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All Journal Jurnal Ilmiah Informatika Komputer MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Elkom: Jurnal Elektronika dan Komputer INFORMAL: Informatics Journal E-Dimas: Jurnal Pengabdian kepada Masyarakat RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JITK (Jurnal Ilmu Pengetahuan dan Komputer) KOMPUTIKA - Jurnal Sistem Komputer JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Cyber Security dan Forensik Digital (CSFD) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jurnal Abdidas Indonesian Journal of Data and Science Jurnal Nuansa Akademik: Jurnal Pembangunan Masyarakat Jurnal Minfo Polgan (JMP) Buletin Sistem Informasi dan Teknologi Islam Ilmu Komputer untuk Masyarakat DEVOTE: Jurnal Pengabdian Masyarakat Global Jurnal (FORSINTA) Informatika, Sistem Informasi dan Kehutanan Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Celebes Journal of Community Services CSRID Jurnal Pengabdian Kepada Masyarakat Variable Research Journal Journal of Information Technology and its Utilization Linier: Literatur Informatika dan Komputer Journal of Computer Science & Intelligent Systems
Erick Irawadi Alwi, Erick Irawadi
Universitas Muslim Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Studi Forensik Digital: Analisis Bukti Video TikTok dengan Metode DFRWS Ahmad Qayyum Ibnu Hidayat; Erick Irawadi Alwi; Andi Widya Mufila Gaffar
Jurnal Minfo Polgan Vol. 13 No. 1 (2024): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v13i1.13966

Abstract

Perkembangan teknologi informasi telah memberikan dampak yang signifikan terhadap kehidupan manusia, baik dalam peningkatan kesejahteraan maupun sebagai medan untuk tindakan kriminal seperti penyebaran berita bohong. Di Indonesia, penanganan masalah ini melibatkan berbagai upaya hukum, termasuk pemblokiran situs web yang dianggap sebagai sumber informasi palsu berdasarkan isi kontennya. Data dari Kementerian Komunikasi dan Informatika menunjukkan peningkatan jumlah hoaks yang diidentifikasi dari tahun ke tahun, mencerminkan tantangan besar dalam mengelola komunikasi publik melalui media sosial.Penelitian ini bertujuan untuk menganalisis penyebaran konten video hoax yang terjadi di platform TikTok menggunakan metode Digital Forensic Research Workshop (DFRWS). Dalam penelitian ini, bukti digital yang dihapus berhasil direkonstruksi dari smartphone pelaku menggunakan alat forensik seperti wondershare dr.fone dan oxygen forensic. Hasil analisis menunjukkan bahwa bukti digital yang ditemukan termasuk video konten, pesan langsung, dan komentar yang ditinggalkan oleh pelaku. Proses analisis menggunakan metode DFRWS, yang terdiri dari enam tahapan, memberikan kerangka kerja yang sistematis untuk memeriksa bukti digital secara menyeluruh. Penelitian ini memberikan kontribusi dalam pemahaman tentang pentingnya bukti digital dalam proses hukum terkait penyebaran hoaks melalui media sosial, serta memperkuat metode analisis forensik yang diterapkan untuk memastikan keabsahan bukti dalam persidangan. Dengan demikian, penelitian ini menyoroti perlunya pendekatan yang efektif dalam penegakan hukum untuk mengatasi fenomena penyebaran hoaks yang semakin meresahkan masyarakat modern.
Implementation of Audio Forensic Methods in the Identification of Digital Evidence from Voice Recordings Izzahara Zalzabila; Erick Irawadi Alwi; Farniwati Fattah
NEXCORE: Journal of Computer Science & Intelligent Systems Vol. 1 No. 1 (2026): Article Reseach
Publisher : Soratekno Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59696/nexcore.v1i1.256

Abstract

The advancement of technology has increased convenience in various daily activities, but it has also heightened the potential for misuse in criminal acts such as fraud, corruption, theft, and the dissemination of hoax information. Digital evidence, including files, images, audio, and video, often plays a crucial role in criminal investigations. Each type of digital evidence requires a specific analytical method, one of which is audio forensics. Audio forensics is a sound analysis method aimed at enhancing speech clarity and reducing noise, thereby providing important clues in investigative processes. Tools such as Praat are used to compare allegedly manipulated voice recordings with original voice samples. This study aims to identify digital evidence in the form of voice recordings using Praat and audio forensic methods. By analyzing voice characteristics such as pitch, formant, and spectrogram, this research seeks to determine the similarity between evidentiary recordings and reference samples as well as to perform audio enhancement. The results indicate that in the pitch analysis stage, the samples of Yuki, Sakinah, Sonia, Marwah, and Salsa were identical to the evidence recordings. Furthermore, formant analysis revealed that the samples of Yuki, Sonia, and Salsa were identical to the evidence, while spectrogram analysis showed that only the Salsa sample matched the evidence recordings.
IMPLEMENTASI BLOCKCHAIN TERINTEGRASI ANDROID SEBAGAI IDENTITAS DIGITAL DALAM DSCUMI Muh. Rafianto; Erick Irawadi Alwi; St. Hajrah Mansyur
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7110

Abstract

Conventional digital identity systems often rely on centralized authorities that are vulnerable to data breaches and manipulation. The Developer Student Club Universitas Muslim Indonesia (DSC UMI) community requires a membership verification mechanism that is credible, secure, and preserves user privacy. This research aims to implement a decentralized digital identity system fully integrated on the Android platform using blockchain technology and Zero-Knowledge Proofs (ZKP), where the entire system logic—including blockchain interactions and cryptography—is processed independently on the client side (backendless) without dependence on intermediary servers. The development method applies a Minimum Viable Product (MVP) approach with a mobile-first architecture. The system is built on native Android using the Kotlin language, integrated with the Polygon Amoy Testnet network via the Web3j library. Authentication utilizes local biometric sensors to generate cryptographic proofs based on SHA-256 hashes without storing raw data on the server. White box testing results show that the application successfully connects to the MetaMask digital wallet, validates anti-duplication logic on the Smart Contract, and automatically issues a Soulbound Token (NFT) as legitimate proof of membership. In conclusion, blockchain integration on mobile devices is proven effective in delivering Self-Sovereign Identity (SSI) that is transparent and auditable without compromising the privacy of community member data.  
SISTEM PERSEDIAAN STOK BARANG MENGGUNAKAN METODE AGILE BERBASIS WEB PADA BENGKEL THO’BONE SHANTIKA; Erick Irawadi Alwi; St. Hajrah Mansyur
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.7174

Abstract

Inventory management at Bengkel Tho’Bone was previously conducted manually, which often resulted in data inconsistencies, delays in stock monitoring, and difficulties in generating accurate inventory reports. This study aims to design a web-based inventory management system using the Agile method as a software development approach to improve efficiency and accuracy in stock management. The study applies the CodeIgniter framework as the system development framework because it adopts the Model–View–Controller (MVC) architecture, which facilitates the separation of business logic, user interface, and data processing. The system development process is carried out through the stages of planning, design, development, testing, and evaluation, which are performed repeatedly according to user requirements. The system is designed to assist administrators and staff in managing item data, suppliers, as well as incoming and outgoing stock transactions. The results show that the developed system is capable of automating stock recording, providing restock notifications when inventory reaches the minimum threshold, and generating structured and easily accessible inventory reports. The implementation of this system improves operational efficiency, reduces human error, and enhances transparency in inventory management. Overall, the application of a web-based inventory management system using the Agile approach and the CodeIgniter framework has proven effective in optimizing inventory control and supporting accurate decision-making at Bengkel Tho’Bone.  
IMPLEMENTASI KARTU TANDA MAHASISWA DIGITAL BERBASIS BLOCKCHAIN Muhammad Ihsan; Erick Irawadi Alwi; Yulita Salim
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8084

Abstract

Identity management in higher education still generally relies on physical cards and centralized systems that are vulnerable to loss, forgery, and limited independent verification. This study aims to design and implement a blockchain-based digital student identity card system that supports integrated credential issuance, verification, and revocation. The study uses the Design Science Research Methodology (DSRM) through the stages of problem identification, design, prototype development, demonstration, and evaluation. The system is built using a hybrid architecture, in which student identity data are stored off-chain, while credential hashes and revocation status are recorded on-chain through a smart contract deployed on the Polygon Amoy Testnet. Credentials are issued in the form of JWT-based Verifiable Credentials and signed using the ES256K algorithm. The test results show that the system successfully implements its main functions, namely credential issuance, verification, and revocation. Performance testing also shows that verification can be carried out without incurring gas costs and with a response time that remains feasible for practical use. Overall, the developed system is feasible to support digital student identity services with better credential integrity and easier verification.  
Comparison of ResNet50 and ResNet101 Feature Extraction for Tea Leaf Disease Classification Using Support Vector Machine Wistiani Astuti; Erick Irawadi Alwi; Farniwati Fattah; Tasrif Hasanuddin; Julisa; Ulfa Sari; Ainur Rahma Almagfirah
Indonesian Journal of Data and Science Vol. 7 No. 2 (2026): Indonesian Journal of Data and Science
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v7i2.338

Abstract

Introduction: Tea leaf diseases can substantially reduce crop quality and productivity, making early and accurate diagnosis important for effective disease management. This study compares ResNet50 and ResNet101 as pretrained deep feature extractors combined with Support Vector Machine (SVM) to determine whether a deeper residual architecture can improve discrimination among visually similar tea leaf disease classes. Method: Images were obtained from the Kaggle “Identifying Disease in Tea Leaves” dataset comprising eight classes. Data augmentation increased each class to 800 images, yielding 6,400 images that were divided into training and testing sets using an 80:20 ratio. ResNet50 and ResNet101 pretrained on ImageNet were used as fixed feature extractors, and the resulting feature vectors were standardized and classified using an RBF-kernel SVM. Results and Discussion: ResNet101–SVM achieved the best performance with 97.97% accuracy and precision, recall, and F1-score of 98%, substantially outperforming ResNet50–SVM, which achieved 89.15% accuracy, 90% precision, 89% recall, and 89% F1-score. The deeper ResNet101 architecture provided more discriminative representations for visually similar disease patterns, although a small number of misclassifications remained. Conclusion: ResNet101 combined with SVM provides a more accurate and reliable framework than ResNet50–SVM for multi-class tea leaf disease classification and offers a promising foundation for automated disease diagnosis systems.
BISINDO Sign Letters Recognition Through HOG Features and Bagging Decision Tree Dolly Indra; Erick Irawadi Alwi; Faudiah Anwar; St. Nadya Kurnia Prihandani
Jurnal Ilmiah Informatika Komputer Vol. 30 No. 3 (2025)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2025.v30i3.57

Abstract

Sign language is one of the primary means of communication for people with hearing disabilities. BISINDO (Indonesian sign language) communicates using hand movements, among other things. One solution to this problem is to use image processing to recognize BISINDO letters A-Z based on hand movements. This study aims to create a BISINDO letter recognition system based on image processing using several stages, namely, preprocessing such as converting RGB images to grayscale images, then improving image quality by adjusting image contrast and removing noise with a median filter, HOG (Histogram of Oriented Gradients) feature extraction, and Bagging Decision Tree classification. A total of 156 images were used in the dataset, consisting of 104 letter images for training data and 52 letter images for test data. The data will be processed in the system as training data, and the dataset will then be stored in ‘mat’ format. Based on the results of testing Classification using Bagging Decision Tree, which produced an average accuracy rate of 86.5%. Thus, this research is expected to contribute to the development of BISINDO character recognition technology based on digital image processing.
Perancangan Sistem Keamanan Jaringan Intrusion Prevention System Menggunakan Suricata Dan IPTables Andi Rahmat Aulia; Erick Irawadi Alwi; Andi Widya Mufila Gaffar
LINIER: Literatur Informatika dan Komputer Vol 1, No 3 (2024)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/linier.v1i3.2500

Abstract

Server merupakan perangkat dalam jaringan telekomunikasi yang bertugas mendistribusikan perangkat lunak IPTables danbasis data. Salah satu tipe server yang rentan terhadap serangan Denial of Service (DoS) merupakan web server. SeranganDoS bekerja dengan menghabiskan sumber daya server sehingga menyebabkan server tersebut menjadi tidak dapat diaksesatau down. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan sistem pencegahan serangan denganmenggunakan Intrusion Prevention System (IPS) yang memanfaatkan Suricata dan IPTables sebagai mekanisme deteksidan pencegahan serangan DoS pada web server. IPS bekerja dengan menganalisis lalu lintas jaringan yang masuk dankeluar, melakukan inspeksi mendalam terhadap setiap paket data yang melintasi jaringan. Dengan penerapan Suricata danIPTables pada web server, administrator jaringan dapat memastikan keamanan web server dari ancaman serangan.Penelitian ini akan menunjukkan bahwa aturan Suricata dan IPTables efektif dalam mendeteksi serangan yang dilakukandengan alat Hping3, sebuah perangkat lunak yang digunakan untuk melakukan pemindaian jaringan dan secara defaulttersedia di Kali Linux yang akan dimanfaatkan untuk simulasi serangan DoS
Implementasi Metode Static Forensics Untuk Ekstraksi File Steganografi Pada Bukti Digital Menggunakan Framework NIST Asran Asran; Erick Irawadi Alwi; Huzain Azis
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7406

Abstract

Steganografi berfungsi sebagai teknik anti-forensik yang memungkinkan pelaku kejahatan menyembunyikan informasi dalam pesan lain, hal tersebut dapat menyulitkan penyelidik untuk menemukan bukti sebenarnya atas suatu kejahatan. Oleh karena itu, penyelidik harus mengenali dan memanfaatkan alat yang tepat untuk ekstraksi guna mengakses pesan yang melibatkan steganografi. Penelitian ini bertujuan untuk menganalisis bukti digital dengan menerapkan metode forensik statis berdasarkan kerangka kerja yang disiapkan oleh National Institute of Standards and Technology (NIST), penelitian ini juga berfokus pada proses ekstraksi file yang disusupi menggunakan steganografi, yang dilakukan berdasarkan skenario kejahatan. Alat yang dipakai dalam penelitian ini mencakup FTK Imager, Autopsy, HashMyFiles, USB Write Blocker, WinHex, Stegspy, serta InvisibleSecrets. Analisis proses ekstraksi menunjukkan bahwa, dari 10 file yang diperiksa sesuai dengan skenario kasus, 9 file berhasil diekstraksi dan menghasilkan tingkat keberhasilan sebesar 90%. Sebaliknya, 10% file yang tersisa tidak berisi data atau informasi tersembunyi yang relevan. Dari hasil tersebut dapat disimpulkan bahwa file steganografi yang berhasil diekstrak dapat dijadikan sebagai alat bukti materiil hukum yang sah.
Penerapan Metode Blockchain Untuk Verifikasi Ijazah Digital Menggunakan Pendekatan Hash Alghorithm Verification Miftahul Rifqi; Yulita Salim; Erick Irawadi Alwi
Jurnal Minfo Polgan Vol. 15 No. 3 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i3.16552

Abstract

Pemalsuan ijazah digital menjadi permasalahan yang dapat mengurangi kepercayaan terhadap keaslian dokumen akademik. Penelitian ini bertujuan mengembangkan sistem verifikasi ijazah digital berbasis blockchain untuk menjamin integritas dan keaslian dokumen. Sistem dibangun dengan mengintegrasikan algoritma SHA-256, Merkle Tree, digital signature, dan blockchain. Proses verifikasi dilakukan melalui pembangkitan hash dokumen, pembentukan Merkle Root, serta pencocokan Merkle Root dan digital signature dengan data referensi yang tersimpan pada blockchain. Pengujian dilakukan menggunakan 14 dokumen yang terdiri atas 1 ijazah asli dan 13 ijazah yang telah dimodifikasi pada berbagai komponen data. Hasil pengujian menunjukkan bahwa sistem mampu mengidentifikasi seluruh dokumen sesuai kondisi sebenarnya dengan Accuracy Verification Rate sebesar 100%. Setiap perubahan data menghasilkan nilai hash dan Merkle Root yang berbeda sehingga dapat dideteksi secara akurat. Hasil penelitian menunjukkan bahwa integrasi SHA-256, Merkle Tree, digital signature, dan blockchain efektif dalam meningkatkan keamanan, integritas, serta keandalan proses verifikasi ijazah digital.
Co-Authors Abd Hamid Ade Gustiyonoo Adhitya Nugraha Ahmad Qayyum Ibnu Hidayat Aidil Wijaya Kusuma Ainur Rahma Almagfirah Andi Rahmat Aulia Andy Aprianto Asman Haris Asran Asran As’ad, Ihwana Atmajaya, Dedy Dedy Atmajaya Diah Ayu Retnani Diah Ayu Retnani, Diah Ayu Dolly Indra Dolly Indra Farniwati Fattah Fathur Rahman Fatwa Hadi Ilham Pamungkas Faudiah Anwar Fifi Febrianti Usman Fitriyani Umar Gaffar, Andi Widya Mufila Gery Ardiansyah Saputra Hargiani, Fransisca Xaveria Hasanuddin, Tasrif Herdianti Herdianti Herman Herman Hidzrullah Ash Syuhrawardi Huzain Azis Ihramsari Akidah Ihwana As’ad Irawati Irawati Isnan Sinusi Izzahara Zalzabila Jasmaniar Jezika Anastazya Julisa Karina Fitriwulandari Ilham Lokapitasari Belluano, Poetri Lestari Lutfi Budi Ilmawan, Lutfi Budi M. Akil Maulana Nuruddin Djamin Miftahul Rifqi Mubarak Abdullah, Syahrul Muchlis Faulah Muh. Ainun Amri Mursalim Muh. Arsyil Karimi Muh. Rafianto Muh. Ridwan Rahim Muhammad Adam - Muhammad Al Mubarak Muhammad Arfah Asis Muhammad Ihsan Muhammad Syahrizal Darwis Murfat, Moh Zulkifli Mustika, Mustika Octavia Mutia Nurul Ilmi Nasrullah Syahir Nurmainna Nurmainna Nurul Ilmy Husain Purnawansyah Purnawansyah Rakha Raharja Ramdan Satra Ramdaniah Ramdaniah Riska Wulandari RM, Rusman Salsa, Salsabila Aurelia SHANTIKA Sheila Nur Afni Zafitri Siska Anraeni Siswahyudianto St. Hajrah Mansyur St. Nadya Kurnia Prihandani Syafie, Lukman Syahrul Mubarak Abdullah Syahrul Mubarak Abdullah Tasmil Tasmil Tasrif Hasanuddin Tasrif Hasanuddin Ulfa Sari Usman, Fifi Febrianti Wahyu Iriansyah Sopamena Wistiani Astuti Yudharta Arif Yulita Salim Zahra, Andi Fathimatuz Zahra