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Prototipe Sistem Kontrol Pemadam Kebakaran Pada Rumah Berbasis Arduino Uno dan ESP8266 Dolly Indra; Erick Irawadi Alwi; Muhammad Al Mubarak
Komputika : Jurnal Sistem Komputer Vol 11 No 1 (2022): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v11i1.4801

Abstract

Kebakaran merupakan salah satu kejadian yang mengganggu kenyamanan pemilik rumah. Ketika terjadi kebakaran tidak ada peringatan dini kepada pemilik rumah yang bersangkutan. Dalam penanganannya juga sering kita temui pihak pemadam kebakaran sendiri kesulitan untuk memadamkan api. Metode penelitian yang digunakan adalah penelitian eksperimen dengan melakukan uji coba pada alat untuk memadamkan kebakaran rumah dengan output yang diberikan berupa nyala api dan asap menggunakan modul sensor api dan sensor MQ7. Hasil pengujian pada sensor api didapatkan jarak maksimal mendeteksi nyala api sebesar 120 cm. Sensor MQ7 mendeteksi asap ketika kadar asap melebihi 100 PPM. Sensor DHT22 dapat membaca suhu ruangan dengan nilai akurasi 97,1%. Tingkat keberhasilan sistem ketika bekerja pada ruang tamu sebesar 100%, kamar 1 sebesar 100%, kamar 2 sebesar 100% dan kamar mandi 100%. Tingkat persentase rata-rata keberhasilan keseluruhan sistem dalam bekerja sebesar 100%. Kata Kunci – Arduno uno, kebakaran rumah, Esp8266, sensor api, MQ7, DHT22.
ANALISIS FORENSIK TERHADAP SERANGAN DDOS PING OF DEATH PADA SERVER Muhammad Adam -; Erick Irawadi Alwi; Ihwana As’ad
Cyber Security dan Forensik Digital Vol. 5 No. 1 (2022): Edisi Mei 2022
Publisher : Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/csecurity.2022.5.1.3423

Abstract

Abstrak Kemajuan teknologi yang terus berkembang bisa menjadi sebuah ancaman salah satunya pada bidang dunia maya dimana terdapat beberapa kejahatan cyber dengan caranya yaitu menurunkan kinerja web server Anda dengan membanjiri lalu lintas jaringan. Terlepas dari apa telah Anda lakukan untuk meningkatkan kinerja web server Anda, peretas masih dapat mensimulasikan lebih banyak pengguna daripada yang dapat ditangani oleh web server itu sendiri.  Pada data IDSIRTI bulan oktober 2020 total serangan mencapai 66 juta dan serangan DDoS dilakukan berdasarkan klasifikasi anomali mencapai 6 juta serangan. Peningkatan ancaman dan serangan terhadap keamanan sistem meningkat karena didukung oleh kemudahan akses dan ketersediaan sumber daya yang lebih mudah didapatkan. Banyak tahapan yang dapat dilakukan pelaku kejahatan cyber untuk memuluskan langkahnya mendapatkan informasi sebanyak mungkin pada target salah satunya adalah DDoS. Untuk memuluskan langkahnya biasanya dilakukan dengan menggunakan metode untuk membanjiri source pada perangkat jaringan.  Web server merupakan salah satu bagian dari sebuah jaringan dan seiring jalanya perkembangan zaman banyak sekali web yang tersebar atau bertebaran di internet dan bisa diakses, serangan intrusi sangat tidak diinginkan pada sistem karena bisa membahayakan kerahasiaan dan ketersediaan sumber daya yang ada jenis serangan terhadap sebuah web server menghabiskan sumber (resource) yang dimiliki.Masalah datang dimulai ketika paket data yang datang sangat banyak dan harus di analisis terhadap sebuah data. Pada penelitian ini akan melakukan sebuah serangan DDOS Ping Of Death pada sebuah web server yang dimana hasil dari sebuah penyerangan tersebut akan menciptakan data record yang terekam pada software snorby, data tersebut dibutuhkan untuk menjalankan forensik agar dapat mengumpulkan bukti digital dengan menggunakan metode forensik (NIST) yang meliputi collection,examination,analysis,reporting. Berdasarkan dari percobaan pengujian tahapan pemeriksaan menghasilkan bukti data oleh snorby tahapan analisis mendapatkan adanya serangan yang dilakukan oleh alamat IP 192.168.177.2 dengan jenis serangan DDOS Ping Of Death dan menyerang web server dengan alamat IP 103.229.73.105. Kata kunci: Web Server,Forensic,NIST, DDoS, Ping Of Death ------ Technological advances that continue to develop become a threat,which one is in the digital world where there are several cyber crimes by reducing the performance of your web server by flooding network traffic. Regardless of what you have done to improve the performance of your web server, hackers can still simulate more users than the web server itself can handled. IDSIRTI data October 2020, total attacks reached 66 million and DDoS attacks carried out based on anomaly classification reached 6 million attacks. Increased threats and attacks on system security are increasing because they are supported by easier access and the availability of resources that are easier to obtain. There are many stages that cyber criminals can smoothen their steps to get as much information as possible on the target, which one is DDoS. To smooth the steps are usually done by using a method to flood the source on the network device.The web server is one part of a network and as the times progress, there are lots of webs that are scattered on the internet and can be accessed, intrusion attacks are very undesirable on the system because they can endanger the confidentiality and availability of resources. spend the resources they have..The problem starts when the data packets come in are very large and must be analyzed against a data. In this study, DDoS Ping of death attack will be carried out on a web server where the results of an attack will create a data record that is recorded on the Snorby software, the data is needed to run forensics in order to collect evidence cyber crime using forensic methods (NIST). which is includes collection, examination, analysis, reporting. Based on the testing experiment, the inspection stage produced evidence of data by Snorby, the analysis stage found an attack carried out by the IP address 192.168.177.2 with the type of DDOS attack Ping of death. Keywords: Web Server,Forensic,NIST, DDoS, Ping of death
Analisis Bukti Digital Direct Message Pada Twitter Menggunakan Metode National Institute Of Justice (NIJ) Yudharta Arif; Erick Irawadi Alwi; Muhammad Arfah Asis
INFORMAL: Informatics Journal Vol 8 No 2 (2023): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v8i2.34025

Abstract

Twitter is a social media application that can be used on desktop, web and smartphone systems. The large number of Twitter users makes Twitter inseparable from cyber crimes, such as pornography, online gambling, hate speech and other crimes. The purpose of this study is to conduct a forensic investigation on the Twitter Direct Message (DM) application using the NIJ method and determine the success rate of forensic tools in finding deleted data. This study uses the National Institute of Justice (NIJ) method with the stages of identification, collection, examination, analysis, and reporting assisted by forensic tools to obtain digital traces that can be used as evidence. The results obtained from this study were the discovery of evidence of deleted chats and images on Twitter DMs with a success rate of forensic tools (Magnet AXIOM and MOBILEedit) in finding these evidences of 66.66%.
Klasifikasi Penyakit Tanaman Bawang Merah Menggunakan Convolutional Neural Network dan K-Nearest Neighbor Fifi Febrianti Usman; Purnawansyah; Herdianti Darwis; Erick Irawadi Alwi
Computer Science Research and Its Development Journal Vol. 15 No. 3 (2023): October 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The potential for yield loss due to shallot plant disease is the main trigger that can reduce agricultural productivity. Pest and disease attacks can be minimized and overcome quickly if farmers are able to classify the types of diseases that attack plants based on the characteristics and symptoms that appear. This study aims to classify shallot plant diseases, namely purple spotting and moles with a total of 320 datasets using Hue Saturation Value color feature extraction using the K-Nearest Neighbor (Euclidean Distance) and Convolutional Neural Network methods. Based on the results of the study, the accuracy, f1-score was 94% and precision, recal was 97%, 91% in purple spot disease while in moler disease it was 94% in accuracy, precision, recall, and f1-score in HSV and KNN classifications. Classification using HSV and CNN yielded high scores in accuracy, precision, recall, and f1-score with a value of 100% in both purple spot and moler shallot leaf diseases. Classification using deep learning CNN obtains very good accuracy, precision, recall and f1-score, namely 100%. With this description, the classification of shallot plant diseases using HSV and CNN, and CNN deep learning are stated to be able to classify shallot plant diseases, namely purple spotting and moles effectively and accurately.
Analisis Malware Hummingbad Dan Copycat Pada Android Menggunakan Metode Hybrid Nurul Qomariah; Erick Irawadi Alwi; Muhammad Arfah Asis
Cyber Security dan Forensik Digital Vol. 6 No. 2 (2023): Edisi Bulan November tahun 2023
Publisher : Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/csecurity.2023.6.2.4180

Abstract

Perkembangan teknologi yang terus berlanjut dapat menjadi ancaman di dunia maya, terutama dalam hal kejahatan cyber. Kemudian tingkat popularitas smartphone serta jumlah penggunanya meningkat dari tahun ke tahun. Sementara itu, smartphone dengan platform android masih menduduki peringkat pertama dalam persentase pengguna tertinggi di dunia. Karena itu, jumlah malware dan serangan berbahaya di platform android semakin meningkat. Pengembang aplikasi penipuan ini mengeksploitasi kekurangan platform android dengan menyuntikkan malware sebagai kode sumber ke dalam aplikasi android dan menyebarkannya melalui blog atau pasar aplikasi android. Teknik yang digunakan dalam penelitian ini adalah teknik hybrid yang menggabungkan metode statis dan dinamis. Penelitian ini menggunakan contoh malware HummingBad dan CopyCat. Penelitian ini memiliki tujuan untuk melakukan identifikasi dan analisis pada malware HummingBad dan CopyCat menggunakan metode hybrid menggunakan mobile security framework. Analisis yang dilakukan pada sampel malware HummingBad dan CopyCat menunjukkan bahwa sampel malware HummingBad memiliki tingkat keamanan 27/100 sedangkan untuk sempel malware CopyCat memiliki tingkat keamanan 38/100. Kata kunci: android, static, dynamic, analysis hybrid, malware ---------------------------------------------------------- The continued development of technology can become a threat in cyberspace, especially in terms of cyber crime. Then the level of popularity of smartphones and the number of users increases from year to year. Meanwhile, smartphones with the android platform are still ranked first in the highest percentage of users in the world. Because of this, the number of malware and malicious attacks on the android platform is increasing. Developers of these deceptive apps exploit the flaws of the android platform by injecting malware as source code into Android apps and spreading it via blogs or android app marketplaces. The technique used in this study is a hybrid technique that combines static and dynamic methods. This study uses the examples of HummingBad and CopyCat malware. This study aims to identify and analyze the hummingbad and copycat malware using a hybrid method using the mobile security framework. The analysis conducted on the HummingBad and CopyCat malware samples shows that the HummingBad malware samples have a security level of 27/100 while the CopyCat malware samples have a security level of 38/100. Keywords: android, static, dynamic, analysis hybrid, malware
ANALISIS REKAMAN VIDEO CCTV DENGAN TEKNIK ENHANCEMENT MENGGUNAKAN METODE NATIONAL INSTITUTE OF JUSTICE (NIJ) Erick Irawadi Alwi; Siska Anraeni
Elkom : Jurnal Elektronika dan Komputer Vol 17 No 1 (2024): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v17i1.1563

Abstract

Crime and criminality are increasing by utilizing electronic and digital devices, such as CCTV (closed circuit television) security devices, smartphones, and other electronic devices that have video features, record and store perpetrator data. CCTV recording files are sometimes unclear, so video forensic software is needed to clarify the object so that it can be used as evidence in court. The method used in this research is the National Institute of Justice (NIJ) method and enhancement techniques to clarify the image frame objects of CCTV video recordings using Amped Five forensic image and video tools. The results of the analysis of the evidence concluded that they had succeeded in identifying the vehicle number plate of the alleged perpetrator by carrying out an enhancement process (improving the quality) of the image object. The enhancement process is carried out by utilizing the optical debluring feature of the amped five forensic video software, in settings by increasing the size from 1 to 2 and increasing the noise value from 0.0100 to 0.6310 so it looks clearer than before.
Analisis Bukti Digital Pada Media Penyimpanan Flash Disk Menggunakan Metode National Institute Of Standards And Technology (NIST) Aidil Wijaya Kusuma; Erick Irawadi Alwi; Ramdaniah Ramdaniah
Cyber Security dan Forensik Digital Vol. 7 No. 1 (2024): Edisi Bulan Mei Tahun 2024
Publisher : Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/csecurity.2024.7.1.4345

Abstract

Dalam perkembangan teknologi digital yang semakin pesat, analisis bukti digital menjadi semakin penting dalam mendukung penegakan hukum dan mengamankan ranah keamanan siber. Proses analisis bukti digital melibatkan pemeriksaan terhadap berbagai informasi digital yang ditemukan dalam investigasi kejahatan atau kasus hukum. Bukti digital tersebut dapat berupa file, pesan teks, email, rekaman panggilan, atau data lainnya yang terdapat dalam perangkat digital seperti komputer, ponsel, dan tablet. Penelitian ini membahas tentang bagaimana memperoleh, mengambil, melestarikan, dan menyajikan data atau informasi tentang jejak aktivitas kasus cybercrime yang terdapat pada media penyimpanan flash disk yang telah dihapus dan bertujuan untuk mendukung penyelidikan terhadap pelaku kejahatan dengan menerapkan prinsip-prinsip forensik digital. Pada penelitian ini menggunakan metode National Institute of Standards dan Technology (NIST) dan menggunakan FTK Imager sebagai tool forensic dan Autopsy sebagai tools analisis dan juga recovery data serta HashGenerator untuk mengecek hasil hash dari tiap-tiap file. Dari hasil analisis yang telah dilakukan, didapatkan file-file yang telah dihapus oleh pelaku dengan perlakuan yang berbeda-beda pada media penyimpanan flash disk menggunakan tools forensik FTK Imager, Autopsy, dan juga HashGenerator, dimana tool Autopsy berhasil mendapatkan metadata file-file yang dihapus pada tanggal yang sama dengan tanggal pelaporan. Perbedaan dari masing-masing perlakuan penghapusan terdapat terdapat pada perlakuan ketiga yaitu dengan perintah quick format dimana nama file yang terhapus berubah menjadi nama file yang berbeda seperti nama file aslinya. Selain itu size dan nilai hash pada semua file pada tiap-tiap perlakuan tidak menunjukkan adanya perubahan pada nilai hash MD5-nya yang menandakan bahwa file-file tersebut tidak ditemukan adanya perubahan. Kata kunci: kejahatan siber, bukti digital, NIST, digital forensik, flash disk,  forensic tools. ------------------------------------------------------------ In the rapid advancement of digital technology, the analysis of digital evidence has become increasingly vital in supporting law enforcement and securing the realm of cybersecurity. The process involves scrutinizing various digital information found in criminal investigations or legal cases. Digital evidence can encompass files, text messages, emails, call recordings, or other data within digital devices such as computers, phones, and tablets. This research delves into the acquisition, retrieval, preservation, and presentation of data or information related to traces of cybercrime activities found on deleted flash disk storage media. The aim is to support investigations into criminal perpetrators by applying principles of digital forensics. The study utilized the National Institute of Standards and Technology (NIST) methodology, employing FTK Imager as a forensic tool, Autopsy for analysis and data recovery, and HashGenerator to verify the hash results of each file. From the analysis conducted, various files deleted by the perpetrator were discovered on the flash disk storage media, subjected to different treatments using forensic tools FTK Imager, Autopsy, and HashGenerator. Autopsy successfully retrieved metadata of the deleted files on the same date as the reporting date. Notable differences were observed among the deletion methods. Particularly, in the third method involving quick format, the deleted filenames were altered to different names similar to their original names. Additionally, the size and hash values of all files for each deletion method showed no alterations in their MD5 hash values, indicating that no changes had occurred to these files. Keywords: Cybercrime, Digital Evidence, NIST, Digital Forensics, Flash Disk,  Forensic Tools
Klasifikasi Penyakit Tanaman Bawang Merah Menggunakan Convolutional Neural Network dan K-Nearest Neighbor Usman, Fifi Febrianti; Purnawansyah; Herdianti Darwis; Erick Irawadi Alwi
CSRID (Computer Science Research and Its Development Journal) Vol. 15 No. 3 (2023): October 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.15.3.2023.177-188

Abstract

The potential for yield loss due to shallot plant disease is the main trigger that can reduce agricultural productivity. Pest and disease attacks can be minimized and overcome quickly if farmers are able to classify the types of diseases that attack plants based on the characteristics and symptoms that appear. This study aims to classify shallot plant diseases, namely purple spotting and moles with a total of 320 datasets using Hue Saturation Value color feature extraction using the K-Nearest Neighbor (Euclidean Distance) and Convolutional Neural Network methods. Based on the results of the study, the accuracy, f1-score was 94% and precision, recal was 97%, 91% in purple spot disease while in moler disease it was 94% in accuracy, precision, recall, and f1-score in HSV and KNN classifications. Classification using HSV and CNN yielded high scores in accuracy, precision, recall, and f1-score with a value of 100% in both purple spot and moler shallot leaf diseases. Classification using deep learning CNN obtains very good accuracy, precision, recall and f1-score, namely 100%. With this description, the classification of shallot plant diseases using HSV and CNN, and CNN deep learning are stated to be able to classify shallot plant diseases, namely purple spotting and moles effectively and accurately.
ANALISIS REKAMAN VIDEO CCTV DENGAN TEKNIK ENHANCEMENT MENGGUNAKAN METODE NATIONAL INSTITUTE OF JUSTICE (NIJ) Erick Irawadi Alwi; Siska Anraeni
Elkom: Jurnal Elektronika dan Komputer Vol. 17 No. 1 (2024): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v17i1.1563

Abstract

Crime and criminality are increasing by utilizing electronic and digital devices, such as CCTV (closed circuit television) security devices, smartphones, and other electronic devices that have video features, record and store perpetrator data. CCTV recording files are sometimes unclear, so video forensic software is needed to clarify the object so that it can be used as evidence in court. The method used in this research is the National Institute of Justice (NIJ) method and enhancement techniques to clarify the image frame objects of CCTV video recordings using Amped Five forensic image and video tools. The results of the analysis of the evidence concluded that they had succeeded in identifying the vehicle number plate of the alleged perpetrator by carrying out an enhancement process (improving the quality) of the image object. The enhancement process is carried out by utilizing the optical debluring feature of the amped five forensic video software, in settings by increasing the size from 1 to 2 and increasing the noise value from 0.0100 to 0.6310 so it looks clearer than before.
ANALISA KEAMANAN WEBSITE TERHADAP SERANGAN HTML INJECTION MENGGUNAKAN METODE PENETRASION TESTING M. Akil; Erick Irawadi Alwi; Syahrul Mubarak Abdullah
VARIABLE RESEARCH JOURNAL Vol. 1 No. 01 (2024): APRIL 2024
Publisher : Media Inovasi Pendidikan dan Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk mengidentifikasi dan menganalisa kerentanan HTML Injection pada website Jakarta Globe menggunakan metode Penetrasion Testing. Dalam penelitian ini terdapat beberapa tahap dalam pengumpulan data. Hasil dari analisa kerantanan yang sudah dilakukan menggunakan metode penetrasion testing terhadap domain https://jakartaglobe.id/ terdapat celah kerentanan diantaranya yaitu kode HTML Injeksi hanya mengizinkan injeksi tag HTML tertentu, ketika website tidak menangani data yang disediakan pengguna dengan benar, penyerang dapat memberikan kode HTML yang valid.