Tasmi Tasmi, Tasmi
Department of Mathematics, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132, Indonesia

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NETWORK FORENSIK UNTUK MENGANALISA TRAFIK DATA GAME ONLINE Tasmi, Tasmi; Antony, Fery; 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
Be Wise With Your Waste: Penyuluhan Sampah Dan Evaluasi Usability Aplikasi Pengelolaan Sampah Untuk Siswa Sekolah Menengah Atas Di Jakarta Selatan Suharti, Suharti; Yunita, Ariana; Tasmi, Tasmi; Adharis, Azis; Mayangsari, Tirta Rona; Ratri, Paramita Jaya; Berghuis, Nila Tanyela; Muttaqin, Muttaqin; Sofiyah, Evi Siti; Fuqaha, Hafizh; Istadewi, Berliani; Afiq, Muhammad; Sakinah, Nanda; Fauziyah, Andanda Reza
Jurnal Pengabdian Masyarakat Bakti Parahita Vol. 4 No. 02 (2023): Jurnal Pengabdian Masyarakat Bakti Parahita
Publisher : Universitas Binawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54771/jpmbp.v4i02.1193

Abstract

Indonesia merupakan penyumbang sampah plastik terbesar ketiga di dunia pada tahun 2020, dimana DKI Jakarta merupakan salah satu kota penyumbang sampah terbesar di Indonesia. Untuk menangani sampah plastik diperlukan kerjasama dari berbagai pihak, baik dari masyarakat, akademisi, pemerintah dan organisasi. Tanpa kontribusi publik, penanganan sampah terutama sampah plastik akan sulit. Tujuan kegiatan ini adalah untuk meningkatkan kesadaran masyarakat untuk memilah dan menangani sampah, sebagai upaya untuk meningkatkan kontribusi publik. Pada kegiatan ini, salah satu aplikasi pengelolaan sampah diperkenalkan dan dilakukan evaluasi usability untuk mengetahui seberapa mudah digunakan aplikasi tersebut. Kegiatan dilakukan pada 50 siswa salah satu Sekolah Menengah Negeri Atas Negeri (SMAN) di Jakarta Selatan. Hasil dari kegiatan ini menunjukkan bahwa siswa-siswa berminat untuk menggunakan aplikasi pengelolaan sampah, tetapi masih mengalami kesulitan dalam menggunakan aplikasi pengelolaan sampah. Selain itu, sebagai tindak lanjut dari penyuluhan ini, tempat sampah untuk memisahkan sampah plastik juga diletakkan di sekolah tersebut sebagai tindak lanjut dari penyuluhan ini.
Design of Additional Safety Locks for Motor Vehicles Using RFID Setiawan, Herri; Tasmi, Tasmi; Dhamayanti, Dhamayanti
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

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; Ependi, Usman; Tasmi, Tasmi; Haikal, Muhammad; Mikko, Mikko
Journal of Information System and Informatics Vol 7 No 1 (2025): March
Publisher : Universitas Bina Darma

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.
ANALISIS PERILAKU PENGGUNA TERHADAP AKSES INTERNET DI PT CHIYODA INTERNATIONAL INDONESIA MENGGUNAKAN MACHINE LEARNING Agustani, Adi; Setiawan, Herri; Tasmi, Tasmi
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.6594

Abstract

Akses internet merupakan faktor penting dalam kelancaran operasional perusahaan. PT Chiyoda International Indonesia yang sangat bergantung pada infrastruktur TI dan konektivitas internet, menjadi objek dalam penelitian ini. Tujuan utama penelitian adalah menganalisis pola perilaku pengguna dalam mengakses internet melalui penerapan teknik machine learning menggunakan metode K-Means berbasis Python . Data yang dianalisis berasal dari lebih dari 10.000 entri aktivitas internet selama enam bulan, mencakup lima departemen utama. Hasil analisis elbow plot menunjukkan bahwa tiga cluster merupakan jumlah optimal, dengan penurunan nilai inersia sebesar 65% dibandingkan konfigurasi awal. Klasterisasi menunjukkan bahwa 40% pengguna tergolong dalam intensitas tinggi (rata-rata 4,5 jam/hari), 35% intensitas sedang (3 jam/hari), dan 25% intensitas rendah (1,5 jam/hari). Analisis visualisasi cluster plot mengungkap perbedaan signifikan antar departemen, terutama dalam jenis aplikasi yang diakses. Departemen dengan intensitas tertinggi cenderung menggunakan aplikasi non-produktif seperti media sosial dan streaming . Temuan ini menjadi dasar penting bagi perusahaan dalam mengoptimalkan alokasi bandwidth dan menetapkan kebijakan pengawasan akses. Penelitian ini diharapkan memberikan kontribusi strategi dalam pengelolaan sumber daya digital secara efisien di era transformasi teknologi.
STUDI PERFORMA DAN EXPLAINABILITY JARINGAN SYARAF TIRUAN UNTUK PERAMALAN CUACA MENGGUNAKAN METODE LIME ,, Rachmansyah; Fajri, Ricky Maulana; Tasmi, Tasmi; Hamim, Sumi Amariena
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.
Comparative Analysis of Mathematical Models: A Case Study of Used Smartphone Price Depreciation Chandrawisesa, Muhammad Nezha Alfatah; Safitri, Annisa Rizky; Almuzakki, Muhammad Zaki; Tasmi, Tasmi
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 2 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i2.3469

Abstract

The price depression of the smartphone after it becomes used is one of the factors that consumers should consider when buying used smartphones. Therefore, accurate prediction of the price of used smartphones becomes a better insight into marketing strategies, and consumer purchasing decisions. The study aims to compare the performance of the Holt-Winters model damped, logistical decay, and exponential decay to predict the price depression of used smartphones. This research method uses historical data from some used smartphone prices as a basis for analysis. Comparisons between the three models were made to assess the performance of each in representing price depression behavior. Then, a statistical analysis was conducted to determine the most optimal model in predicting the price depression of used smartphones, the optimity of a model measured by the accuracy and speed of the computer performing the model execution. The accuracy measure in this study is the mean square error (MSE) value generated by a model with historical data alignment based on the ratio to the price when the smartphone has not been indicated as usable and the execution speed measure is the time it takes a computer to execute the model. The results show that the Holt-Winters damped model provides the most optimal predictive results compared to the exponential and decay models. This is demonstrated by the lower MSE average value twice as low as compared with the other two models, on the other hand, the holt-winters Damped has the weakness of requiring the longest average execution time of the three models with an average performance speed of 2.7 seconds, but the shortfall is not fatal because the predicted time period in this case is monthly so there is no urgency to advance the speed of seconds rather than accuracy.