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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Mahasiswa Sistem Informasi (JMSI) Journal of Artificial Intelligence and Engineering Applications (JAIEA) AMMA : Jurnal Pengabdian Masyarakat INTERNAL (Information System Journal)
Dodi Solihudin
STMIK IKMI Cirebon
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Education Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Other

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Rancang Sistem Presensi Online dengan Metode Gamifikasi dan Online Collaborative Learning Dodi Solihudin; Iin Iin; Dian Ade Kurnia
INTERNAL (Information System Journal) Vol. 5 No. 2 (2022)
Publisher : Masoem University

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Abstract

Online lectures are still being held while Covid-19 pandemic is going to end. Suitable system is needed to ensure the quality of online learning. We must combine the teleconference with the Collaborative Learning System to maintenance the interactions between students and their lecturer. The research is to build a system that can implement the Collaborative Learning System in online lectures. The methods used are gamification and Extreme Programming. The results of the research is the Online Presence application with chat system features, real-time polling system, real-time question-answer, and real-time leaderboard. The application can be accessed athttps://ikmiapp.web.id/presline.
Analisis Keadaan Stunting pada Kelompok Balita di Kecamatan Tukdana dengan Pendekatan Decision Trees Asep Budiyanto; Dodi Solihudin; Ryan Hamonangan; Cep Lukman Rohmat; Ade Rizki Rinaldi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10230

Abstract

The impact of stunting on babies is an important parameter for assessing the health and welfare of children in an area. Stunting, often triggered by demographic and health factors, has serious implications for children's physical and cognitive growth. This research aims to understand the impact of demographic and health factors on stunting in children in Tukdana District, Indramayu Regency. Through data analysis, factors such as maternal age, access to clean water, sanitation facilities, and baby weight and length status were identified as significant contributors to stunting. The Decision Trees method was used to identify factors that play a role in stunting in babies, with an accuracy rate of 95.43%. The implications of this research include planning more effective interventions to deal with stunting, both in Tukdana District and in similar areas in Indonesia. Even though the majority of babies in Tukdana District have good nutritional status, further monitoring and prevention efforts are still needed to ensure optimal nutritional well-being for them. In conclusion, this research highlights the importance of identifying factors that cause stunting in infants in Tukdana District, as a basis for planning more effective interventions.
OPTIMIZATION IOT TECHNOLOGY IN WEATHER STATIONS FOR IMPROVE AGRICULTURAL SUCCESS DURING EL NIÑO ERA Dodi Solihudin; Odi Nurdiawan; Rudi Kurniawan; Cep Lukman Rohmat
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 2 (2024): JITK Issue November 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i2.5851

Abstract

The El Niño phenomenon is significant to global weather patterns, particularly in Indonesia, which adversely affects the agricultural sector, especially rice production. El Niño causes drastic changes in rainfall patterns, making it difficult for farmers to determine the right planting time. Limited access to accurate weather information is a major obstacle for farmers in planning their agricultural activities. This research aims to develop an Internet of Things (IoT)-based weather station capable of providing real-time and accurate weather data to support farmers' decision-making in their land management. The research method starts with observation in Babakan Jaya Village, Gabuswetan District, Indramayu Regency, to understand the local weather conditions and specific challenges faced by farmers. Next, the construction and implementation of a weather station equipped with sensors to measure various weather parameters such as temperature, humidity, wind direction and speed, and rainfall. The weather data collected by these stations is then processed and presented in real-time through a cloud platform, which allows access from computer devices and smart phones. The observation results from 1 June to 27 July 2024 showed that the air temperature ranged from 29°C to 35°C, humidity between 55% to 90%, and wind speed ranged from 0 to 7 km/h, with sporadic rainfall patterns. The developed IoT weather station successfully provides relevant and accurate weather data, which can be accessed in real-time by farmers. With this data, farmers can make more informed decisions in their land management, hopefully improving the efficiency and success of farming practices, especially in the midst of erratic weather conditions due to El Niño.
Pengembangan Website Promosi Produk UMKM Berbasis Online Dodi Solihudin; Fathurrohman; Marfelio Muhamad Fajid; Mochamad Adhari Febrian
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2023): AMMA : Jurnal Pengabdian Masyarakat (INPRESS)
Publisher : CV. Multi Kreasi Media

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Abstract

Micro, Small, and Medium Enterprises (MSMEs) require effective promotion strategies to enhance the visibility and competitiveness of their products, especially in the digital era. This Community Partnership Program aims to develop product promotion websites for MSMEs based on WordPress. Activities include basic training on using the WordPress platform, designing and developing attractive and informative websites, simple search engine optimization (SEO) of content, and website management training for MSME representatives. It is expected that with this promotional website, MSMEs can expand their online market reach, enhance product brand image, and facilitate interaction with potential consumers, ultimately contributing to increased sales and business growth.
Pelatihan Dasar Microsoft Office Bagi Remaja Putus Sekolah Sebagai Upaya Pemberdayaan Digital Edi Tohidi; Dodi Solihudin; Mochamad Arief Saputra; Mochammad Haris Maulana Ibrahim
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 3 (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Basic skills in using Microsoft Office applications are essential competencies for enhancing job opportunities and participation in various activities in the digital era, especially for out-of-school youth who often have limited access to formal education. This Community Partnership Program aims to empower out-of-school youth through basic Microsoft Office training. This training is designed to provide understanding and practical skills in using Microsoft Word for document processing, Microsoft Excel for data processing and simple calculations, and Microsoft PowerPoint for creating presentations. It is expected that, through this training, out-of-school youth can improve their functional skills, open opportunities for jobs requiring basic administrative abilities, and increase their self-confidence in facing the challenges of the digital era.
Peningkatan Layanan RT Melalui Sistem Informasi Administrasi Berbasis Web Dodi Solihudin; Edi Tohidi; Abi Fajar Ahmad Fauzi; Ade Valentino
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 03 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Administrative services at the neighborhood level (Rukun Tetangga/RT) are an essential component in supporting good governance within communities. However, in practice, these services are still frequently managed manually, leading to various issues such as service delays, data entry errors, and inefficiencies in documentation. This Community Service Program (PKM) aims to design and implement a web-based neighborhood administrative information system to assist RT administrators in delivering faster, more accurate, and transparent services to residents. The implementation methods include needs assessment, system design, software development, as well as training and technical assistance for both administrators and residents. The system is developed using web-based technologies (PHP, MySQL, and HTML/CSS), allowing access via computers or smartphones. Key features of the system include resident data management, automated issuance and printing of official letters, archive management, and financial and activity reporting. The implementation results indicate a significant improvement in the efficiency of RT administrative services. RT administrators are no longer burdened with manual record-keeping, and residents can access services independently from their homes. Moreover, the system supports administrative transparency, as all activities are digitally recorded and easily traceable. This program has a positive impact on digital literacy among residents and strengthens the integration of information technology with public services at the micro community level. In the future, the system is expected to be replicated in other RTs as a community-based digital transformation solution.
Optimalisasi Penggunaan Aplikasi Digital Payment bagi Pedagang Pasar Tradisional Fatihanursari Dikananda; Dodi Solihudin; Anjar Ayuning Lestari; Athhar Hafizha Luthfi
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This Community Partnership Program aims to optimize the use of digital payment applications among traditional market traders. Activities include education on the benefits of digital payment, training on application usage, and assistance in non-cash transactions. This program is expected to increase transaction efficiency, security, and financial accessibility for traders, while also promoting financial inclusion in traditional markets.
PENINGKATAN AKURASI KLASIFIKASI KEMATANGAN KELAPA SAWIT BERBASIS CITRA DENGAN ENSEMBLE DEEP LEARNING TEROPTIMASI DIMENSI RASIO Ahmad Rifai Ikhsanudin; Dian Ade Kurnia; Yudhistira Arie Wijaya; Dodi Solihudin; Tati Suprapti
Jurnal Mahasiswa Sistem Informasi (JMSI) Vol. 7 No. 2 (2026): Jurnal Mahasiswa Sistem Informasi (JMSI)
Publisher : Program Studi DIII Sistem Informasi - Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jmsi.v7i2.11181

Abstract

Penentuan tingkat kematangan buah kelapa sawit secara manual sering menimbulkan subjektivitas dan menurunkan efisiensi. Penelitian ini mengembangkan metode klasifikasi berbasis citra menggunakan ensemble averaging pada tiga arsitektur MobileNetV2 dengan ukuran input berbeda (224×224, 224×300, dan 300×300) untuk mengurangi varians prediksi akibat variasi dimensi dan rasio aspek citra. Dataset yang digunakan berasal dari Kaggle berjumlah 1.380 citra, dengan pembagian 80% data latih dan 20% data validasi. Proses pengolahan mencakup rescaling, aspect-ratio-aware resizing, augmentasi, serta pelatihan menggunakan transfer learning dengan optimizer Adam dan early stopping. Hasil menunjukkan bahwa model berukuran 300×300 memberikan performa terbaik dengan akurasi 95,22% dan F1-score 0,9523. Ensemble averaging menghasilkan akurasi 94,71% dan F1-score 0,9475, yang meskipun sedikit lebih rendah dari model terbaik, memberikan stabilitas prediksi yang lebih baik dibanding model individual. Temuan ini menunjukkan bahwa resolusi input yang lebih tinggi meningkatkan kualitas ekstraksi fitur, sementara ensemble averaging tetap efektif dalam mereduksi varians dan meningkatkan ketahanan sistem klasifikasi di kondisi lapangan.
Implementation of Deep Learning Based on Convolutional Neural Network for Detecting Images of Solar Panel Damage in Smart Grid Systems Camelia Putri Lestari; Nining Rahaningsih; Irfan Ali; Dodi Solihudin; Tati Suprapti
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2225

Abstract

This study aims to implement Deep Learning based on Convolutional Neural Network (CNN) in detecting solar panel damage using thermal images as part of a Smart Grid system. The main problem addressed is the difficulty of early automatic identification of solar panel cell damage using conventional methods. Through the CNN approach, this study developed a classification model to distinguish between damaged (Defective) and undamaged (Non-Defective) solar panel conditions. The research stages included thermal image dataset collection, pre-processing, model training, and performance evaluation. The results showed that the CNN model was able to achieve an accuracy of over 87% with stable performance on the validation data. Visualization using the Grad-CAM method helps interpret the damaged areas that are the focus of the model's decision.
Co-Authors Abi Fajar Ahmad Fauzi Ade Rizki Rinaldi Ade Valentino Ahmad Rifai Ikhsanudin Anjar Ayuning Lestari Arye Fandia Kusuma Asep Budiyanto Athhar Hafizha Luthfi Camelia Putri Lestari Cep Lukman Rohmat Dian Ade Kurnia Edi Tohidi Fathurrohman Fatihanursari Dikananda Iin Irfan Ali Marfelio Muhamad Fajid Mochamad Adhari Febrian Mochamad Arief Saputra Mochammad Haris Maulana Ibrahim Nana Suarna Nining Rahaningsih Odi Nurdiawan Rudi Kurniawan Ryan Hamonangan Tati Suprapti Yudhistira Arie Wijaya