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All Journal Jusikom : Jurnal Sistem Komputer Musirawas Jurnal Informatika Global Journal of Information Systems and Informatics
Tasmi, Tasmi
Universitas Indo Global Mandiri
Computer Science & IT

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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
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 : Asosiasi Doktor Sistem Informasi Indonesia

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.
Design of Additional Safety Locks for Motor Vehicles Using RFID Herri Setiawan; Tasmi Tasmi; Dhamayanti Dhamayanti
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.620

Abstract

Indonesia, facing the dual challenges of rapid economic development and rising vehicle theft rates due to economic inequalities, has prompted a need for innovative security solutions in the automotive sector. This research aims to address this growing concern by introducing a sophisticated motor vehicle security system utilizing Radio Frequency Identification (RFID) technology. The proposed system employs RFID keys, which use ID tag cards as unique identifiers to activate motor vehicles. The methodology centers around the integration of RFID technology with a microcontroller, creating a security system that is both advanced and user-friendly. This system includes an alarm feature that is triggered when an ID tag card not registered with the vehicle's RFID is used, providing an additional layer of security against unauthorized access. The results of implementing this system have been promising. Testing revealed that the RFID locks, when combined with the microcontroller, effectively recognized authorized ID tag cards and successfully denied access when unauthorized cards were used. The alarm system also functioned as intended, activating when discrepancies in ID tag data were detected. This integration of RFID with a microcontroller not only enhanced the security of motor vehicles but also contributed to a significant reduction in vehicle thefts in the community, showcasing the potential of RFID technology as a viable solution to the prevalent issue of vehicle security in Indonesia.
Advanced Techniques for Anomaly Detection in Blockchain: Leveraging Clustering and Machine Learning Ferdiansyah Ferdiansyah; Usman Ependi; Tasmi Tasmi; Muhammad Haikal; Mikko Mikko
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i1.1047

Abstract

Blockchain technology has revolutionized data security and transaction transparency across various industries. However, the increasing complexity of blockchain networks has led to anomalies that require further investigation. This study aims to analyze anomalies in blockchain systems using machine learning approaches. Various anomaly detection techniques, including supervised and unsupervised methods, are evaluated for their effectiveness in identifying irregularities. The results indicate that machine learning models can detect anomalies with high accuracy, providing insights into potential threats and system vulnerabilities. The findings of this research contribute to improving blockchain security and developing more robust monitoring systems.
STUDI PERFORMA DAN EXPLAINABILITY JARINGAN SYARAF TIRUAN UNTUK PERAMALAN CUACA MENGGUNAKAN METODE LIME Rachmansyah; Ricky Maulana Fajri; Tasmi Tasmi; Sumi Amariena Hamim
Jusikom : Jurnal Sistem Komputer Musirawas Vol. 10 No. 1 (2025): Jusikom : Jurnal Sistem Komputer Musirawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusikom.v10i1.2655

Abstract

Accurate weather prediction is crucial to support various sectors such as agriculture, transportation, and disaster mitigation. Artificial Neural Networks have been proven to improve the accuracy of weather forecasts through their ability to capture complex nonlinear patterns in atmospheric data. However, the complexity of these artificial neural networks architectures often results in decisions that are non-transparent and difficult for end users to understand. To address this issue, this study examines the effectiveness of the Local Interpretable Model-agnostic Explanation (LIME) method in providing local explanations for weather predictions generated by the artificial neural networks. The study uses historical meteorological data and evaluates the interpretability of prediction results for several key weather variables. Experimental results show that LIME is capable of identifying the most influential features affecting the model's decisions, as well as providing human-understandable insights into the prediction logic. These findings reinforce the importance of integrating explainability methods into artificial neural network-based weather prediction systems to enhance user trust and support more informed decision-making.
Co-Authors Dhamayanti Dhamayanti Ferdiansyah Ferdiansyah Herri Setiawan Herri Setiawan Husnawati Husnawati Mikko Mikko Muhammad Haikal Rachmansyah Reza Maulana Ricky Maulana Fajri Sumi Amariena Hamim Usman Ependi