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All Journal ComEngApp : Computer Engineering and Applications Journal Techno.Com: Jurnal Teknologi Informasi Telematika Jurnal Ilmiah Pangabdhi Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer InComTech: Jurnal Telekomunikasi dan Komputer EKONOMIS : Journal of Economics and Business JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JSiI (Jurnal Sistem Informasi) Journal of Information Technology and Computer Engineering Journal of Computer Science and Informatics Engineering (J-Cosine) Jurnal Telematika Multitek Indonesia : Jurnal Ilmiah KOMPUTIKA - Jurnal Sistem Komputer Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal Teknologi Komputer dan Sistem Informasi Jurnal Pendidikan dan Konseling Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JSR : Jaringan Sistem Informasi Robotik Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat JAPI: Jurnal Akses Pengabdian Indonesia Publikasi Hasil Pengabdian Kepada Masyarakat. Jurnal Karya Abdi Masyarakat Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Ilham Firman Ashari
Program Studi Teknik Informatika, Institut Teknologi Sumatera
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Nursing Public Health Social Sciences Other

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Monitoring and Control System of Server Devices Based on IoT Using Sugeno Fuzzy Achmad Syafriyal; Ilham Firman Ashari; Eko Dwi Nugroho
InComTech : Jurnal Telekomunikasi dan Komputer Vol 13, No 2 (2023)
Publisher : Department of Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/incomtech.v13i2.17132

Abstract

Fire is a disaster or disaster caused by a fire, it can happen anywhere and anytime. Server is a very important asset for owners of companies or institutions that implement information technology. The importance of a server in an agency is because the server has applications and databases that store all important and valuable information for the company. A server must have security standards that protect the work of the devices in it and one of them is the temperature on the server device must always be in good condition. For this reason, in this study, a system that can perform supervision and control related to temperature, smoke and fire levels and can send notifications of the state of the server device is safe or not using the fuzzy logic of the Sugeno method. From the test results, the system can determine various server device conditions with accuracy reaching 100%. In fuzzy testing, the percentage of success is 100%. This shows that the results of testing the fuzzy method on the system are in accordance with the design that has been made. The system can determine the condition of the server device (Safe, Standby, Danger).
ANALYSIS SENTIMENTS IN FACEBOOK DOWN CASE USING VADER AND NAIVE BAYES CLASSIFICATION METHOD Ilham Firman Ashari
MULTITEK INDONESIA Vol 16, No 2 (2022): Desember
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/mtkind.v16i2.5601

Abstract

Abstrak Facebook adalah media sosial terbesar di dunia. Semua aplikasi media sosial besutan Facebook tidak bisa diakses secara bersamaan dalam waktu kurang lebih 6 jam. Hal ini tidak hanya terjadi di Indonesia, tetapi di seluruh negara di dunia, pada tanggal 5-6 Oktober waktu Indonesia. Dengan adanya kasus ini, berbagai komentar dan opini dari masyarakat di Twitter terkait kasus Facebook pun turun. Komentar positif atau negatif bermunculan di twitter. Analisis sentimen digunakan untuk mengidentifikasi komentar positif dan negatif. Pada penelitian ini, komentar positif dan negatif akan diklasifikasikan menggunakan klasifikasi Vader dan nave bayes. Data yang terkumpul sebanyak 500 data dari twitter terkait down case facebook. Dari hasil perhitungan diperoleh sentimen positif sebanyak 33,92% dan sentimen negatif dengan hasil 66,08%. Berdasarkan hasil visualisasi dengan wordcloud, kata yang paling banyak muncul adalah kata facebook down untuk sentimen positif dan negatif. Hasil yang didapatkan dari tabel Confusion Matrix dari model klasifikasi menggunakan data sharing, 80% data training dan 20% data testing, dengan metode klasifikasi menggunakan Naive Bayes dengan pembobotan kata TF-IDF, nilai akurasinya sebesar 73,69% dan untuk Count Vektorizer adalah 70,18%. AbstractFacebook is the largest social media in the world. All social media applications made by Facebook cannot be accessed simultaneously in approximately 6 hours. This happens not only in Indonesia, but in all countries in the world, on October 5-6, Indonesian time. With this case, various comments and opinios from people on Twitter related to the Facebook case were down. Positive or negative comments popping up on twitter. Sentiment analysis is used to identify positive and negative comments. In this study, positive and negative comments will be classified using Vader and nave Bayes classification. The data collected was 500 data from twitter related to the Facebook down case. From the calculation results, positive sentiment was obtained as much as 33.92% and negative sentiment with 66.08% results. Based on the results of the visualization with wordcloud, the words that appear the most are the word facebook down for positive and negative sentiments. The results obtained from the confusion matrix table from the classification model using data sharing, 80% training data and 20% testing data, with the classification method using Naive Bayes with TF-IDF word weighting, the accuracy value is 73.69% and for the Count Vectorizer is 70.18%.
Analysis and Implementation of Blowfish and LSB Algorithm on RGB Images using SHA-512 Ilham Firman Ashari; Mugi Praseptiawan
Computer Engineering and Applications Journal Vol 13 No 1 (2024)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v13i1.450

Abstract

The growth of the internet globally keeps increasing as time goes. There's a big amount of data type saved there too. Those data need to be secured so anyone who doesn't have the right to access them can access it. The purpose of this article is to secure text information into image media using the Blowfish method for encrypting text information and securing it using the Hash function SHA-512 and then embedded it in image media using the Least Significant Bit (LSB) method. The result of implementing those methods using image media sized 138Kb and 39.85Kb with plaintext measuring 27 and 85 characters shows that integrity data is secured with SHA-512 method. The test result using PSNR method to get the score of image quality after embedding information to the image shows that the average number of PSNR’s score is 70,74 dB which means the quality is good and has less difference from the original image.
Empowerment of Partner Schools Through the Development of the Mini Bank Application (m-MiniBank) at SMKN 7 Bandar Lampung Mugi Praseptiawan; ilham Firman Ashari; Samsu Bahri; Meida Cahyo Untoro; Arre Pangestu; Aidil Afriasnyah; Muhammad Habib Algifari
Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Vol. 3 No. 9 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jppmi.v3i9.173

Abstract

SMKN 7 Bandar Lampung is an educational unit that manages a Mini Bank which is used for teaching factory practices in financial accounting practices, besides that it is also a school designated by the regional government of Lampung province which heads the Lampung regional public service agency (BLUD). The problems faced in the management of mini-banks are that the business processes are not running optimally, the transaction process is running manually, besides that the manager's capacity knowledge is also inadequate in managing it. The purpose of this community service activity is to develop the capacity and capabilities of partner schools through the development of the Mini Bank application. The empowerment method used is starting from identifying needs and problems, application design, implementation, testing, and finally evaluation. The result of this dedication is a mini bank application with testing carried out involving 10 respondents, the results of the UEQ (User Experience Questionnaire) test show the value of the efficiency aspect is 2.15, the accuracy aspect is 2.14, the clarity aspect is 2.44, the stimulation aspect that is 2.15 and the attractiveness aspect is 2.26 so that the scores on all aspects get an excellent score.
Hyperparameter Tuning Feature Selection with Genetic Algorithm and Gaussian Naïve Bayes for Diabetes Disease Prediction Ashari, Ilham Firman; Untoro, Meida Cahyo
Jurnal Telematika Vol. 17 No. 1 (2022)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v17i1.488

Abstract

Diabetes Mellitus is a disease that occurs due to disorders of carbohydrate, fat and protein metabolism associated with a lack of performance of insulin secretion. Diabetes is a degenerative disease that requires appropriate and serious treatment efforts. The effects lead to various complications of other serious diseases such as heart disease and stroke. Erectile dysfunction, kidney failure, nervous system damage, etc. Because there are so many impacts caused by diabetes, it is important to study this disease. The benefit of this study is to prevent the occurrence of severe complications and can help medical personnel in predicting this disease early and reduce the cost burden that arises due to this problem.  The purpose of this study is to determine the level of accuracy resulting from the use of feature selection with genetic algorithms and nave Bayes. In this study, predictions will be made using hyperparameter tuning with genetic algorithms and Naive Bayes optimization by performing feature selection. After conducting related research, it was found that the accuracy of 17 features using a genetic algorithm was better than modeling with 10 features. By using 17 features and hyperparameter tuning with genetic algorithm and naive Bayes modeling, the accuracy is 93.2%. By using 17 features without feature selection, the accuracy is 91.2%, there is an increase in accuracy of 1.5%.
DESIGN AND BUILD INVENTORY MANAGEMENT INFORMATION SYSTEM USING THE SCRUM METHOD Ashari, Ilham Firman; Aryani, Annisa Jufe; Ardhi, Alief Moehamad
Jurnal Sistem Informasi Vol 9 No 1 (2022)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v9i1.4050

Abstract

PT Telkom Akses (PTTA) is a subsidiary of PT Telekomunikasi Indonesia, Tbk (Telkom) which share owned entirely by Telkom. PT Telkom Akses is engaged in the business of providing construction services and network infrastructure management. Data collection manually can result in slow data management and will have an impact on the workflow of PT. Telkom Akses 3 Ilir Palembang. There will be a lot of damaged or duplicated data and finding data will be difficult. Therefore, it is necessary to develop a system that can collect data on incoming and outgoing goods, namely a Web-based Inventory System. The development of this inventory system uses the CodeIgniter3 Framework and Scrum methodology. Scrum is one of the methods that uses the Agile principal, which refers to team collaboration, product incremental, and iterative processes to achieve goals. The results of the evaluation of system testing using the black-box testing method show that the developed system can run well and as expected. Hopefully with the present of this system, it can help PT Telkom Akses 3 Ilir Palembang in performing incoming and outgoing goods data collection. Keyword: Inventroy System, Web, Codeigniter 3, Scrum, BlackBox Testing
Analisis dan Implementasi Sistem Monitoring Banjir Berdasarkan IoT Menggunakan Logika Fuzzy Sugeno Akbar, Alvijar; Clinton, Martin; Ashari, Ilham Firman
Komputika : Jurnal Sistem Komputer Vol 12 No 1 (2023): 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.v12i1.7089

Abstract

Flood disasters can have a detrimental impact such as damage to infrastructure, materials, and loss of life. One of the efforts that can be made to carry out early detection of flood disasters is to use a flood prediction system, where this system can monitor water levels, water flow rates, and predict real-time water increases. Information is sent to every citizen using the telegram chatbot. This system is built using several sensors and integrated with Telegram. The sensors used are ultrasonic and water flow sensors. The ultrasonic sensor is used to read the water level in the range of 0-50 cm and the water flow sensor is used to calculate the flow of water entering the test container with an interval of 0-10 liters / minute. Data is sent to telegram in realtime using the firebase database through NodeMCU ESP8266 and the WiFi module. The results of reading water level and water discharge data are processed using Sugeno fuzzy logic. The results obtained in this study indicate that the average error reading from the ultrasonic sensor is 2.43% or 97.58%. The water flow sensor shows an average error of 0.206 liters/minute or the percentage of tool accuracy is 87.06 %.
ANALISIS DAN PERBANDINGAN STEGANOGRAFI PADA MEDIA AUDIO DAN GAMBAR MENGGUNAKAN LSB DAN RC4 Ashari, Ilham Firman; Siwi, lkhsanudin Raka; Londata, Hafizh; Wicaksono, Ihtiandiko
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 7 No. 1 (2023)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v7i1.583

Abstract

In the current digital era, it is deemed essential to ensure security and confidentiality of information when exchanging information through communication networks. This is done to allow recipients to receive the information from senders in its entirety without any interference from third parties who are not entitled to the information. Cryptography and Steganography are some useful methods to secure a confidential message, including the RC4 algorithm as one type of applicable method to secure the original message into a random secret message to make it remain unknown to others. One of the methods used in steganography to secure messages, including images, audio, video, and documents, is the least significant bit (LSB) algorithm. This study aims to analyze the comparison of the two-storage media, namely audio and images using LSB and RC4 in order to see the effect of the LSB and RC4 algorithms on the container media based on the aspects of imperceptibility, fidelity, recovery, and capacity. Having tested the imperceptibility aspect as indicated by the histogram of the image and the audio spectrum, it is clear that there is no difference between the image and audio before and after insertion. The fidelity test of the PSNR (Peak Signal to Noise Ration) resulted in an average value of > 30 dB, while the recovery test shows 100% success because there is no difference between the original message and after extraction. The capacity test indicates that the larger the size of the container media, the larger the message that can be inserted.
Comparative Analysis of OpenMP and MPI Parallel Computing Implementations in Team Sort Algorithm Nugroho, Eko Dwi; Ashari, Ilham Firman; Nashrullah, Muhammad; Algifari, Muhammad Habib; Verdiana, Miranti
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.6409

Abstract

Tim Sort is a sorting algorithm that combines Merge Sort and Binary Insertion Sort sorting algorithms. Parallel computing is a computational processing technique in parallel or is divided into several parts and carried out simultaneously. The application of parallel computing to algorithms is called parallelization. The purpose of parallelization is to reduce computational processing time, but not all parallelization can reduce computational processing time. Our research aims to analyse the effect of implementing parallel computing on the processing time of the Tim Sort algorithm. The Team Sort algorithm will be parallelized by dividing the flow or data into several parts, then each sorting and recombining them. The libraries we use are OpenMP and MPI, and tests are carried out using up to 16 core processors and data up to 4194304 numbers. The goal to be achieved by comparing the application of OpenMP and MPI to the Team Sort algorithm is to find out and choose which library is better for the case study, so that when there is a similar case, it can be used as a reference for using the library in solving the problem. The results of research for testing using 16 processor cores and the data used prove that the parallelization of the Sort Team algorithm using OpenMP is better with a speed increase of up to 8.48 times, compared to using MPI with a speed increase of 8.4 times. In addition, the increase in speed and efficiency increases as the amount of data increases. However, the increase in efficiency that is obtained by increasing the processor cores decreases.
Optimizing Driving Completeness Prediction Models: A Comparative Study of YOLOv7 and Naive Bayes at Institut Teknologi Sumatera Algifari, Muhammad Habib; Ashari, Ilham Firman; Nugroho, Eko Dwi; Afriansyah, Aidil; Vebriyanto, Mario
Journal of Applied Informatics and Computing Vol. 7 No. 2 (2023): December 2023
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v7i2.6761

Abstract

The number of vehicles in Indonesia is increasing every year. The number of motor vehicle accidents in 2022 will be more than 100,000. It is hoped that several regulations regarding motorbike rider equipment will increase awareness of rider safety. By utilizing image recognition technology developed with artificial intelligence, it is possible to create digital image processing models or images that are fast and accurate for detecting driving equipment. The object detection model developed uses a dataset in the form of images of motorists who want to enter ITERA through the main gate. The object detection model will also be integrated with the classification model to create a program that can detect motorbike rider equipment, such as mirrors, helmets, not wearing a helmet, shoes, not wearing shoes, open clothes, and closed clothes. After detecting motorized rider equipment in the classification area, the results will be transferred to a classification model to determine the level of safety for motorized riders, either insufficient or sufficient safety. The test results show that the optimal object detection model was found at an epoch value of 70 with a batch-size of 16, producing a mAP value of 0.8914. The optimal classification model uses the naive Bayes method which has been trained with a dataset of 62 data and achieves an accuracy of 94%.
Co-Authors Achmad Syafriyal Adinda Sekar Tanjung Adrian Putradinata, Gusti Made Afriansyah, Aidil Agustine, Verlina Ahmad Auzan Varian Syahputra Aidil Afriansya Aidil Afriasnyah Ajrina, Fadiah Izzah Akbar, Alvijar Algifari, Muhammad Habib Alkarkhi, Makruf Anastasia Puteri Dewi Andhika Wibawa Bhagaskara Andika Setiawa Andika Setiawan Andre Febrianto Andrianto, Dodi Devrian Ardhi, Alief Moehamad Ardi Gaya Manalu Arimbi Ayuningtyas Arre Pangestu Aryani, Annisa Jufe Azwarman Azwarman Baraku, Randi Clinton, Martin Daniel Rinald Dede Rodhatul Farida Dita Alviuni P Dwi Nugroho, Eko Eka Nur'azmi Yunira Eko Dwi Nugroho Eko Dwi Nugroho Eko Dwi Nugroho Fadhillah A Fikri Halim Ch Filiana, Edinia Rosa Fil’aini, Raizummi Gunawan, Rayhan Fatih Hendri Tri Putra Idris, Mohamad Jaya Megelar Cakrawarty Laisya, Nashwa Putri Leonard Rizta Anugrah P Liwardana, Ridho Londata, Hafizh M. Daffa M. Fazar Zuhdi Majesty, Achmad Bany Marbun, Rustian Afencius Mastuti Widianingsih, Mastuti Muhammad Abdul Mubdi Bindar Muhammad Affandi Muhammad Afif H Muhammad Alfarizi Muhammad Najie K Muhammad Rizky Hikmatullah Muhammad Telaga Nur Muhammad Tyaz Gagaman Muhammad Yusuf Nashrullah, Muhammad Nazla Andintya W Nela Agustin Kurnianingsih Novri Yanda, Ilham Nur'azmi, Eka Nurhayati, Misfallah Nuril Humaya Perdana Raga Winata Praseptiawan, Mugi Prasetyawan, Purwono Radhinka Bagaskara Rahmat Setiawan Raidah Hanifah Raidah Hanifah Revangga, Dwi Arthur Ringgo Galih Sadewo Romantika Banjarnahor Salman Damanhuri Samsu Bahri Satria, Mahesa Darma Sekar A Sianturi, Elsa Elisa Yohana Sicilia Putri Aisyah Sinaga, Nydia Renli Sinaga, Rutlima Siraz Tri Denira Siregar, Abu Bakar Siddiq Sisilia Juli A Siwi, lkhsanudin Raka soleha, Ayu Sophia Nouriska Syamsyarief Baqaruzi Untoro, Meida Cahyo Utoro, Meida Cahyo Vanesa Adhelia Vebriyanto, Mario Verdiana, Miranti Verlina Agustine Vina Oktarina Wicaksono, Ihtiandiko Winda Yulita Yulita, Winda Yunira, Eka Nur'azmi Yusuf, M. Asyroful Nur Maulana