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All Journal Annual Research Seminar Jurnal Ampere JETT (Jurnal Elektro dan Telekomunikasi Terapan) Indonesian Journal of Artificial Intelligence and Data Mining JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Sopian Soim
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Intelligent Transportation System dalam Sistem Monitoring Kecelakaan Lalu Lintas Hani Marta Putri; Ade Silvia Handayani; Sopian Soim; M. Ilham Akbar
Annual Research Seminar (ARS) Vol 4, No 1 (2018): ARS 2018
Publisher : Annual Research Seminar (ARS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

 Pada Paper ini menyajikan perancangan Intelligent Transportation System (ITS)  sebagai sistem monitoring kecelakaan lalu lintas. Sistem pada penelitian ini dirancang untuk secara otomatis mendeteksi kecelakaan lalu lintas menggunakan akselerometer dan data akustik, memberikan notifikasi kepada server tanpa selang waktu melalui pesandarurat setelah kecelakaan, dan   memberikan situasi pengemudi, koordinat GPS, saluran komunikasi video, dan perekaman data kecelakaan. Dalam perancangan ITS ini komponen yang mudah ditemui dan  praktis serta harga yang terjangkau. Strategi Pengendalian pada penelitian ini menggunakan metode fuzzy logic dengan memanfaatkan skema multi kriteria sehingga dapat memecahkan masalah yang memiliki nilai kompleks.  Adapun  kelebihan sistem ini ialah adanya panic button yang akan terhubung ke pihak pelayananmasyarakat apabila terjadi aktivitas yang mencurigakan atau keadaan darurat. Diharapkan dengan adanya aplikasi ini dapat meningkatkan keamanan dan keselamatan  berkendara danmengurangi angka kematian akibat kecelakaan lalu lintas
PERANCANGAN ROBOT HUMANOID BERBASIS MIKROKONTROLER ATMEGA 32 Sopian Soim; Bahri Joni; Junaidi Junaidi; Faisal Damsi
Jurnal Ampere Vol 1, No 2 (2016): JURNAL AMPERE
Publisher : Universitas PGRI Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31851/ampere.v1i2.898

Abstract

ABSTRAKRobot adalah sebuah alat mekanik yang dapat melakukan tugas fisik, baik menggunakan pengawasan dan kontrol manusia, ataupun menggunakan program yang telah didefinisikan terlebih dulu. Robot humanoid adalah robot yang mempunyai karakteristik menyerupai manusia. Perancangan suatu robot humanoid yang memiliki kemampuan bergerak seperti manusia dan menjaga keseimbangan. Pada perancangan robot ini manggunakan  mikrokontroler ATmega 32 sebagai sistem kontrol pergerakan robot,  motor servo yang terletak disetiap persendian kaki untuk pergerakan robot dan untuk posisi robot berdiri ketika jatuh menggunakan sensor gyro. Robot ini memiliki kemampuan berjalan kedepan, belok kesamping kiri dan juga kekanan yang dikontrol oleh mikrokontroler ATmega 32. Pada prinsipnya, robot humanoid yang dirancang  hanya robot dapat berjalan dan menjaga keseimbangannya namun dalam penelitian ini robot dapat berjalan dengan pengontrol masing-masing  sudut dari motor servo dan robot berdiri ketika jatuh parameternya posisi kemiringan dari badan robot terhadap referensi sumbu X dan sumbu Y. Kata kunci : Robot  Hummanoid,  Mikrokontroler, motor servo,
Aplication ADeV Aplikasi Air Detection Environment System (ADeV) Dalam Mendeteksi Kadar Kualitas Udara Di Area Parkiran Berbasis Android Ade Silvia Handayani; Al Fatur Sayid; Sopian Soim; Nyayu Latifah Husni; Rumiasih Rumiasih; Rosmalinda Permatasari
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 7 No 3 (2020): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v7i3.507

Abstract

This paper presents an application of Air Detection Environment System using Android that based on the WSN technology. This technology related to multiple sensors that could detect the air quality of environmental parking lot. The proposed application has been successful in detecting automatically the air quality of vehicle exhaust, such as CO, CO2, HC, PM10, temperature, and humidity. This multisensors technology can trasmit air quality data to servers and displays some menu, such as: the air quality status, the time, and the location of the event. This application will be benefit for the people to know the surround environmental condition practically, in real time and in mobile. It is due to they only need to have access to their smart application. It is expected that they will increase their safety and attention of to the unhealthy environmental qualities.
Implementasi CRISP-DM Model Menggunakan Metode Decision Tree dengan Algoritma CART untuk Prediksi Curah Hujan Berpotensi Banjir Msy Aulia Hasanah; Sopian Soim; Ade Silvia Handayani
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3200

Abstract

Indonesia is part of a tropical climate with high rainfall intensity. High rainfall intensity can potentially cause flooding. To minimize this, accurate weather predictions are needed to be able to anticipate beforehand. This research was conducted with the aim of classifying based on the rain category with the dichotomy of heavy rain and very heavy rain using data mining techniques with the CRISP-DM methodology. The algorithm used in the classification technique is CART (Classification And Regression Tree) with Confusion Matrix test parameters. Based on the results of the model evaluation, it shows that the CART algorithm has a fairly good performance in classifying with an accuracy value of 89.4%.
ANALISA LINK BUDGET DENGAN PERBANDINGAN PEMODELAN PROPAGASI PADA KOMUNIKASI SELULAR DAERAH URBAN Monica Pasu Aprilia Simarmata; Sopian Soim; Mohammad Fadhli
Jurnal Elektro dan Telekomunikasi Terapan (e-Journal) Vol 5 No 2: JETT Desember 2018
Publisher : Direktorat Penelitian dan Pengabdian Masyarakat, Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jett.v5i2.1989

Abstract

High increasingly the need for wireless communication is lncreasing the need for cellular communication system, especially in urban area. The propagation media of cellular communication is air, which is it affecting quality of communication. The important think in link budget calculation is to able to build good communication system. This research was conducted with the calculation and measurment of RSL, the result will be analyzed and can be determined the appropite propagation model to be implemented in urban area of Palembang. This research uses PCS Extension to Hata model and SUI model in pathloss calculation and uses drive test method with G-Net Track in acquisition of measurement data. The distance range specified in 500 – 1500 m and located on 5 different sites. Based on this research, the propagation model that appropriating in urban area that has been evaluated is SUI model.
Optimizing Malware Detection Using Back Propagation Neural Network and Hyperparameter Tuning Annisa Arrumaisha Siregar; Sopian Soim; Mohammad Fadhli
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 2 (2023): September 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i2.24731

Abstract

The escalating growth of the internet has led to an increase in cyber threats, particularly malware, posing significant risks to computer systems and networks. This research addresses the challenge of developing sophisticated malware detection systems by optimizing the Back Propagation Neural Network (BPNN) with hyperparameter tuning. The specific focus is on fine-tuning essential hyperparameters, including dropout rate, number of neurons in hidden layers, and number of hidden layers, to enhance the accuracy of malware detection. A Back Propagation Neural Network (BPNN) with dropout regularization is trained on an extensive dataset as part of the research design. Hyperparameter optimization is conducted using GridSearchCV, with experiments varying learning rates and epochs. The best configuration achieves outstanding results, with 98% accuracy, precision, recall, and F1-score. The proposed approach presents an efficient and reliable solution to bolster cybersecurity systems against malware threats.
Co-Authors Ade Silvia Handayani Al Fatur Sayid Annisa Arrumaisha Siregar Bahri Joni Faisal Damsi Hani Marta Putri Husni, Nyayu Latifah Junaidi Junaidi M. Ilham Akbar Mohammad Fadhli Monica Pasu Aprilia Simarmata Msy Aulia Hasanah Permatasari, Rosmalinda Rumiasih Rumiasih