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All Journal Seminar Nasional Informatika (SEMNASIF) Jurnal Ilmiah Dinamika Rekayasa (DINAREK) Jurnal PIPSI: Jurnal Pendidikan Ilmu Pengetahuan Sosial Indonesia Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) YUSTISI J-SAKTI (Jurnal Sains Komputer dan Informatika) JETL (Journal Of Education, Teaching and Learning) JURNAL TEKNOLOGI INFORMASI TAPAK (Teknologi Aplikasi Konstruksi) : Jurnal Program Studi Teknik Sipil JPDI (Jurnal Pendidikan Dasar Indonesia) EDUTEC : Journal of Education And Technology Abdi Dosen : Jurnal Pengabdian Pada Masyarakat PENA AKUATIKA : JURNAL ILMIAH PERIKANAN DAN KELAUTAN REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Didaktik : Jurnal Ilmiah PGSD STKIP Subang Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Yustisi: Jurnal Hukum dan Hukum Islam Sinar Sang Surya: Jurnal Pusat Pengabdian kepada Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS) eProceedings of Management JUMATISI : Jurnal Mahasiswa Teknik Sipil Cendikia Pendidikan Jurnal Indonesia : Manajemen Informatika dan Komunikasi JURMA YUSTISI
Dadang Iskandar, Dadang
Universitas Pasundan
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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
ENHANCED SPEED AND ACCURACY IN COCOA FRUIT DISEASE IDENTIFICATION USING THE INCEPTION-RESNET CONVOLUTIONAL NEURAL NETWORK (CNN) ALGORITHM Iskandar, Dadang; Novanto, Adi; Kurniawan, Yogiek Indra
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4144

Abstract

The increase in world cocoa consumption is not accompanied by an increase in production, causing a problem of supply shortages in the world. One of the causes of the stagnation in the increase in cocoa production is due to diseases that attack cocoa fruit. The disease can cause unproductive plants, unusable cocoa fruit, and even cause the spread of epidemics in a cocoa fruit garden. One of the preventions that can be done is to identify diseases in cocoa fruit in order to reduce the spread of the disease. The identification process is usually carried out independently by farmers. Identification of cocoa fruit diseases requires knowledge and experience by farmers, so it can cause misidentification or failure to identify the disease. In addition, other factors can arise such as the number of farmers who check, the area of ​​the cocoa fruit garden, and the urgency of identification. To help overcome these problems, a Convolutional Neural Network (CNN) model was developed with the Inception and ResNet architectures. The data used were images obtained from Davao City, Philippines. The model obtained from the analyzed dataset got the best results of 0.99, a specificity value of 0.99, and an F1-score value of 0.99. The model configuration used is a learning rate value of 0.0001, RMSProp optimization function, initialization function (x) He uniform, initialization function (y) Glorot normal, and a batch size of 32.
From Monoliths to Microservices: Designing a Scalable Super App Architecture for Academic Services at Universitas Jenderal Soedirman Wijayanto, Bangun; Iskandar, Dadang; Rahayu, Swahesti Puspita
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5237

Abstract

Jenderal Soedirman (Unsoed) currently operates more than 30 monolithic information systems built with heterogeneous technology stacks, resulting in duplicate functionality, inconsistent user experience, and high maintenance costs. This study designs a modular, microservices‑based Super App architecture that integrates core academic services (KRS/KHS, transcript, student & lecturer attendance, lecturer activity log) and a parent/guardian monitoring feature. Using the Design Science Research (DSR) method, we (1) identified problems via a technology audit and problem–objective matrix; (2) designed the artifact with Domain‑Driven Design, C4 modelling, and API‑first contracts; (3) demonstrated a working prototype with API Gateway, SSO, and event‑driven notifications; (4) evaluated performance (<300 ms latency for 500–1000 concurrent users) and stakeholder impact; and (5) communicated results through this paper. The proposed architecture reduces integration complexity, supports zero‑downtime deployment, and enhances transparency for parents without violating consent and privacy. The validated blueprint provides a roadmap for transforming legacy campus systems into a scalable, observable, and governable Super App.
DESIGN AND DEVELOPMENT OF COMPUTER-BASED TEST (CBT) SYSTEM IN THE ACADEMIC SELECTION PROCESS FOR RECRUITING SOLDIERS IN THE AIR FORCE Anggraini Pratiwi, Nabilla; Iskandar, Dadang; Nofiyati, Nofiyati
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.1.1334

Abstract

The selection of recruits is a crucial stage for the continuity of the existence of the Indonesian Air Force (TNI AU). This selection process consists of several stages, one of which is the academic stage conducted with a paper-based test model. This model requires a lengthy conventional process, indicating the need for a computer-based system to expedite the selection process. Therefore, this study proposes a solution for the academic selection of TNI AU recruits by implementing a Computer Based Test (CBT) system, aiming to enhance the efficiency of the selection process. The development of the CBT system utilizes the Waterfall method, with PHP programming language and MySQL. The research results in a CBT system designed for electronic academic selection of TNI AU recruits, equipped with Safe Exam Browser (SEB) to reduce cheating during the selection exams. According to testing results, the CBT system meets the requirements and is deemed suitable for use.
WEB-BASED IMAGE CAPTIONING FOR IMAGES OF TOURIST ATTRACTIONS IN PURBALINGGA USING TRANSFORMER ARCHITECTURE AND TEXT-TO-SPEECH Muazam, Safa; Kurniawan, Yogiek Indra; Iskandar, Dadang
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 5 (2024): JUTIF Volume 5, Number 5, Oktober 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.5.2585

Abstract

Purbalingga is a region located in Central Java Province, offering interesting natural beauty and tourist destinations. Many tourists capture their moments in photos, which are then uploaded to social media. However, a picture can contain a lot of information, and each individual may interpret it differently. Without captions, people may struggle to extract this information. Image captioning addresses this challenge by automatically generating text descriptions for images. Additionally, text-to-speech is used to enhance accessibility for the visually impaired in understanding image descriptions. This research aims to develop an image captioning model for images of tourist attractions in Purbalingga using transformer architecture and ResNet50. The transformer architecture employs an attention mechanism to learn the context and relationships between inputs and outputs, while ResNet50 is a robust convolutional network for image feature extraction. Model evaluation using BLEU metrics, which compare generated sentences to reference sentences, shows the best results as BLEU-{1, 2, 3, 4} = {0.672, 0.559, 0.489, 0.437}. Experiments indicate that increasing embeddings and layers extends training time and lowers BLEU scores, while changing the number of heads has minimal impact on results. The best model is implemented in a web-based application using the SDLC waterfall method, Flask framework, and MySQL database. This application allows users to upload tourist attraction images, receive automatic descriptions in Indonesian, and listen to the captions read aloud using the Web Speech API-based text-to-speech feature. Blackbox testing results show valid outcomes for all tests, indicating that the application operates as required and is suitable for use.
Co-Authors Ahdiat, Mulki Akbar, Yuma Al-Miraza Hsb, M. Yusril Ihza Aldila Dinanti, Aldila Aldila Krisnaresanti, Aldila Amran, Yusuf Anggraini Pratiwi, Nabilla Arief Kelik Nugroho, Arief Kelik Arinal, Veri Aulia, Mutia Ayu Permata Sari Azizah Mahary Bahari, Muhamad Hasbi Toharudin Bangun Wijayanto Deasy Rahmawati Dedi Gunawan Dian Puspitasari Fadillah, Muhammad Ilham Farisyihab, Joe Renaldy Ferdiansyah, Adam Hamdani, Acep Roni Harmaen, Deni Hudzaifah, Salim Maula Ida Hadijah, Ida Ika Julianti Indra Satria Khairullah, Muhammad Daffa Kurniawan, Septyanto Kurniawan, Yogiek Indra Lina Rifda Naufalin Lutma Ranta Allolinggi Manurung, Azwar Anas Muazam, Safa Muftadi, Imam Muhammad Eka Purbaya Nasution, Nurdila Hasana Noerafifah, Hani Nofiyati Nofiyati, Nofiyati Novanto, Adi Nur Chasanah Nurfaishal, Muhammad Dzaky Nurlaila Nurlaila Oktavia, Chica Oktavia, ST., MT, Chica Paulus Insap Santosa Permana, Arif Wahyu prasetiya, dandy Pratiwi, Septi Elang Prawati, Eri Purwaningsih, Prihatini Putra, Adhy Hantar Putri, Amellya Eka Putri, Feby Aristia Rahayu, Swahesti Puspita RINI Rizki, Andika Serdianto Rolia, Eva S, Fahmi Chairulloh Widia Saharuddin Daming Salsabila Sarimole, Francis Matheus Sriharyani, Leni Sukmana, Dede Syaeful, Achmad Syahfikri, Mahesky Taufiqulloh Dahlan Teti Suhartini Tullah, Rahmah Van Marsally, Silvia Yanuar E. Restianto