidence analysis stage, we used the customized OSCAR (Obtain information, Strategies, Collect Evidence, Analyze and Report) methods, where attacking is the stage for preparation, determining which wifi Access Points is going to be the target of the attack, and carrying out attacks. While, analysis is the stage of analyzing the steps of attack and how to distinguish between AAP and UAP. The results of our research are that after determining the target, the pen tester/attacker will use aircrack-ng on Fluxion to get a handshake, create a fake web interface, then launch a deauth all attack, also known as DoS, to AAP so that the victim / client cannot connect with the AAP and switch to Fake Access Point. The fake web interface will then ask the victim to enter the password, where after the password is found, the pen tester/attacker can see it through Fluxion. As a precautionary measure, the difference between a Fake Access Point and an Authorized Access Point is found in the presence or absence of the padlock symbol (Android) or an exclamation point (Windows 10).Pada zaman ini, free access point telah tersedia di berbagai tempat. Namun, nyatanya kebebasan ini memiliki harga, dan hanya sedikit pengguna yang memahami benar risikonya. Ancaman terbesar terhadap kemanan wifi publik adalah bagaimana seorang hacker memposisikan dirinya sebagai penghubung antar korban dan Authorized Access Point. Untuk melakukan hal tersebut, hacker membuat Unauthorized Access Point (Fake Access Point). Dalam artikel ini pen tester/attacker diambil sudut pandang sebagai dengan tujuan edukasi, agar pengguna mengetahui tahapan serangan Fake Access Point dengan tool Fluxion berbasis OS Kali Linux. Tahapan analisis bukti digital menggunakan metode OSCAR (Obtain Information, Strategies, Collect Evidence, Analyze and Report) yang telah di kostumisasi, di mana attacking adalah tahapan untuk persiapan menentukan target wifi Access Point yang akan diserang serta menjalankan serangan. Analysis adalah tahapan menganalisa langkah penyerangan serta bagaimana cara membedakan Authorized Access Point dengan Unauthorized Access Point. Hasil penelitian yang dilakukan setelah menentukan target, pentester/attacker akan menggunakan Aircrack-ng pada Fluxion untuk mendapatkan handshake, membuat web interface palsu, kemudian melancarkan serangan Deauth all, dikenal DoS ke AAP, sehingga korban/client tidak dapat terkoneksi dan masuk ke Fake Access Point. Web interface palsu kemudian akan meminta korban untuk memasukkan password. Setelah password ditemukan, maka pen tester/attacker dapat melihatnya melalui Fluxion. Sebagai langkah pencegahan, perbedaan antara Fake Access Point dan yang Authorized Access Point ditemukan pada ada tidaknya simbol gembok (Android) atau tanda seru (Windows 10).
Lightweight Deep Learning for Object Detection on Mobile Device Lika, Sudiharyanto; Pernando, Yonky; Kurniawan, Ade
Bulletin of Informatics and Data Science Vol 2, No 2 (2023): November 2023
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v2i2.82

Abstract

Computer vision is a research in the development of technology to obtain information from images and replicate or imitate human visual processes, so that computers can know the objects around them. Deep learning is now the key word as a new era in machine learning that trains computers in finding patterns from large amounts of data. The Convolution Neural Networks (CNN) algorithm has proven impressive in terms of performance for detecting objects, image classification and semantic segmentation. Object detection is a technique used to identify the type of object in an image and also the exact location of the object in the image. Face detection is one of the most challenging problems of pattern recognition. Effective training needs to be done to be able to detect faces effectively. The accuracy in face detection using machine learning does not give good results. This research focuses on the level of accuracy of detecting faces using deep learning methods. This study compares the level of accuracy of deep learning and machine learning in detecting faces effective and efficient. This study uses the Convolution Neural Networks (CNN) model in the deep learning method to detect faces in real time on Android. According to the test results, the accuracy obtained in this study reached 97.97% in several normal facial conditions and face masks.
Ketahanan Pembelajaran Mesin terhadap Adversarial examples: Metodologi dan Pertahanan Kurniawan, Ade; Aprilia, Ely; Aulia, Achmad Indra; Siregar, Amril Mutoi; Goeirmanto, Leonard
Faktor Exacta Vol 18, No 2 (2025)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v18i2.26078

Abstract

This paper examines the vulnerability of machine learning models to adversarial examples: inputs that are subtly manipulated to deceive a model into making incorrect predictions. Although deep learning has demonstrated remarkable performance across various tasks, the security of these models remains a significant challenge. This study provides a comprehensive review of various methods for generating adversarial examples, a classification of attack techniques, and corresponding defense strategies, including both active and passive approaches. The findings indicate that a combination of several defense techniques is significantly more effective in enhancing model robustness compared to any single approach. This research is expected to provide a foundation for the development of more secure and reliable machine learning models for critical applications.
Co-Authors Agung Bara Muli Alvina, Olga Andreanus, Jeky Aprilia, Ely Aulia, Achmad Indra Cristina Cristina Erma Yunita Felicia Paramita Goeirmanto, Leonard Lika, Sudiharyanto Madeline, Madeline Meilvin Wijaya Pernando, Yonky Raymond Erz Saragih Sentia, Rahel Esther Siregar, Amril Mutoi Suhardi Suhardi Verdian, Ihsan Wilianto Wilianto Winda Andrini Wulandari