Article Per Year (5 Year)
p-Index From 2021 - 2026
1.376
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Informatika Komputer Jurnal Ilmiah Teknik (JUIT) Jurnal Teknik dan Science (JTS) Jurnal Ilmiah Multidisiplin (JUKIM) Impression : Jurnal Teknologi dan Informasi
Erma Sova
Universitas Gunadarma
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
PEMANTAUAN KASUS PENYEBARAN COVID-19 BERBASIS WEBSITE MENGGUNAKAN FRAMEWORK REACT JS DAN API Tri Sulistyorini; Erma Sova; Rafli Ramadhan
Jurnal Ilmiah Multidisiplin Vol. 1 No. 04 (2022): Juli : Jurnal Ilmiah Multidisiplin
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (814.632 KB) | DOI: 10.56127/jukim.v1i04.137

Abstract

The world has been attacked by the pandemic of coronavirus, starts from 2019 until this day, 2022. Coronavirus was detected in Indonesia started from 2020, specifically on March, 2020. The coronavirus or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus which attacks human’s respiratory system. It is also known as COVID-19. The virus may cause mild illnesses of human’s respiratory system, severe lung infections, and even death. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is categorized as the new infectious disease to human. The virus attacks anyone, such as elderly, adult, children, toddler, pregnant women, and breastfeeding mothers. Utilization of information technology that continues to develop can be felt in various fields. Such as the fields of education, government, health, social culture and so on. Information about COVID-19 is always needed by the people of Indonesia, even abroad. Utilization of this website-based technology can help the public in obtaining up to date information. Website application built using React JS framework and API. According to the problems experienced now, a website was created to monitor and provide accessible information to the public regarding the spread of COVID-19 virus cases in Indonesia and the entire world as well. People could approach the website called Covices which was created in programming languages, such as React Js and API.
PEMANFAATAN NODEMCU ESP8266 BERBASIS ANDROID (BLYNK) SEBAGAI ALAT ALAT MEMATIKAN DAN MENGHIDUPKAN LAMPU Tri Sulistyorini; Nelly Sofi; Erma Sova
Jurnal Ilmiah Teknik Vol. 1 No. 3 (2022): September : Jurnal Ilmiah Teknik
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/juit.v1i3.334

Abstract

Internet of Things (IoT) is a concept that aims to expand the benefits of continuously connected internet connectivity. This study aims to utilize IoT in home automation and remote light control systems that can be operated with a smartphone application via an internet connection (WiFi). This system uses the NodeMCU ESP8266 module as a microcontroller, a light emitting diode (LDR) sensor as a controller for automating lights according to environmental conditions, and the Blynk smartphone application as a remote control for lights. The light control process can be carried out specifically on certain lamps and can be controlled by changes in ambient light in the morning and evening. The results show that when the LDR sensor gets minimal light, the light will be ON and vice versa the light will be OFF when more light intensity is received by the LDR. In addition, the Blynk application is able to control the lights remotely when connected to the internet network and, in this study, has been tested up to a distance of 2.7 km. It can be concluded that as long as the system is connected to WiFi stably and continuously, this control system can perform the task of turning on and off the lights independently when the owner is not at home.
APLIKASI GAME EDUKASI UNTUK MERANGSANG OTAK ANAK-ANAK DALAM MENGENAL DAN BELAJAR PENDIDIKAN AGAMA ISLAM MENGGUNAKAN CONSTRUCT 2 BERBASIS ANDROID Erma Sova
Jurnal Teknik dan Science Vol. 2 No. 2 (2023): Juni : Jurnal Teknik dan Science
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jts.v2i2.789

Abstract

Learning is quickly developed by several experts, both from professionals in this case are observers of children, namely those who work as psychologists supported by hardware and software makers from the computer field. This aims to stimulate children in accepting and recognizing learning methods that are fun and not boring, namely learning to play, especially for children with an age interval of 5-10 years. Because childhood is still a difficult playing period if invited to learn seriously. The method used in this study is using the MDLC (Multimedia Development Life Cycle) method with stages such as concept, design, material collection, manufacturing, testing and deployment. Making Islamic Religious Education Educational Game Applications using Construct 2 is able to help foster honest character, responsibility, respect for others and manners. Game application results provide fun entertainment and education for children aged 5-10 years, especially with the theme or educational background of the Islamic religion. This way of learning in the form of adaptation of learning while playing is very attractive to children.
PENERAPAN HYPERPARAMETER CONVOLUTIONAL NEURAL NETWORK (CNN) DALAM MEMBANGUN MODEL SEGMENTASI GAMBAR MENGGUNAKAN ARSITEKTUR U-NET DENGAN TENSORFLOW Tri Sulistyorini; Erma Sova; Nelly Sofie; Revida Iriana Napitupulu
Jurnal Ilmiah Informatika Komputer Vol 28, No 2 (2023)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2023.v28i2.6959

Abstract

Teknologi canggih membutuhkan keterampilan atau performa yang baik untuk memudahkan sebagian pekerjaan di era modern, yaitu dengan menggunakan pendekatan machine learning. Bidang machine learning telah mengalami perubahan yang impresif dengan adanya kemunculan Artificial Neural Network (ANN). Model komputasi ini terinspirasi oleh jaringan saraf biologis yang telah melampaui bentuk kecerdasan buatan pada machine learning pada umumnya. Salah satu arsitektur Artificial Neural Network (ANN) yang paling unggul yaitu Convolutional Neural Network (CNN). CNN pada umumnya digunakan untuk memecahkan masalah pengenalan pola berbasis gambar yang kemudian menghasilkan output yang cukup baik dalam hal kompleksitas sederhana. Tujuan penelitian  adalah untuk Menerapkan convolutional neural network yaitu U-NET dan penerapannya pada TensorFlow, pembuatan segmentasi gambar dengan deep learning yang diterapkan seperti pada Oxford-IIIT Pet Dataset, melakukan pencarian prediksi yang dilakukan dengan arsitektur U-Net untuk menghasilkan hasil yang baik atau malah sebaliknya, melihat perbandingan Predicted Mask dengan True Mask pada kelas kucing yang munculkan dalam bentuk skor IOU dan penerapannya menggunakan nilai batas bawah pada IOU. Metode penelitian adalah untuk mengenalkan machine learning, CNN, dan arsitektur U-NET yang awalnya dirancang untuk segmentasi gambar biomedis. Hasil prediksi yang dilakukan dengan arsitektur U-Net menghasilkan hasil yang baik, perbandingan Predicted Mask dengan True Mask pada kelas kucing yang mendapatkan skor IOU sebesar 0.933. Pada penerapan ini menggunakan batas bawah 0.5 pada IOU sehingga model ini dapat berjalan dengan baik
PENERAPAN SENSOR CAPACITIVE PROXIMITY DAN SENSOR INFRARED PROXIMITY PADA PERANCANGAN PEMILAH SAMPAHH ORGANIK DAN ANORGANIK Tri Sulistyorini; Nelly Sofi; Erma Sova; Mohammad Faizul Irsyad
Jurnal Ilmiah Multidisiplin Vol. 3 No. 06 (2024): November: Jurnal Ilmiah Multidisiplin
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/jukim.v3i06.1834

Abstract

Sampah merupakan sesuatu yang sudah tidak terpakai lagi atau sesuatu yang tidak disukai lagi dan dibuang dari sisa kegiatan manusia atau proses alam yang berbentuk zat organik anorganik, terurai tidak terurai. Sampah dapat dikelompokkan menjadi dua jenis yaitu sampah organik dan sampah anorganik. Membuang sampah berdasarkan jenisnya dapat menimbulkan dampak positif bagi lingkungan. Pemilahan sampah berdasarkan jenisnya sebelum dibuang memiliki peran penting dikarenakan pembusukan dari sampah menjadi sempurna. Tujuan penelitian ini adalah menerapkan sensor capacitive dan infrared proximity terhadap pembuatan tempat sampah yang dapat memilah jenis sampah organik dan anorganik. Selain itu Motor servo akan melakukan buka tutup tempat sampah setelah sensor capacitive proximity dan sensor infrared proximity mendeteksi sampah. Tempat sampah akan dideteksi penuh dengan menggunakan sensor ultrasonik dan buzzer akan mengeluarkan suara dengan tujuan agar tempat sampah dikosongkan. Semua komponen dihubungkan dengan kabel jumper ke Arduino Uno yang telah diprogram menggunakan Arduino IDE. Pengujian alat ini dilakukan dengan cara menghubungkan power bank ke Arduino Uno menggunakan kabel USB, menekan power on pada power bank dan semua komponen, yakni sensor capacitive proximity, sensor infrared proximity, motor servo, sensor ultrasonik, serta buzzer akan aktif berfungsi sesuai dengan tujuannya.
Studi Komprehensif Faktor Manusia, Kendaraan, Jalan, dan Lingkungan terhadap Kecelakaan Lalu Lintas Indonesia (2018–2023) Erma Sova; Jonathan Alexander Siahaan; Nanda Dhiarifqi Harahap; Hidarrahman Assidiqie
Impression : Jurnal Teknologi dan Informasi Vol. 5 No. 1 (2026): Maret 2026
Publisher : Lembaga Riset Ilmiah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59086/jti.v5i1.1377

Abstract

Kecelakaan lalu lintas merupakan permasalahan keselamatan publik yang serius di Indonesia karena menimbulkan dampak sosial dan ekonomi yang besar. Penelitian ini bertujuan menganalisis pengaruh faktor manusia, kendaraan, jalan, dan lingkungan terhadap tingkat kecelakaan lalu lintas di Indonesia periode 2018–2023. Penelitian menggunakan pendekatan mixed methods dengan desain explanatory sequential, di mana analisis kuantitatif dilakukan terlebih dahulu untuk mengidentifikasi pola dan hubungan antarvariabel, kemudian diperdalam dengan analisis kualitatif untuk menjelaskan temuan statistik. Data kuantitatif dianalisis menggunakan korelasi Pearson, regresi linier berganda, dan analisis spasial, sedangkan data kualitatif dianalisis secara tematik. Hasil penelitian menunjukkan bahwa faktor manusia merupakan penyumbang terbesar kecelakaan lalu lintas dengan kontribusi 81,5%, diikuti oleh faktor jalan (40%), kendaraan (28%), dan lingkungan. Analisis regresi menunjukkan bahwa keempat faktor tersebut secara simultan berpengaruh signifikan terhadap tingkat kecelakaan dengan nilai koefisien determinasi (R²) sebesar 0,72. Temuan ini menegaskan secara empiris pengaruh terpadu keempat faktor dalam kerangka sistem keselamatan jalan (Safe System). Implikasi kebijakan penelitian ini menekankan pentingnya prioritas intervensi keselamatan berbasis faktor dominan melalui peningkatan edukasi dan penegakan hukum, pengawasan kelaikan kendaraan, serta perbaikan infrastruktur pada titik rawan kecelakaan berbasis data.   Traffic accidents represent a serious public safety issue in Indonesia, generating significant social and economic impacts. This study aims to analyze the influence of human, vehicle, road, and environmental factors on the level of traffic accidents in Indonesia during the 2018–2023 period. The research employs a mixed methods approach with an explanatory sequential design, where quantitative analysis is conducted first to identify patterns and relationships among variables, followed by qualitative analysis to further explain the statistical findings. Quantitative data were analyzed using Pearson correlation, multiple linear regression, and spatial analysis, while qualitative data were examined through thematic analysis. The results indicate that human factors are the dominant contributor to traffic accidents, accounting for 81.5%, followed by road factors (40%), vehicle factors (28%), and environmental factors. Regression analysis shows that these four factors simultaneously have a significant effect on traffic accident levels, with a coefficient of determination (R²) of 0.72. These findings empirically confirm the integrated influence of the four factors within the road safety Safe System framework. The policy implications highlight the need to prioritize safety interventions based on dominant factors, including enhanced education and law enforcement, stricter vehicle roadworthiness supervision, and data-driven improvements to infrastructure at accident-prone locations.  
Chaos-Based Digital Image Encryption Using Arnold’s Cat Map Permutation and Duffing Map Diffusion: A Python Desktop Implementation Makmun Makmun; Edi Sukirman; Erma Sova; Muhamad Wahyudi
Jurnal Ilmiah Teknik Vol. 5 No. 1 (2026): Januari: Jurnal Ilmiah Teknik
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/juit.v5i1.2529

Abstract

Digital images are widely used for identification, communication, and information exchange, yet their large size, high pixel correlation, and uneven intensity distribution make them vulnerable to theft, manipulation, and statistical inference, thereby requiring encryption mechanisms tailored to image characteristics.Purpose: This study proposes a chaos-based permutation–diffusion scheme that combines Arnold’s Cat Map for pixel permutation and the Duffing Map as a keystream generator for diffusion to strengthen digital image encryption and improve resistance to unauthorized analysis. Methodology: An experimental quantitative approach was conducted through the development of a Python-based desktop application. Ten test images (RGB and grayscale) with varying resolutions were encrypted and decrypted using predefined key settings. Security and performance were evaluated using histogram analysis, entropy, pixel correlation, key sensitivity, processing time, and key space. Findings: The encrypted images exhibit near-uniform histograms, entropy values approaching the ideal for 8-bit images (≈8), and pixel correlation values close to zero, indicating strong statistical concealment. The scheme also demonstrates high key sensitivity, where small key changes prevent meaningful decryption, and a large key space that supports brute-force resistance. Processing time increases with image size but remains practically feasible for desktop implementation. Implications: The proposed scheme can be applied to protect sensitive image data in local desktop environments and image exchange scenarios, reducing risks of statistical attacks and brute-force attempts while maintaining acceptable runtime for common image sizes. Originality: This study delivers an end-to-end integration of Arnold’s Cat Map and the Duffing Map within a permutation–diffusion structure implemented as a Python desktop application, supported by structured security and efficiency evaluation, thereby providing a practical and reproducible contribution to chaos-based image cryptography.
Co-Authors Edi Sukirman Hidarrahman Assidiqie Jonathan Alexander Siahaan Makmun Mohammad Faizul Irsyad Muhamad Wahyudi Nanda Dhiarifqi Harahap Nelly Sofi Rafli Ramadhan Revida Iriana Tri Sulistyorini