Garuda - Garba Rujukan Digital

Classification is one method in image processing. Image processing to search for similar images or with similarity ownership is called image matching or image matching. In the measurement of image matching, the original and fake logo objects are used. Ide Dewi Astria Faroek; Rusydi Umar; Imam Riadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 2 (2022): April 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The random noise signal is widely used as a test signal to identify a physical or biological system. In particular, the Gaussian distributed white noise signal (Gaussian White Noise) is popularly used to simulate environmental noise in telecommunications system testing, input noise in testing ADC (Analog to Digital Converter) devices, and testing other digital systems. Random noise signal generation can be done using resistors or diodes. The weakness of the noise generator system using physical components is the statistical distribution. An alternative solution is to use a Pseudo-Random System that can be adjusted for distribution and other statistical parameters. In this study, the implementation of the Gaussian distributed pseudo noise generation algorithm based on the Enhanced Box-Muller method is described. Prototype of noise generation system using a minimum system board based on Cortex Microcontroller or MCU-STM32F4. The test results found that the Enhanced Box-Muller (E Box-Muller) method can be applied to the MCU-STM32F4 efficiently, producing signal noise with Gaussian distribution. The resulting noise signal has an amplitude of ±1Volt, is Gaussian distributed, and has a relatively broad frequency spectrum. The noise signal can be used as a jamming device in a particular frequency band using an Analog modulator.

Analisis Penerimaan Terhadap Penerapan Sistem E-Learning Menggunakan Technology Acceptance Model (TAM) Tuska Abe; Anton Yudhana; Imam Riadi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2212

E-laerning is an electronic media that functions as a tool to facilitate students in absorbing and obtaining material. The e-learning system itself has been implemented in Talam West Huamual High School as a learning aid, but the application of the e-learning system students need to familiarize themselves with the learning system that has just been studied by previous learning media. the purpose for assessing the level of students of the level of acceptance of e-learning systems in schools. This study involved 35 students as respondents in the West Huamual Talaga High School. The model uses the technology acceptance model (TAM). The data analyzed in this study used descriptive analysis according to category and percentage. Based on the results of the study that showed e-learning system of West Talaga huamual high school for user-suitable analysis according to the category of "strongly agree" "Strongly agree" according to the percentage of 98.09%.

Penerapan JST Backpropagation untuk Prediksi Siswa Penerima Bantuan Supriyanto Supriyanto; Sunardi Sunardi; Imam Riadi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3870

The role of education is to educate students and build quality human resources. School Operational Assistance (BOS) from the government is used to relieve students, not free schools but free students from school fees and extracurriculars. BOS can be used to provide scholarships to underprivileged students. Students are entitled to a scholarship if they meet three conditions, namely not having a Smart Indonesia Card (KIP), not having a Prosperous Family Card (KKS), and parental income of less than one million rupiah per month. The determination of BOS scholarship recipients is based on an agreement and joint decision by the management team, the teacher council, and the school committee. The process of determining students as scholarship recipients often encounters obstacles because it is done manually. This study applies backpropagation ANN to determine students who are eligible for BOS scholarships. The system is built based on the web using bootstrap as a framework, Javascript, and PHP. The training process uses a sample of 78 students with input architecture 4, hidden 6, output 1, learning rate 0.7, momentum 0.9, SSE 0.1, output 1, and a maximum of 10,000 iterations, an error of 0.03 is obtained. Testing with 21 student data obtained an error of 0.414923 and the accuracy of the test was 93.67%. The test results using the cause-effect graph technique can display the training process, graphs, error results, weight values and testing time with 93.67% success.

Optimization of System Authentication Services using Blockchain Technology Imam Riadi; Herman Herman; Aulyah Zakilah Ifani
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 6, No. 4, November 2021
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v6i4.1325

With the development of the era, one thing that must be considered for security is the Login System. In most cases, user login information is stored on the server. This gives access to sensitive informatio, many hackers easily break into data from users. Based on these problems, this research focuses on data security authentication in the form of usernames and passwords in the login system. Authentication using blockchain is used to reduce malicious access and increase security for the authentication process. One of the innovative technologies that can solve these problems is Blockchain Technology. Using blockchain technology, hackers will find it difficult to change and modify the same data on all computers at the same time because it takes a very long time to crack the encryption code on each block of data in the entire computer network. Data storage or transactions in the blockchain are stored in the form of hashes. This makes it difficult for hackers to break into it. Tests in this study using Wireshark tools and network miner. Based on the research conducted, the test was conducted as many as 5 times with two scenarios, namely authentication of the login system before using the blockchain and after using the blockchain. The results obtained. The, system built using blockchain can secure data. The test results obtained that data in the form of usernames and passwords were converted into hashes and with the immutable nature of the blockchain, data from users could not be changed or replaced by anyone.

Analisis Forensik Digital Storage pada Owncloud Drive Dewi Estri Jayanti; Rusydi Umar; Imam Riadi
Jurnal Repositor Vol 2 No 8 (2020): Agustus 2020
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v2i8.968

Penyimpanan data saat ini dapat menggunakan model Cloud. Cloud dapat di akses oleh beberapa user yang telah dibuatkan akun oleh admin. Semua aktivitas user terekam di history cloud. Tindak kejahatan dapat dilakukan dengan menghapus semua data penting yang ada pada Owncloud Drive yakni Nextcloud menggunakan salah satu admin dan menghapus histori pada cloud. Penelitian ini melakukan analis investigasi untuk mengethui siapa pelaku dan mengembalikan data yang sudah terhapus. Proses forensik digital storage pada owncloud drive (Nextcloud) dapat menggunakan metode dari National Institute of Standard and Technology (NIST) yang merupakan metode digital forensik yang digunakan secara umum oleh para peneliti di dunia. NIST dikembangkan untuk menyelesaikan simulasi kasus penyalahgunaan owncloud drive menggunakan skenario 5 akun yang terdiri dari satu admin dan user, pelaku melakukan kejahatan mengambil lalu menghapus data pada akun admin. Tahapan digital forensik NIST yakni pengumpulan data, pemeriksaan, analisis dan pelaporan. Berdasarkan proses investigasi yang dilakukan didapatkan laporan terkait pelaku kejahatan yang telah menghapus semua data penting yakni laporan keuangan, foto dokumentasi rahasia, dan beberapa data lainnya. Sebesar 75% data yang terhapus didapatkan kembali. Hasil penelitian ini juga didapatkan keterangan jejak pelaku kejahatan yang dibutuhkan sebagai barang bukti.

Analisis Keamanan Sistem Informasi Akademik Menggunakan Open Web Application Security Project Framework Muh. Amirul Mu'min; Abdul Fadlil; Imam Riadi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4099

Information system security is one of the important things in the development of technology to protect comprehensive and structured data or information. The Academic Information System (SIA) has a service to receive requests in the form of HTTP or HTTPS protocol website pages from clients called browsers. Intruders can hack websites without the owner's knowledge. This research was conducted to find the vulnerability of SIA STIKES Guna Bangsa Yogyakarta. The framework used is the Open Web Application Security Project (OWASP) which is usually used to evaluate systems or applications. The tools used are WhoIs, SSL Scan, Nmap, and OWASP Zap. The results obtained were finding 12 vulnerabilities with four vulnerabilities at the medium level, namely Absence of Anti-CSRF Tokens, Cross-Domain Misconfiguration, Missing Anti-clickjacking Header, and Vulnerable JS Library, six at the low level namely Cookie Without Secure Flag, Cookie without SameSite Attribute, Cross-Domain JavaScript Source File Inclusion, Server Leaks Information via "X-Powered-By" HTTP Response Header Field(s), Timestamp Disclosure – Unix, and X-Content-Type-Options Header Missing, and two at the informational level namely Content-Type Header Missing and Information Disclosure - Suspicious Comments.

Pengembangan Layanan Kependudukan Dan Pencatatan Sipil Menggunakan Algoritma Naïve Bayes Anton Yudhana; Imam Riadi; M Rosyidi Djou
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4515

The “pick-up ball service” program or commonly called mobile services is a form of developing services for the Population and Civil Registration Service (disdukcapil), especially Alor NTT Regency, which aims to reach people who have difficulty getting services due to various obstacles, including due to long distances and difficult access to service centers. Disdukcapil is an implementing agency in the district that is obliged to ensure that all residents, both Indonesians and foreigners, are recorded in the population database, have a NIK, and population documents. In its implementation, not all villages can be served due to insufficient time and funds, so it is necessary to select villages that are worthy of being served by “ball pick up service” or mobile service programs. So far, the determination of villages that are worthy of the program is still determined manually so that it is inseparable from the element of subjectivity. In this study, a classification method was used in data mining using the naïve bayes algorithm. Naïve bayes is one of the algorithms that is able to predict well by calculating the probability of each class and comparing them, Naïve bayes is used to calculate probability values from training data so that it can predict which villages are feasible for the program. The study used 25 training data taken from previous dukcapil service data and data on the distance and difficulty of access to the village, which were tested and simulated using the naïve bayes algorithm of weka software. The purpose of this study was to obtain accurate information about the villages in Alor district that deserve the program. The results of the process using WEKA software found that from 25 tuples used as test data, it resulted in 100% accuracy .

Analisis Sentimen HateSpeech pada Pengguna Layanan Twitter dengan Metode NaÃ¯ve Bayes Classifier (NBC) Murni Murni; Imam Riadi; Abdul Fadlil
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5984

In January 2023, Twitter users experienced a significant increase of 27.4% compared to the previous year. The social media platform Twitter is commonly used to share various types of information. One type of information frequently shared by users is Hate Speech. Hate Speech involves the dissemination of messages that nurture feelings of hatred and hostility towards specific individuals or groups, including ethnicity, religion, race, and other categories. Forms of Hate Speech encompass insults, defamation, blasphemy, provocation, incitement, and the spread of fake news. In order to address the potential for division and threats to Indonesia's unity, sentiment analysis capable of categorizing tweets as Hate Speech or Non-Hate Speech is necessary. This research aims to conduct sentiment analysis on Hate Speech tweets posted by Twitter users using the NaÃ¯ve Bayes Classifier method. The dataset consists of 5000 samples processed using the Python programming language. Data processing stages involve preprocessing (including case folding, tokenization, stopword removal, normalization, and stemming), labeling, and assigning word weights (Term Weighting) using the Term Frequency (TF) and Inverse Document Frequency (IDF) methods. The data is then divided into training and testing sets, with three different data splits: 70% training and 30% testing, 30% training and 70% testing, and 50% training and 50% testing. Evaluation using the Confusion Matrix yields the highest accuracy of 81%, precision of 81%, recall of 100%, and F1-Score of 90% in the 70% training and 30% testing data split.

Forensik Video Pada CCTV Menggunakan Framework Generic Computer Forensics Investigation Model (GCFIM) Imam Riadi; Anton Yudhana; Rachmad Very Ananda Saputra
JURIKOM (Jurnal Riset Komputer) Vol 10, No 2 (2023): April 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v10i2.5888

The level of crime recorded by CCTV (Closed Circuit Televison) cameras continues to increase, criminals who are proven to have committed certain criminal acts will be punished in accordance with statutory regulations. The problem is how a case recorded on a CCTV camera can be used as digital evidence at trial. And how to handle it if there is evidence that has been manipulated or changed by irresponsible parties to eliminate traces of digital evidence. Digital evidence is closely related to ensuring the security, privacy and integrity of data when following the stages of the forensic digital identification process. The identification model using the Generic Computer Forensic Investigation Model (GCFIM) Framework is used for the investigation stage in finding information related to video recording metadata on CCTV cameras, in order to provide structured and valid information to be accepted in court as digital evidence. The results of this study obtained information on the data testing process using the Generic Computer Forensic Investigation Model (GCFIM) framework and for the metadata analysis process using two tools, namely exiftool and mediainfo. Testing is done on the original video and tempering video. Regarding the metadata of the original video and tempering video, there is a very significant difference in the size of the original video 4.6Mb while the tempering video is 4.2Mb, the duration of the original video is 38s for the tempering video 32s and the modification date / time for the original video 2020:03:21 while the tempering video is 2022:08:04. It can be concluded that exiftool and mediainfo can be utilized to obtain metadata information from data, with the aim of strengthening digital evidence at the time of trial regarding the validity of the data

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