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All Journal JOIV : International Journal on Informatics Visualization JURNAL ILMIAH INFORMATIKA Warta Pengabdian Jurnal Informatika Universitas Pamulang MIND (Multimedia Artificial Intelligent Networking Database) Journal Jurnal ICT : Information Communication & Technology JISKa (Jurnal Informatika Sunan Kalijaga) JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Journal of Innovation Information Technology and Application (JINITA) Innovation in Research of Informatics (INNOVATICS) Informatics and Digital Expert (INDEX) Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Ilmu Komputer untuk Masyarakat Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) International Journal of Informatics and Computing
Rizal, Randi
Informatika, Universitas Siliwangi, Tasikmalaya
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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Journal : Innovation in Research of Informatics (INNOVATICS)

 1 
Sistem Kendali dan Monitoring Pada Rumah Pintar Berbasis Internet of Things (IoT) Ruuhwan Ruuhwan; Randi Rizal; Indra Karyana
Innovation in Research of Informatics (INNOVATICS) Vol 1, No 2 (2019): September 2019
Publisher : Informatika Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v1i2.877

Abstract

The Smart Home system consists of control, monitoring and automation devices that can be accessed from anywhere as long as there is an internet connection. In Smart Home, several devices or home appliances that can be accessed through android-based applications such as temperature monitoring, gas intensity, fire identification and automatic monitoring of door conditions. This research aims to design and create a smart home system based on the IoT concept. The research methodology uses an experimental methodology. The design of this system is made using an Android smartphone, Arduino microcontroller, Ethernet shield, relay module, fire sensor, temperature sensor (LM35), gas sensor (MQ6), and magnetic sensor. The results of this study are monitoring and control systems on smart homes by utilizing an already available Web service called Teleduino. This web service functions as an intermediary between an Android device and the Arduino microcontroller. The Arduino Microcontroller requires an additional device called the Ethernet Shield to connect Arduino to the Internet that is connected directly to the Teleduino web service.
Perbandingan Algoritma Naïve Bayes Classifier dan Algoritma Decision Tree untuk Analisa Sistem Klasifikasi Judul Skripsi Rasi Nuraeni; Aso Sudiarjo; Randi Rizal
Innovation in Research of Informatics (INNOVATICS) Vol 3, No 1 (2021): Maret 2021
Publisher : Informatika Universitas Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v3i1.2976

Abstract

Penelitian ini mengkaji tentang perbandingan klasifikasi judul skripsi menggunakan algoritma naïve bayes classifier dan algoritma decision tree. Tujuan dari penelitian ini adalah untuk membandingkan dua algoritma dalam pengklasifikasian judul skripsi. Proses pengumpulan data dilakukan dengan cara studi pustaka dan literature sejenis. Hasil pengumpulan data akan di analisis dengan menggunakan algoritma naïve bayes classifier dan algoritma decision tree dengan tools rapidminer. Hasil penenlitian ini menemukan perbandingan yang cukup signifikan dengan hasil akurasi 80,33% untuk algoritma naïve bayes classifier dan 60,33% untuk algoritma decision tree dari 52 data judul skripsi yang digunakan.
Performance Comparison of Response Time Native, Mobile and Progressive Web Application Technology Rochim, Rachma Verina; Rahmatulloh, Alam; El-Akbar, R Reza; Rizal, Randi
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 5, No 1 (2023): Maret 2023
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i1.7045

Abstract

The development of technology in web-based applications is growing, this creates new problems. The web technology that is currently being discussed is Progressive Web Application (PWA) but is the PWA's performance better than the previous technology. This research is about measuring the performance of the Native Web, Mobile Web and PWA using three testing tools, namely GTMetrix, Lighthouse, and Chrome DevTool. The results of this study show how to measure the performance of a Progressive Web Application (PWA), where PWA can beat the performance of Native Web and Mobile Web if a web page is tested more than once. Test results on the Progressive Web Application (PWA), the minimum number of page files (home) is 217 kB with page loading time of 638 ms, while the medium page (about) is 431 kB with page loading time of 646 ms, and when accessing heavy pages (news) with a size of 41700 kB the page load time is 532 ms.
Data Integrity Testing of Digital Evidence Data Capture Results on Private Cloud Computing Services Komarudin, Arif Maulana; Widiyasono, Nur; Aldya, Aldy Putra; Rizal, Randi
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 5, No 2 (2023): September 2023
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v5i2.8420

Abstract

Private Cloud has better advantages than other cloud services because private cloud is managed and run by the company itself so that cloud needs can be tailored to the company's needs, but allows abuse from within the company itself, as in the case study simulation of a Gojek startup company. This case occurred because of a security weakness in the system so that internal people took advantage of these weaknesses for their own benefit by leaking confidential data, acquisitions were carried out to prove and find evidence of crime, acquisitions used live acquisition techniques, namely acquisitions on an ongoing system, namely monitoring network traffic using Wireshark tools , the method in this case uses the Digital Forensics Investigating Framework (DFIF), data integrity must be properly maintained when acquiring digital evidence because to maintain the authenticity of the digital evidence obtained, then data integrity is tested on the digital evidence obtained, testing is carried out on digital evidence before and after the acquisition to see if there is a change in data integrity, the research results show that there is no change in data integrity.
Stabilization of Image Classification Accuracy in Hybrid Quantum-Classical Convolutional Neural Network with Ensemble Learning Oumarou, Hayatou; Siradj, Yahdi; Rizal, Randi; Candra, Fikri
INNOVATICS: International Journal on Innovation in Research of Informatics Vol 6, No 1 (2024): March 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i1.10437

Abstract

Stabilization of Image Classification Accuracy in Hybrid Quantum-Classical Convolutional Neural Network Model with Ensemble Learning. Image classification plays a significant role in various technological applications, such as object recognition, autonomous vehicles, and medical image processing. Higher accuracy in image classification implies better capabilities in recognizing and understanding visual information. To enhance image classification accuracy, a Hybrid Quantum-Classical Convolutional Neural Network (HQ-CNN) model is developed by integrating quantum and classical computing elements with ensemble learning techniques. Compared to conventional neural networks, HQ-CNN enriches feature mapping in image classification predictions. The research results with HQ-CNN using ensemble learning demonstrate impressive and stable accuracy, with the lowest deviation being 1.1037.
Co-Authors Alam Rahmatulloh Aldya, Aldy Putra Amien, Nashihun Candra, Fikri El-Akbar, R Reza Faisal Muhammad Dzikry Gunawan, Rohmat Indra Karyana Komarudin, Arif Maulana Mohd. Zaki Mas’ud Nugraha, Cindera Syaiful Nur Widiyasono, Nur Nursihab, Cucu Oumarou, Hayatou Pendit, Ulka Chandini Purwayoga, Vega Rahmi Nur Shofa Ramli, Nuraminah Rasi Nuraeni Rianto Rianto Rianto, Rianto Rifki Maulana Insan Rizal Kurniawan Rochim, Rachma Verina Ruuhwan Ruuhwan Selamat, Siti Rahayu Septian Chandra Siti Annisa, Siti Siti Rahayu Selamat Sudiarjo, Aso Tiara Komala Sutra, Melanda Yahdi Siradj Yusuf Sumaryana