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All Journal Jurnal Media Infotama Pixel : Jurnal Ilmiah Komputer Grafis JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Pseudocode POSITIF Jurnal Informatika Upgris International Journal of New Media Technology JURIKOM (Jurnal Riset Komputer) Jurnal Tekno Kompak JSAI (Journal Scientific and Applied Informatics) Journal of Technopreneurship and Information System (JTIS) Jusikom: Jurnal Sistem Informasi Ilmu Komputer Journal of Applied Engineering and Technological Science (JAETS) JISA (Jurnal Informatika dan Sains) Journal of Applied Data Sciences Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat ABDIMAS Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Sistem Informasi Jurnal Ilmu Komputer Dan Informatika eProceedings of Engineering Jurnal Rekayasa Sistem Informasi dan Teknologi Jurnal Informatika: Jurnal Pengembangan IT Pengabdian Kepada Masyarakat Bidang Teknologi dan Sistem Informasi JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) Applied Information Technology and Computer Science (AICOMS) Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Dedy Agung Prabowo
Universitas Telkom
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Public Health Social Sciences Other

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Analisis Sentimen Berbasis Aspek pada Layanan Hotel di Wilayah Kabupaten Banyumas dengan Word2Vec dan Random Forest Wijayanto, Sena; Prabowo, Dedy Agung; Kristiyanto, Daniel Yeri; Fathoni, M Yoka
Jurnal Informatika: Jurnal Pengembangan IT Vol 8, No 1 (2023)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v8i1.4186

Abstract

Dalam industri pariwisata, hotel memiliki peran penting untuk membantu wisatawan karena menyediakan penginapan terutama bagi wisatawan dari luar kota. Kualitas layanan hotel dapat dilihat dari opini-opini yang diberikan ooleh pengunjung yang telah menginap di hotel tersebut. Penelitian ini bertujuan untuk melakukan analisis sentimen terhadap ulasan yang diberikan oleh pengunjung hotel. Data ulasan tersebut diambil dari Traveloka menggunakan web scrapping. Metode yang digunakan untuk ekstraksi fitur adalah word2vec. Untuk klasifikasi sentimen, metode yang digunakan adalah random forest. Hasil percobaan terbaik didapatkan dari hasil percobaan dengan menggunakan jumlah tree 100, 200, dan 300 dengan hasil akurasi sebesar 82%-83%.
Analisis Kinerja Rantai Pasok Produk Kedelai Menggunakan Metode Supply Chain Operation Reference Fathoni, M Yoka; Prabowo, Dedy Agung; Wijayanto, Sena; Fernandez, Sandhy; Susanto, Ardi
Jurnal Informatika: Jurnal Pengembangan IT Vol 7, No 2 (2022)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v7i2.3740

Abstract

Indonesia is a country that has one of the advantages, namely as the largest agricultural country that has natural wealth, one of which is the agricultural sector. Soybean is one of the most widely grown crops in Indonesian agriculture and is included in the legumes group which has the highest vegetable protein content when compared to other types of beans such as red beans, green beans, and peanuts. The use of the SCOR method in this study is to measure good SCM performance, because SCOR divides supply chain processes into five 5 core processes, namely plan, source, make, deliver and return, where these processes have represented all supply chain activities. management from upstream to downstream in detail, so that it can define and categorize the measurement indicators needed in measuring Supply Chain Management performance. Based on the SCOR method, the results of the calculation of the final performance value of the soybean supply chain in the province of Central Java are 76.8 out of 100 which are in the "good" category.
Klasifikasi Kekeringan dan Penyakit pada Daun Padi Berdasarkan Ekstraksi Ciri Warna dan Tekstur Menggunakan CSPDarknet: Klasifikasi Kekeringan dan Penyakit pada Daun Padi Berdasarkan Ekstraksi Ciri Warna dan Tekstur Menggunakan CSPDarknet Abdul Jabbar Robbani; Dwi Putro Wicaksono, Aditya; Dedy Agung Prabowo
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 11 No 1 (2025): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v11i1.14964

Abstract

The decline in rice productivity in Indonesia is often caused by drought and leaf diseases that are difficult to detect early. This condition requires a technology-based classification system that is able to provide fast and accurate diagnosis as support for decision making in the agricultural sector. This study aims to develop a rice leaf image classification model using the CSPDarknet architecture, with a color and texture feature extraction approach. The dataset used is the result of primary documentation that has gone through an augmentation process to increase the diversity of training data. The model architecture consists of a CSPDarknet backbone combined with a Cross-stage Partial Bottleneck with two Convolutions (C2f) block, Spatial Pyramid Pooling - Fast (SPPF), Global Average Pooling, and dropout to improve model generalization. Training was carried out using the Stratified 5-Fold Cross-Validation method and three optimizer variations, namely Stochastic Gradient Descent (SGD), Adam, and AdamW. The experimental results showed that the best model combination was achieved with the AdamW optimizer, with an average accuracy value of 99.72%, precision of 99.73%, recall of 99.72%, and F1-score of 99.72%. These findings indicate that the proposed classification approach is able to effectively distinguish healthy, diseased, and drought-affected leaves. In the future, this model has the potential to be further developed through the integration of Raspberry Pi-based Internet of Things (IoT) devices for real-time monitoring of plant conditions in the field.
Hybrid Optimization Model for Integrated Image Data Extraction Expert System in Rice Plant Disease Classification Aldo, Dasril; Kurniawati, Ajeng Dyah; Prabowo, Dedy Agung; Fauzi, Ahmad; Saputra , Wahyu Andi; Sudianto, Sudianto; Yasin, Feri; Agustianto, Satya Helfi; Pangestu, Farhan Aryo; Sulaeman, Gilang
Journal of Applied Engineering and Technological Science (JAETS) Vol. 7 No. 1 (2025): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v7i1.6633

Abstract

The purpose of this study is to increase the accuracy for rice plant disease classification by developing a hybrid optimization model using Convolutional Neural Network (CNN) in combination with Extreme Learning Machine (ELM), followed by Support Vector Machine. A key issue is to overcome with traditional expert systems that difficult, due the variation differences and complex among rice plant image data set. For feature extraction, plant images are passed through CNN and for classification ELM & SVM used. Experimental results show the best accuracy of 98.63% is attained using CNN+ELM model on images resized to 100x100 pixels and has precision, recall, F1-Score all at value=0.99 By comparison, the CNN+SVM model achieves an accuracy of 91.92% using that same image size. Top AbstractIntroductionMethodsResultsDiscussionConclusionReferencesOverall, the proposed CNN+ELM combination can classify rice plant diseases better than using only a conventional approach (CNN) through various results from devices with limited computing power. The study presents a novel plant disease detection system that can be utilized for the development of precise tools to help improve agricultural management practices.
The Classification of Anxiety, Depression, and Stress on Facebook Users Using the Support Vector Machine Wijiasih, Tsania Maulidia; Amriza, Rona Nisa Sofia; Prabowo, Dedy Agung
JISA(Jurnal Informatika dan Sains) Vol 5, No 1 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i1.1273

Abstract

Social media remains an essential platform for connecting people with friends, family, and the world around them. However, when events spread on social media are primarily negative, it will cause depression, anxiety, and stress that tend to increase. This study aims to classify depression, anxiety, and stress using the Support Vector Machine. The data in this study were obtained from active Facebook users using the Depression Anxiety Stress Scale (DASS 21) questionnaire. This study adopted the Knowledge Discover Database process. The result of this study is an evaluation of the performance of the Support Vector Machine classification of depression, anxiety, and stress. The accuracy of the Support Vector Machine in this study is 98.96%.
Improving Cattle Farmers Knowledge of Animal Weight Monitoring Using IoT: Peningkatan Pengetahuan Peternak Sapi dalam Monitoring Berat Badan Hewan Ternak Berbasis IOT Wahyu Andi Saputra; Muhamad Azrino Gustalika; Faizah Faizah; Silvia Van Marsally; Dedy Agung Prabowo; Fahrudin Mukti Wibowo
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 10 No. 3 (2026): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/je.v10i3.536

Abstract

The Mukti Mandiri Livestock Group is located in Karanggitung Village, Banyumas Regency. This group focuses on beef cattle farming. Currently, the group faces various obstacles, including the lack of ability to accurately calculate cattle weight. This causes the group to often rent scales or entrust their cattle to other cattle groups to determine their weight. Furthermore, the Mukti Mandiri Group often chooses to estimate the weight of cattle due to the high rental price of scales. This impacts the selling price of cattle to collectors, resulting in farmers only earning a small profit. Therefore, a weighing device is needed to assist the Mukti Mandiri Livestock Group. This community service activity was carried out in order to provide IoT (Internet of Things)-based weighing devices to facilitate the cattle weighing process. The activity consisted of 5 stages: socialization, technology implementation, training, mentoring and evaluation, and the sustainability of the community service program. The results of this community service showed that 51% of respondents answered strongly agree, 46% agreed, and 3% quite agreed, in terms of increasing the knowledge of livestock farmers regarding the community service activity and the use of IoT-based weighing devices. It is hoped that this community service activity can continue in the management aspect for RPH (Animal Slaughterhouse) and Juleha (Halal Slaughterhouse) so that it can encourage participation from other livestock breeders in the use of technology in the livestock sector.
Performance Comparison of AES and Blowfish Algorithm Hendrawan Nur Majid; Trihastuti Yuniati; Dedy Agung Prabowo
IJNMT (International Journal of New Media Technology) Vol 13 No 1 (2026): Vol 13 No 1 (2026): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v13i1.4709

Abstract

The rapid advancement of communication and data storage technologies requires security systems capable of protecting sensitive information from cyber threats. Symmetric cryptography algorithms such as AES and Blowfish are widely used, although they exhibit different performance characteristics. This study compares both algorithms based on processing time, memory usage, and throughput on .txt, .pdf, and .zip files. The testing was conducted through a Python implementation using ECB and CTR modes. The results show that AES consistently outperforms Blowfish in terms of speed and throughput. For large files, AES using ECB mode reaches a throughput of 1128.42 MB/s, significantly higher than Blowfish using ECB mode at 92.26 MB/s, with faster encryption time as well, AES using ECB mode within 0.075 seconds while Blowfish using ECB mode within 0.928 seconds. The decryption process shows similar results, where AES using CTR mode achieves 546.70 MB/s, while Blowfish using CTR mode reaches only 81.59 MB/s. Overall, AES is more suitable for fast encryption-decryption on large-scale data processing, whereas Blowfish is more appropriate for small files or low-complexity applications.
PERANCANGAN SISTEM INFORMASI OBJEK WISATA DI KABUPATEN BENGKULU UTARA BERBASIS WEB Yopita Syaputri; Kirman Kirman; Anisya Sonita; Dedy Agung Prabowo
Jurnal Media Infotama Vol 20 No 2 (2024): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i2.6327

Abstract

A design ofweb-based information system oftourism objects in north Bengkulu regency is used as a tool in delivering information on tourism and cultural areas in north Bengkulu regency to people who want to know the tourism areas. It is one form of tourism promotion to attract tourists to visit north Bengkulu. This research is expected to be useful as a medium of information and promotion of tourismpotential in north Bengkulu, so that people will be more familiar with regional tourismplaces. The more tourists who visit, the income of the area and the surrounding community will increase. The method used in this research was the Rapid Application Development (RAD) method. This method includedthe requirements analysis, system design, implementation, testing and maintenance stages, followed by making applications using the PHP and HTML programming languages with MySQL and XAMPP database
Co-Authors 12.5202.0161 Daniel Yeri Kristiyanto Abdul Jabbar Robbani Agustianto, Satya Helfi Agustomi, Endri Ajeng Dyah Kurniawati Akhdan Syarif Hidayatullah, Dias Akhmad, Fajar Kamaludin Alon Jala Tirta Segara Andri Sarpiadi Ardi Susanto Ardi Susanto Aritonang, Sudarsono Azzahra, Fathya Yuanita Cahyo Prihantoro Dandi Sunardi Dasril Aldo Dedy Abdullah Dedy Abdullah Dernata, Jaka Dimas Fanny Hebrasianto Permadi Dofiyer, Fernaldo Christofer Dwi Putro Wicaksono, Aditya Eki Agustiawan Fahrudin Mukti Wibowo Faizah Faizah Fauzi Ahmad Muda Fauzian Setiawan, Kelvin Fernaldo Christofer Dofiyer Firdaus, Ammar Musthofa Gunawan Gunawan Hendrawan Nur Majid Hengki Putra Irawan Jaka Dernata Kirman M Yoka Fathoni marhalim, marhalim Marsally , Silvia Van Marsally, Silvia Van Muflih Haura Muhamad Azrino Gustalika Muhamad Azrino Gustalika Muhammad Husni Rifqo Muna, Bunga Laelatul Nicolaus Euclides Wahyu Nugroho Novian Adi Prasetyo Pangestu, Farhan Aryo Paradise Perdi Leo Ade Candra Pratama, Rendra Agung Putra, Erwin Dwika Rachman, Ari Rakhma, Nazwa Aulia Rendra Agung Pratama Rendra Agung Pratama Resad Setyadi Rifqo, Muhammad Husni Rona Nisa Sofia Amriza Sandhy Fernandes Sandhy Fernandez Saputra , Wahyu Andi Sarah Astiti S.Kom., M.MT Silvia Van Marsally Sonita, Anisya Sudianto Sudianto, Sudianto Sulaeman, Gilang Sundari Sundari Syarif Hidayatullah, Dias Akhdan Tarigan, Emya Ninta Teguh Ramadhani, Dimas Toyib, Rozali Triaji Morgana Kaban Trihastuti Yuniati Usman, Muhammad Lulu Latif Utami, Annisaa Wahyu Andi Saputra Wicaksono, Apri Pandu Wijiasih, Tsania Maulidia Yasin, Feri Yopita Syaputri Yuza Reswan