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All Journal PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Informatika Global Journal of Information Systems and Informatics Klik - Jurnal Ilmu Komputer
Tasmi, Tasmi
Universitas Indo Global Mandiri
Computer Science & IT Engineering

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Implementation of Android Smartphone as CCTV Camera Based on Wifi Network Herri Setiawan; Tasmi Tasmi; Husnawati Husnawati
Journal of Information System and Informatics Vol 2 No 2 (2020): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/journalisi.v2i2.97

Abstract

The Security systems using cameras as monitors or what is commonly known as Closed Circuit Television (CCTV) have recently become more prevalent. However, to have a monitoring system or monitoring requires a fairly expensive cost to buy hardware and installation services. On the other hand, the development of mobile devices is increasingly being used, such as smartphones and tablets. The ease of carrying and the variety of applications available such as WIFI devices and a series of other applications and at relatively affordable prices have made this mobile device more and more in demand by the public today. This research is based on the idea of ​​creating a CCTV camera application using a smartphone that is always with us. This use will be useful for seeing the state of the room or certain places and can be monitored directly using the Android mobile device itself or from a Laptop / PC / Tablet and others.
Sistem Pendukung Keputusan Pemilihan Dosen Terbaik Dengan Metode Simple Additive Weighting (SAW) Berbasis Web Herri Setiawan; Husnawati Husnawati; Tasmi Tasmi
Journal of Information System and Informatics Vol 3 No 4 (2021): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v3i4.215

Abstract

Lecturers are academic staff in charge of planning and implementing the learning process, assessing learning outcomes, conducting guidance and training, as well as conducting research and community service. Lecturers are entitled to promotions and awards according to their academic performance. The selection of the best lecturers at STIKES Al Su'Aibah Palembang was carried out using several factors. The assessment is based on the performance assessment of each lecturer, namely knowledge of work, creativity, planning, quality of work, cooperation, attendance and attitudes towards other lecturers/employees. This study aims to build a decision support system that has the ability to analyze the selection of the best lecturers using the Simple Additive Weighting (SAW) method, where each criterion in this case the assessment factors and alternatives in this case the lecturers are compared with one another. so as to provide output values ​​that produce a system that provides an assessment of each lecturer. This decision support system helps evaluate each lecturer, changes the criteria, and changes the weight value. This is useful to facilitate decision makers related to the problem of selecting the best lecturers, so that the lecturers who are most worthy of being given rewards or awards will be obtained.
Visualisasi Trafik Jaringan Dengan Metode Support Vector Machine (SVM) (Studi Kasus: Universitas Indo Global Mandiri) Tasmi Tasmi; Reza Maulana; Husnawati Husnawati
Jurnal Informatika Global Vol 12, No 2
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v12i2.1939

Abstract

Limited network resources and the increasing number of internet users in the current digital era have an impact on high traffic which results in decreased access speed to internet services. This is also a problem that occurs at the Indo Global Mandiri University (UIGM) Palembang, causing access to academic services to be slow. The purpose of this research is to identify the types of network traffic patterns which are then carried out by the process of grouping and visualizing these types of traffic. The data in this study were taken in real-time at the UIGM campus. The data obtained is the result of responses which are then extracted. The extraction results are processed using the Support Vector Machine (SVM) method for the process of grouping and visualizing data. The results of this study can distinguish types of traffic based on communication protocols, namely tcp and udp, where the results of the experiment were carried out six times with the results being the first experiment where 99.7% TCP and 0.1% for UDP, the second experiment 97.6% for TCP and 1.1% for UDP , trial three 99.7 % TCP and 0.2% UDP, trial four 97.5% and 1.3% UDP, trial five 99.5 TCP and 02% UDP, and the sixth or final try 97.7% TCP and 1.1% UDP. The data from the use of the SVM method obtained several types of traffic such as games by 0.4%, mail 0.2%, multimedia 0.4% and the web by 82.8% and this research still produces data that the pattern is not yet recognized by 15.5% Keywords : Network Traffic, Classification, Support Vector Mesin
NETWORK FORENSIK UNTUK MENGANALISA TRAFIK DATA GAME ONLINE Tasmi Tasmi; Fery Antony; Ubaidillah Ubaidillah
Klik - Jurnal Ilmu Komputer Vol. 3 No. 1 (2022): Klik - Jurnal Ilmu Komputer
Publisher : Fakultas Ilmu Komputer Universitas Sumatera Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56869/klik.v3i1.352

Abstract

Network forensics adalah salah satu cara dalam menganalisi jenis trafik dalam sebuah jaringan adalah dengan menggunakan file log dengan merecord aktifitas pada jaringan. File log disetiap sistem sering dipakai untuk media melihat aktifitas pada sebuah sistem, terkhusus pada sebuah router dan server file ini sangat diperlukan proses investigasi analisis forensik jaringan dengan menggunakan metode Generic Network Forensics Process Model yang merupakan ilmu digital forensik yang berkaitan dengan tahap-tahap untuk menemukan sumber serangan dan mendapatkan bukti-bukti serangan yang bersumber dari file log. Tujuan dari penelitian ini dapat menerapkan model network forensic dalam memonitoring trafik games-online dan dapat menghasil satu sistem yang dapat menentukan prioritas memberian bandwidth, dan juga dapat dijadikan sebagai salah satu dasar pengambilan keputusan dalam membagian bandwidth. Hasil penelitian yang telah dilakukan telah mampu menganalisi jenis trafik game online dengan menggunakn tool wireshark untuk sniffing packet data serta membaguan sebuah sistem autentikasi untuk memvalidasin user pengguna jaringan. Pada tahap awal penelitian ini hasil investigasi forensik jaringan. Berdasarkan hasil pengujian tersebut dapat dinyatakan hasil sudah sesuai dengan tujuan yang diharapkan, sehingga dapat disimpulkan penelitian ini berhasil berjalan dengan baik
Local Government Project Assessment Application Using Group Decision Support System (GDSS) Model Herri Setiawan; Dhamayanti Dhamayanti; Tasmi Tasmi
Journal of Information System and Informatics Vol 4 No 4 (2022): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v4i4.410

Abstract

The assessment process is an important step in the evaluation, as it underlies the successful evaluation of a project. One solution to make the project assessment more objective is to apply the concept of a Group Decision Support System (GDSS), which in the decision process uses computing. This research tries to implement the concept by building an application for project evaluation and providing recommendations on project performance in local government agencies. The proposed Decision Makers (DMs) are involved: Executives of Government Institutions, Project Management Work Units, Business Process Owner Units, and Communities represented by the DPRD. The computational process uses the Multi-Criteria Decision Making (MCDM) method, and the Copeland scores voting method ranks the project of all DMs. The results of application computing in implementing GDSS and MCDM indicate that the process of determining project rankings will be faster and more accurate.
Pengenalan Pola Serangan pada Internet of Thing (IoT) Menggunakan Support Vector Mechine (SVM) dengan Tiga Kernel Tasmi Tasmi; Ferry Antony; Dhamyanti Dhamyanti; Herri Setiawan; Fali Oklilas
Jurnal PROCESSOR Vol 18 No 2 (2023): Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2023.18.2.1457

Abstract

Internet of things (IoT) technology is very popular these days around the world, with the development of IoT technology raises the impact of security threats and attacks on IoT devices. One of the most is the theft of data and information, one form of threat in IoT is malware. This research uses attacks in the form of bontet to detect attacks on the Internet of Things IoT) and uses Machine Learning to perform data detection of attacks on IoT devices. The method used in this research is Support Vector Mechine (SVM) by comparing three kernels namely Liner, polynominal and Radial Basis Function (RBF). This method is used to determine the level of accuracy in the detection process and compare between kernels. The results obtained are the accuracy value of 0.997 for the liner kernel, meaning that this kernel is able to separate the classes well, while the Polynomial kernel accuracy value of 0.993 is good in separating classes even though the value is smaller than the liner. Meanwhile, the RBF (Radial Basis Function) kernel has an accuracy of 1.0 (100%).
Co-Authors Dhamayanti Dhamayanti Dhamyanti Dhamyanti Fali Oklilas Ferry Antony Fery Antony Herri Setiawan Herri Setiawan Herri Setiawan Husnawati Husnawati Reza Maulana Ubaidillah Ubaidillah