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All Journal Teknika: Jurnal Sains dan Teknologi Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Ilmu Administrasi Negara (JUAN) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Tekinkom (Teknik Informasi dan Komputer) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) JINAV: Journal of Information and Visualization Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer ARRUS Journal of Engineering and Technology JURNAL ILMIAH GLOBAL EDUCATION Conten : Computer and Network Technology Brilliance: Research of Artificial Intelligence PENA ABDIMAS : Jurnal Pengabdian Masyarakat NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Pengabdian Masyarakat Waradin Sejahtera: Jurnal Inspirasi Mengabdi Untuk Negeri Indonesian Research Journal on Education Jurnal Manajemen Teknologi dan Sistem Informasi Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Pengabdian Multidisiplin Indonesia SISFOTENIKA INOVTEK Polbeng - Seri Informatika
Gagah Dwiki Putra Aryono
Universitas Bina Bangsa
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PENGGUNAAN ENERGI RAMAH LINGKUNGAN PANEL SURYA SEBAGAI PEMBANGKIT LISTRIK PADA DESA KALUMPANG Gagah Dwiki Putra Aryono
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 4 No. 4 (2023): Volume 4 Nomor 4 Tahun 2023
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v4i4.18886

Abstract

PLTS atau Pembangkit Listrik energi surya ialah alat-alat pembangkit listrik yg meru- bah cahaya mentari menjadi listrik. PLTS sering jua disebut Solar Cell, atau Solar Photovolta- ic, atau Solar Energy. Dengan konsep yg sederhana yaitu membarui cahaya matahari menjadi energi listrik yg mana cahaya mentari ialah galat satu bentuk tenaga dari sumber Daya Alam. Cahaya mentari telah banyak digunakan untuk memasok daya listrik pada satelit komunikasi melalui panel matahari. Panel surya ini bisa membentuk tenaga yg tidak terbatas langsung terpancar dari surya, tidak memerlukan bahan bakar. Sebagai akibatnya panel mentari sering dikatakan higienis serta ramah bagi lingkungan.
Perancangan Sistem Informasi Pemasaran Jasa Pada Difa Make-Up & Decoration Berbasis Web Menggunakan Bahasa Pemrograman PHP Mansyuri, Umar; Arief, Rahadian; Farhan Fauzan, Achmad; Dwiki Putra Aryono, Gagah; Hidayat, Amat
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 4 No 2 (2024): JMS Vol 4 No 2 September 2024
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2024.4.2.1848

Abstract

This study discusses the development and implementation of a web-based marketing information system for Difa Make-Up & Decoration. Using the prototyping method, this research aims to address the issues faced by Difa Make-Up & Decoration in managing marketing and service bookings. The system is designed to enhance online visibility, modernize business operations, and open new opportunities for growth. The developed information system includes features such as an interactive online catalog, real-time booking system, efficient customer data management, and analytical tools for strategic decision-making. This Wedding Organizer information system uses PHP and MySQL programming languages. The development method used for this system is prototyping, which consists of analysis, design, application development, evaluation, and results. The results of the study show that this system successfully improves operational efficiency and market reach. Thus, this research significantly contributes to the digital transformation in the creative services sector and enhances the competitiveness of SMEs in the wedding industry
Program Penyehatan Masyarakat melalui Posyandu di Desa Kalumpang Gagah Dwiki Putra Aryono
Nusantara: Jurnal Pengabdian kepada Masyarakat Vol. 3 No. 4 (2023): November : Jurnal Pengabdian kepada Masyarakat
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/nusantara.v3i4.1876

Abstract

Integrated service posts (posyandu) are community-sourced health efforts that are managed and organized from, by, for and with the community in implementing health development. Posyandu is an important health service for babies and toddlers. The visit of toddlers at Posyandu is related to the role of the mother as the person most responsible for the health of her toddler, influenced by the mother's visit, namely education, employment status, income level, level of knowledge, age of toddler, and number of children. toddler. Stunting is one of the national development problems in Indonesia which can hamper economic growth, increase poverty and inequality. This research aims to determine the role of posyandu in dealing with stunting in Kalumpang Village, Padarincang District, Serang Regency.
Advanced Deep Learning Models For Emotion Detection In Speech: Applying The Ravdess Dataset Aryono, Gagah Dwiki Putra; Ferawati, Dede; Auliana, Sigit
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 2 (2024): Edisi Agustus
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i2.815

Abstract

This study introduces a comprehensive approach to emotion recognition in speech using the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). The method integrates several state-of-the-art deep learning models known for their proficiency in pattern recognition and audio processing. The RAVDESS dataset comprises diverse audio files featuring emotional expressions by professional actors, meticulously categorized by modality, emotion, intensity, and other attributes. These data are utilized to train and evaluate various deep learning architectures including AlexNet, ResNet, InceptionNet, VGG16, and VGG19, as well as recurrent neural network (RNN) models such as LSTM and the latest transformer models. The analysis results indicate that the Transformer model excels with higher accuracy, precision, recall, and F1 score in emotion classification tasks compared to other models. This study not only enhances understanding of subtle emotional nuances in spoken language but also establishes new benchmarks in applying diverse neural network types for emotion recognition from audio. By providing detailed comparisons among models, this research advances the technology of emotion recognition, enhancing its applications in human-computer interaction, psychotherapy, entertainment industry, and paving the way for further development in multimodal emotion recognition systems.
Pemanfaatan Aplikasi E-Commerce Pada Pemasaran Produk UMKM Keripik Beras Di Desa Kalumpang Gagah Dwiki Putra Aryono
Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Vol. 1 No. 4 (2023): Oktober : Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat
Publisher : Asosiasi Riset Ilmu Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/pandawa.v1i4.172

Abstract

MSMEs are trading businesses managed by business entities or individuals which refer to productive economic businesses in accordance with the criteria stipulated by Law Number 20 of 2008. One of the MSMEs in the Kalumpang Village area is the Rice Chips MSME which is located at Kp Kedung Bulus, Kalumpang Village Padarincang District, Serang Regency, which is a community business in the village. So far, the marketing process for this product is still carried out traditionally, so that sales results are not optimal and the reach of promotion is limited because promotion is still carried out by word of mouth. Therefore, we as students with this community service activity contribute to designing applications and utilizing e-commerce through creating applications or websites as promotional and sales media for Rice Chips products so that we can increase sales and expand market share.
APPLICATION OF CODEIGNITER FRAMEWORK IN DETERMINING THE BEST EMPLOYEES USING THE MOORA METHOD AT THE IBUNDA GENERAL HOSPITAL IN SERANG CITY Basuki Rakhim Setya Permana; Gagah Dwiki Putra Aryono; Gelard Untirtha Pratama; Ahmad Munawir; Maman Masyhuri
INTERNATIONAL JOURNAL OF SOCIETY REVIEWS Vol. 2 No. 6 (2024): JUNE
Publisher : Adisam Publisher

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

Abstract

This research is based on the need to select the best appropriate employees so that they can maximize employee performance potential. Meanwhile, the process of determining the best employees currently at the "IBUNDA" Maternity Hospital in Serang City is still less than optimal. Based on these problems, a solution was created for a decision support system application to help management assess the overall determination of employees at the "IBUNDA" Nursing Hospital in Serang City easily and quickly. The MOORA (Multi Objective Optimization On The Basis Of Ratio Analysis) method is a decision making method applied to solve problems with complex mathematical calculations. The results of this research are first, in analyzing determining the best employees at the "IBUNDA" public hospital in Serang City, namely by carrying out calculations based on existing criteria so that you can carry out calculations using the MOORA method and get the best results. Second, implementing a decision support system application using the Moora method for selecting the best employees, so that the calculation process can be carried out using this method, and third, in implementing a decision support system application using the MOORA method, implementing the algorithm of this method into the system that will be built to determine employees the best at the "IBUNDA" General Hospital in Serang City.      
Machine Health Monitoring Using An Innovative Mechanical Approach Romayasari, Vera; Auliana, Sigit; Aryono, Gagah Dwiki Putra
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.450

Abstract

In today's world, machines are essential in daily life, requiring efficient and safe operation. Tools have been developed to assess machine health by monitoring power usage, temperature, noise, and vibrations. Anomalies in these parameters can indicate potential defects. FFT analyzers, commonly used for vibration measurement, are often too costly for small businesses and may lack the ability to measure speed, temperature, or power usage. This project aims to create a low-cost alternative for health monitoring systems, capable of measuring vibrations, noise, temperature, speed, and power consumption. Integrating an Arduino Uno R3 with sensors and a MATLAB 2018b GUI provides an affordable solution, catering to small firms unable to invest in expensive FFT analyzers
Deep Learning Techniques For Skin Cancer Detection And Diagnosis Aryono, Gagah Dwiki Putra; Audina, Alisa; Auliana, Sigit
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 5, No 3 (2024): Edisi Juli
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v5i3.451

Abstract

Skin cancer is the most common type of cancer globally, and early detection is crucial for effective treatment. This research reviews the use of deep learning techniques in detecting and diagnosing skin cancer. A review of current methodologies was conducted to propose new strategies for improving the accuracy and reliability of the detection and diagnosis processes. Various deep learning models, including convolutional neural networks, were evaluated using three publicly available datasets. The PSO algorithm was utilized for segmentation and feature extraction, while also exploring the impact of transfer learning, data augmentation, and model ensemble on model accuracy. The findings of this study indicate that deep learning techniques can significantly enhance the detection and diagnosis of skin cancer
Enhanced Facial Expression Recognition Through a Hybrid Deep Learning Approach Combining ResNet50 and ResNet34 Models Auliana, Sigit; Mahrojah, Siti; Aryono, Gagah Dwiki Putra
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1874

Abstract

Recognizing facial expressions is a critical aspect of computer vision and human-computer interaction. It facilitates the interpretation of human emotions from facial images, aiding in applications such as affective computing, social robotics, and psychological research. In this work, we propose using hybrid deep learning models, ResNet50 and ResNet34, for facial expression classification. These models, pre-trained on large-scale datasets, demonstrate exceptional feature extraction capabilities and have achieved excellent performance in various computer vision tasks. Our approach begins with the collection and preprocessing of a labeled facial expression dataset. The collected data undergoes face detection, alignment, and normalization to ensure consistency and reduce noise. After preprocessing, the dataset is divided into training, validation, and testing sets. We fine-tune the ResNet50 and ResNet34 models on the training set, employing transfer learning to adapt the pre-trained models specifically for the facial expression recognition task. Optimization techniques such as SGDM, ADAM, and RMSprop are used to update the models' parameters and minimize the categorical cross-entropy loss function. The trained models are evaluated on the validation set, achieving an accuracy of 98.19%. Subsequently, the models are tested on unseen facial images to assess their generalization capabilities. This proposed approach aims to deliver accurate and robust facial expression classification, thereby advancing emotion analysis and human-computer interaction systems.
Multi-Domain Medical Image Enhancement Through Fuzzy and Regression Neural Network Approach Auliana, Sigit; Nur Janah, Meishi; Gagah Dwiki Putra Aryono
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1875

Abstract

Medical image processing has heralded a significant transformation in contemporary medical science, offering the promise of diagnosing, treating, and curing patients while minimizing adverse effects. By leveraging medical imaging, physicians gain the ability to visualize internal structures without invasive procedures. Moreover, this technology contributes to our understanding of neurobiology and human behavior, with brain imaging aiding investigations into addiction mechanisms. Interdisciplinary collaboration among biologists, chemists, and physicists is facilitated by medical imaging, with resultant technologies finding applications across various fields. This study focuses on enhancing medical images in both frequency and time domains. Contrast enhancement is achieved through local transformation histogram techniques, followed by overall enhancement using a Fuzzy-Neural approach. The proposed methodology is implemented using MATLAB 2018b. The findings emphasize the efficacy of the proposed technique in improving image quality for both MR and Selenography images. Its outstanding performance, marked by a higher PSNR (32.96) and a lower MSE (20.04), indicates its potential for more precise and dependable image enhancement compared to current methods.
Co-Authors A Halim Abdul Kohar Abdul Kohar Achmad Dwi Saputro Aisah, Anggi Nur Aldi Setiawan, Aldi Aldiyanti, Fitri Aliffito, Sadam Nazar AMELIA, NUR Andika Purnama Andriani, Fipi April Laksana Ardiansyah, Rizqi Arfiansyah Putra Arief, Rahadian Audina, Alisa Auliana, Sigit Azis, Marisa Basuki Rakhim Setya Permana Bate’e, Welni Desrinayanti Chafid, Nurul DEWI FITRIANI Eightian, Vieri Ginola Elfrida Ratnawati Eris Dwi Purnama Fachruroji, Fahmi Farhan Fauzan, Achmad Fasya, Nabiila Ferawati, Dede Gelard Untirtha Pratama Hamdan Hawariz, Mamdu Mahsan Hidayat, Amat Ilham Danuarta Ilham, Ilham Rizqi Kenedi, Kenedi Lukman David Mahrojah, Siti Maman Masyhuri Masyhuri, Maman Masyuri, Umar Maulida, Fadia Syifa Miftahul Huda Muhamad Ja’far Sodik Muhammad Saifulloh Naufal, Dody Noviyanti, Ayu Nur Janah, Meishi Nurul Chafid Nurul Chapid Prasetya, Bima Purnama, Andika Purnama, Eris Dwi Putra, Arfiansyah Ramadhan, Adhitya Restiana, Anti Rizqa Ramadhian, Putri Rizqi Ardiansyah rohaimudin, iim Romayasari, Vera Sapaatullah, Asep Saptanzani, Wildan Setiawan, Ajis Siti Umaya Slamet Gunadi Sukmawan, Irwan Surya Wirana Rezky Umar Mansyuri Umar Mansyuri Untirtha Pratama, Gelard Wiwi Sulandari Yustiana, Sisy