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All Journal Jurnal technoscientia Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) JUITA : Jurnal Informatika JSAI (Journal Scientific and Applied Informatics) Jurnal Teknologi Informasi dan Multimedia JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Generic Innovation in Research of Informatics (INNOVATICS) Jurnal Pendidikan dan Teknologi Indonesia Jurnal Informatika Teknologi dan Sains (Jinteks) Blend Sains Jurnal Teknik Prosiding Seminar Nasional Hasil-hasil Penelitian dan Pengabdian Pada Masyarakat VISA: Journal of Vision and Ideas Sistem dan Teknik Transportasi Indonesia
Tito Pinandita
Universitas Muhammadiyah Purwokerto
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Transportation

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Deteksi Penyakit Daun Tomat Real-Time pada Platform Android Berbasis Convolutional Neural Network Nova Rahmawati, Eprisa; Pinandita, Tito; Ayu Fitriani, Maulida; Ambar Pambudi, Elindra
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 8 (2025): JPTI - Agustus 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.964

Abstract

Tanaman tomat (Solanum lycopersicum) merupakan komoditas hortikultura dengan kerentanan tinggi terhadap infeksi patogen pada daun, berdampak signifikan pada kualitas dan produktivitas. Identifikasi dini penyakit daun tomat menjadi krusial untuk mencegah kerugian ekonomi, namun metode konvensional secara visual dinilai kurang efektif karena bersifat subjektif dan membutuhkan waktu lama. Penelitian ini bertujuan mengembangkan aplikasi mobile untuk mengidentifikasi penyakit daun tomat secara real-time, akurat, dan dapat mengetahui hasil langsung di lokasi penanaman. Sistem dikembangkan menggunakan pendekatan CNN dengan arsitektur MobileNetV2V2 yang di optimasi untuk perangkat mobile. Model dilatih menggunakan 9.600 citra daun tomat mencakup enam kategori penyakit, dikonversi ke format ONNX dan diimplementasikan ke platform Android melalui Unity dengan framework Barracuda. Evaluasi model menunjukkan performa yang sangat baik dengan akurasi pelatihan 95%. Pengujian pada 60 sampel di lingkungan nyata menghasilkan akurasi deteksi real-time 88,33%, dengan precision 87,5%, recall 88,3%, dan F1-score 87,9%. Aplikasi ini menawarkan solusi praktis bagi petani untuk identifikasi penyakit tanpa bergantung pada koneksi internet, memungkinkan penanganan dini yang tepat, mengurangi penggunaan pestisida berlebihan, dan berpotensi meningkatkan produktivitas tanaman tomat melalui pengendalian penyakit yang lebih efektif.
Implementasi Perpustakaan Digital untuk Meningkatkan Minat Baca Siswa di SDN 3 Cikoneng Firdaus, Rizqi Muhammad; Pinandita, Tito
VISA: Journal of Vision and Ideas Vol. 4 No. 2 (2024): VISA: Journal of Vision and Ideas (In Press)
Publisher : IAI Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/visa.v4i2.3409

Abstract

Reading interest is an important aspect for students' intellectual and academic development at the primary school level. However, in some elementary schools, including SDN 3 Cikoneng, students' interest in reading tends to be lacking or declining. Especially in the era of rapid development of information and communication technology, utilizing information and communication technology is one of the solutions to increase students' reading interest by implementing a digital library. The purpose of this research is to design and implement a digital library at SDN 3 Cikoneng as a means to increase student interest in reading. This digital library can be accessed easily and quickly to various learning resources in digital form. The system is designed and developed with the Waterfall model with stages including Requirements Analysis, System Design, Implementation, Testing, and Maintenance. The results of this study indicate that the digital library has begun to increase student interest in reading at SD Negeri 3 Cikoneng, because it is undeniable that now students use cellphones more than their books. Through the digital library, it will be easier for students to read material books anytime and anywhere. So it is hoped that the use of digital libraries can increase student interest in reading more effectively and efficiently.
Pengembangan Media Pembelajaran Interaktif Berbasis Augmented Reality untuk Klasifikasi Hewan Vertebrata dan Invertebrata Menggunakan Metode GDLC Hidayahtullah, Muhammad Iqbal; Sugiyanto, Sigit; Pinandita, Tito; Hakim, Dimara Kusuma
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 4 (2025): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i4.849

Abstract

This study introduces an innovative Augmented Reality (AR)-based learning media for teaching ani-mal classification, specifically visualizing vertebrates and invertebrates in interactive three-dimensional form. Developed using Unity 3D and Vuforia with the Game Development Life Cy-cle (GDLC) waterfall model, the application offers an engaging learning experience through mark-er-based scanning that displays 3D animal objects, instructional materials, and evaluative quizzes. The novelty of this research lies in the integration of 3D visualization and interactive learning that enables students to explore and test their understanding in real time. Functional testing using the Black Box method confirmed that all features operated correctly, while field trials involving 20 students from SD Negeri Karanggintung 04 showed a high satisfaction rate of 88.75% (strongly agree category). Fur-thermore, post-test results demonstrated a significant improvement compared to pre-test scores, with students’ performance increasing from the 2–3 range to 4–5. With its visual and interactive approach, this AR-based learning media effectively enhances student comprehension and engagement, offering a promising and innovative solution for biology education at the elementary level.
Freshwater Fish Classification Based on Image Representation Using K-Nearest Neighbor Method Suwarsito Suwarsito; Hindayati Mustafidah; Tito Pinandita; Purnomo Purnomo
JUITA: Jurnal Informatika JUITA Vol. 10 No. 2, November 2022
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v10i2.15471

Abstract

Indonesia is a maritime and agricultural country with enormous world fishery potential. The large variety of fish is often confusing for ordinary people in recognizing types of fish, especially freshwater fish. It was stated that the types of freshwater fish often consumed by the Indonesian people are bawal (pomfret), betutu, gabus (cork), gurame (carp), mas (goldfish), lele (catfish), mujaer (tilapia), patin (asian catfish), tawes, and nila (tilapia nilotica). Some fish types have similar shapes, so it is tricky to tell them apart. Meanwhile, in the digitalization era today, Artificial Intelligence (AI)-based technology has become a demand in all areas of life. It is overgrowing, not apart from the fisheries sector. Therefore, in this study, the K-Nearest Neighbor (KNN) method was applied as one of the methods in AI to identify and classify freshwater fish species based on their images. The KNN method classifies new data into specific classes based on the distance between the new data and the closest k data through the learning process. This KNN model is built by preparing the dataset stages, separating the dataset into data-train and data-test with a ratio of 70%:30%, then building and testing the model. The dataset is freshwater fish images, totaling 100 images from 10 freshwater fish types. Model testing is done by measuring performance using a confusion matrix. Based on the test results, the model has an accuracy performance of 70%. Thus, KNN can be used as a model to identify freshwater fish species based on their image.
Penerapan Zachman Framework pada Perancangan Architecture Sistem Informasi Pengelolaan Obat Dinas Kesehatan Purbalingga Annisa Dwi Risqi; Achmad Fauzan; Tito Pinandita; Feri Wibowo
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8491

Abstract

The application of the right information system architecture framework is very important in ensuring efficiency and consistency in data management, especially in drug management information systems in the government sector. This study aims to evaluate the maturity level of the application of the Zachman Framework in the design of the Drug Management Information System at the Purbalingga Health Office using the Capability Maturity Model (CMM) approach. The evaluation was conducted on six main perspectives of Zachman: Planner, Owner, Designer, Builder, Subcontractor, and Functioning System. The measurement results showed the following maturity percentage values: Planner (60%), Owner (40%), Designer (60%), Builder (40%), Subcontractor (20%), and Functioning System (60%), with an average maturity level of 46.67% or equivalent to Level 2 (Repeatable). These results indicate that the design process already has a basic pattern but has not been thoroughly documented or standardized. The main recommendation in this research is to improve technical documentation, HR training, and integration between architecture perspectives to achieve a higher level of maturity.
Co-Authors . Suwarsito Achmad Fauzan Agung Purwo Wicaksono Ahmad Ahmad Ambar Pambudi, Elindra Annisa Dwi Risqi Ardhine Attafaqquf Ayu Fitriani, Maulida Aziz, Hilmi Dimara Kusuma Hakim Feri Wibowo Firdaus, Rizqi Muhammad Hidayahtullah, Muhammad Iqbal Hidayat, Arif Lukman Hidayat, Arif Lukman Himawan, Hidayatulloh Hindayati Mustafidah Juanita Juanita Kusuma, Fajar Budi Nova Rahmawati, Eprisa Purnomo Purnomo Rizky Ridwan Sigit Sugiyanto Supriyono Supriyono Suwarti Suwarti Syah, Hendar Ivan Verdiatmoko, Ardief Candra