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All Journal Techno.Com: Jurnal Teknologi Informasi BERDIKARI : Jurnal Inovasi dan Penerapan Ipteks INTECOMS: Journal of Information Technology and Computer Science JurTI (JURNAL TEKNOLOGI INFORMASI) IJID (International Journal on Informatics for Development) Jurnal Informatika dan Rekayasa Elektronik Jurnal Riset Rekayasa Elektro JISA (Jurnal Informatika dan Sains) International Journal of Engineering, Technology and Natural Sciences (IJETS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) International Journal of Applied Business and Information Systems TIN: TERAPAN INFORMATIKA NUSANTARA Fidelity : Jurnal Teknik Elektro Jurnal Informatika Teknologi dan Sains (Jinteks) Journal of Scientific Research, Education, and Technology Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Rodhiyah Mardhiyyah
Universitas Teknologi Yogyakarta
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other

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Implementasi Payment Gateway Pada Pengembangan Sistem Pemesanan Menu Kafe Berbasis Mobile Tamam, Muhammad Mundzir; Mardhiyyah, Rodhiyah
Techno.Com Vol. 24 No. 2 (2025): Mei 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i2.12642

Abstract

Pemesanan menu pada suatu kedai kopi, umumnya dilakukan dengan pelanggan datang langsung ke lokasi, memilih menu yang diinginkan, dan melakukan pemesanan melalui kasir. Cara tersebut seringkali dijumpai sebagai satu-satunya cara untuk memesan menu kafe. Sistem tersebut juga diterapkan pada Kopi Gambus Krapyak, Yogyakarta dan masih terdapat beberapa kelemahan, seperti waktu yang dibutuhkan apabila antrean melonjak dan kesalahan saat mencatat pesanan pelanggan. Penelitian ini bertujuan untuk mengembangkan sistem pemesanan menu berbasis mobile yang memungkinkan pelanggan untuk memesan dan membayar langsung dari ponsel dan mengurangi antrean dan waktu tunggu. Metode yang digunakan melibatkan perancangan sistem menggunakan Unified Modelling Language (UML) dan pengembangan aplikasi pemesanan berbasis mobile sekaligus sistem pengelolaan kafe berbasis website. Aplikasi pemesanan dibangun dengan menggunakan framework React Native, sedangkan Sistem pengelolaan menggunakan sebuah framework bahasa PHP, yakni CodeIgniter. Sistem yang dibangun ini dilengkapi dengan fitur Payment Gateway dari Midtrans yang memungkinkan pelanggan untuk membayar pesanannya secara cashless langsung di dalam aplikasi sehingga dapat mengurangi antrean. Hasil penelitian menunjukkan bahwa sesudah pengimplementasian aplikasi, pelanggan tidak perlu repot untuk memesan, membayar, dan menunggu di kafe sehingga beberapa antrean pesanan pelanggan dapat dikerjakan secara bersamaan.   Keywords - Aplikasi Mobile, Payment Gateway, Pemesanan Menu, Sistem berbasis website, Unified Modelling Language.
Aplikasi Pemantauan Akademik dan Non-Akademik Siswa Sekolah Dasar Berbasis Web dan Mobile Hidayat, Rizki; Mardhiyyah, Rodhiyah
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8455

Abstract

Student learning assessment is an essential component of education as it measures competency achievement and supports the continuous development of learning strategies. At SDN 2 Bungko Lor, Cirebon, the management of academic and non-academic data is still carried out manually using printed report cards and Excel spreadsheets. This condition limits parents’ ability to monitor their children's learning progress, as results are only accessible at the end of each semester. This study aims to design and develop a Web- and Android-based Academic and Non-Academic Monitoring Application using the Waterfall method to simplify data management, improve information accessibility, and strengthen communication among schools, teachers, and parents. The system was developed using Vue.js for the web application, Flutter for the Android application, PHP as the back-end, and MySQL as the integrated database. The system design applied UML (Use Case, Activity, and Class Diagrams) to model workflows and data structures. The main features include multi-user login, management of grades and attendance as academic data, recording of student behavior as non-academic data, class schedules, and a two-way chat feature to support coordination between schools and parents. Testing using the Black Box method confirmed that all core functionalities operated properly. The implementation of this system provides a more structured presentation of information and enhances collaboration between schools and parents in monitoring students’ academic and non-academic development.
Pengembangan Aplikasi Mobile Berbasis Location-Based Service dalam Mendukung Efisiensi Distribusi Pertanian Padi Yakti, Ikhwan Kuncoro; Mardhiyyah, Rodhiyah
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8545

Abstract

Rice harvest distribution is a critical aspect of maintaining price stability and national food security. However, the traditional distribution system still faces numerous challenges, such as long supply chains, lengthy delivery times, and limited information regarding prices and rice mill locations. These conditions lead to distribution inefficiencies, price fluctuations detrimental to farmers, and a decrease in their welfare. This research focuses on developing a Location-Based Service (LBS) mobile application integrated with a monitoring website to support the efficiency of rice distribution. The developed system is designed to connect farmers, rice mills, and distributors on a single digital platform, enabling a more monitored and integrated distribution process. The mobile application provides features for harvest recording, searching for nearby rice mill locations, real-time market price information, product sales and ordering, transaction logging, agricultural news, and digital payment integration. The monitoring website is intended for relevant agencies to display production and distribution data, progress graphs, and distribution maps of farmers and rice mills. The system was implemented using Flutter for the mobile application, Vue.js for the website, and Firebase Realtime Database as the integrated database, using data from the Cilamaya Wetan Agricultural Technical Service Unit (UPTD). Black Box Testing results indicate that all main system functions such as authentication, product management, ordering, location services, and payment integration are functionally sound and operate according to user requirements. Nevertheless, this testing was limited to technical functionality and did not include usability evaluation or user acceptance in the field. While the traditional distribution process involves 3-4 intermediaries (e.g., farmers, brokers, collectors, mills, large distributors, retailers, end distributors), the developed system offers a design that can shorten this process to only 1-2 intermediaries via a direct channel from farmer to mill, and then to the distributor. Potential analysis indicates that the system could enhance distribution efficiency by reducing intermediaries, improving price transparency, and facilitating easier monitoring by relevant agencies. The mobile application can display rice mill location information on a digital map, accessible to farmers in real-time. This research, therefore, yields a system developed to digitally support rice distribution efficiency. It can serve as a foundation for future research to test the system's implementation in the field and assess its real-world impact on farmer welfare and distribution effectiveness.
Enhancing Convolutional Neural Network Accuracy for Herbal Leaf Classification Using Squeeze and Excitation Attention Utomo, Ragil Gigih; Mardhiyyah, Rodhiyah
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 4 No. 4 (2025): Vol. 4 No. 4 2025
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v4i4.938

Abstract

Accurate identification of herbal plant species is crucial for human health, but remains challenging, even for experts. This study addressed this need by developing a Convolutional Neural Network (CNN) model integrated with an attention mechanism for reliable herbal leaf classification. The research implemented the MobileNetV2 architecture, which was enhanced by incorporating the Squeeze-and-Excitation (SE) attention module. The dataset consisted of 1,500 images across 10 classes of herbal leaves, split into 80% for training, 10% for validation, and 10% for testing. Both the native CNN and the enhanced CNN (CNN-AM) models were trained using TensorFlow and evaluated using standard metrics like accuracy, precision, recall, and F1-score. The comparison results decisively demonstrated the effectiveness of the attention mechanism. Integrating Squeeze-and-Excitation significantly improved performance. The average accuracy of the model increased from 68% to 72%, while the average loss decreased from 1.03 to 1.02. The best-performing CNN-AM model achieved a strong 86% accuracy with a 0.53 loss. These findings confirm that the Squeeze-and-Excitation attention mechanism effectively enhances herbal leaf classification performance, offering a promising foundation for developing reliable and efficient identification systems.
Traffic Sign Recognition System Using YOLOv8 Algorithm Fauzi, Yoga Dwi Rizki; Mardhiyyah, Rodhiyah
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 4 No. 4 (2025): Vol. 4 No. 4 2025
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v4i4.946

Abstract

The advancement of artificial intelligence technologies has driven significant innovation in intelligent transportation systems, particularly in autonomous vehicles that require real-time object detection capabilities. This study develops a web-based traffic sign detection system using the YOLOv8 (You Only Look Once version 8) algorithm. The dataset consists of 5,224 annotated images representing 20 classes of traffic signs, collected through direct image acquisition and managed using Roboflow. The preprocessing stage includes resizing all images to 640×640 pixels and applying data augmentation to enhance model generalization. Model training was conducted on Google Colab using an optimal configuration of 50 epochs, a batch size of 32, and a learning rate of 0.001, resulting in a Precision score of 0.9406, a Recall of 0.9395, and an mAP50 of 0.9748. The trained model was integrated into a Flask-based web application to support image, video, and real-time camera detection. The results indicate that the system is capable of detecting traffic signs with high accuracy and strong computational efficiency.
Klasifikasi Citra Biji Kopi Sangrai Arabika dan Robusta Menggunakan Convolutional Neural Network Al Firdaus, Muhammad Rafi; Mardhiyyah, Rodhiyah; Sanjaya, Fadil Indra
TIN: Terapan Informatika Nusantara Vol 6 No 7 (2025): December 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i7.8695

Abstract

Coffee is one of Indonesia's leading commodities, with two main varieties: Arabica and Robusta. The differences in characteristics between these two types of coffee, such as bean shape, color, and texture, are often difficult to distinguish visually, especially for the general public. This study aims to develop an automatic classification system capable of distinguishing Arabica and Robusta coffee beans using the Convolutional Neural Network (CNN) method with the application of transfer learning based on the MobileNetV2 architecture. The dataset used consists of 210 images of coffee beans taken using a smartphone camera with various positions and lighting, which were then divided into training data (60%), validation data (20%) and test data (20%). Before the training process, data augmentation such as rotation, zoom, flip, and brightness adjustment was performed to enrich image variation and reduce the risk of overfitting. Training was conducted with a learning rate of 0.0001, a batch size of 32, and an Adam optimizer. The results showed that the CNN model with MobileNetV2 transfer learning was able to achieve a training accuracy of 99.21% and a testing accuracy of 97.62%, with relatively low loss values of 0.0682 for training data and 0.1333 for validation data. The application of transfer learning contributes to improving the stability of the training process by utilizing the pre-trained weights from the ImageNet model. Based on these results, it can be concluded that the MobileN-based CNN method.
Rancang Bangun Sistem Pemantauan Baterai PLTS Berbasis IoT pada Lahan Pertanian Zulkhairi Zul; Adelia Octora Pristisahida; Rodhiyah Mardhiyyah; Bledug Kusuma Prasaja; Akhmad Fakhrurrozi; Totok Sarwi Amiyanto; Achmad Agim Machfud
Jurnal Riset Rekayasa Elektro Vol. 7 No. 2 (2025): JRRE VOL 7 NO 2 DESEMBER 2025
Publisher : PROGRAM STUDI TEKNIK ELEKTRO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/jrre.v7i2.24681

Abstract

Teknologi penyiraman otomatis pada lahan pertanian memerlukan sumber energi yang dapat dijangkau. Jauhnya sumber listrik dan luas lahan menjadi salah satu kendala dalam penerapan teknologi penyiraman otomatis. Pembangkit Listrik Tenaga Surya (PLTS) menjadi salah satu solusi sebagai sumber energi yang dapat dimanfaatkan. Pemanfaatan, keberlanjutan, dan keandalan sistem ini sangat bergantung pada performa baterai yang rentan terhadap kondisi Deep Discharge sehingga perlu untuk melakukan pengawasan pada penggunaannya. Penelitian ini melakukan rancang bangun sistem pemantauan kemampuan baterai dan mencegah terjadinya Depth of Discharge (DoD) berlebihan. Pemantauan dilakukan dengan merekam data listrik (tegangan, arus, daya) secara otomatis ke dalam spreadsheet dan mengendalikan sistem dari jarak jauh melalui aplikasi Blynk. Berdasarkan pengujian sistem monitoring berhasil memantau tegangan baterai. Baterai yang digunakan dapat bekerja pada siang hari dengan tegangan lebih dari 11V. Pada malam hari baterai mengalami penurunan tegangan hingga 9V namun sistem dapat memutus aliran penggunaan listrik saat tengangan kurang dari 11V untuk menghindari terjadinya DoD. Cara ini dapat digunakan untuk penggunaan PLTS secara luas agar kualitas baterai dapat terjaga
Pendampingan Sosial Dan Implementasi Teknologi AR-IoT Dalam Penguatan Pendidikan SMK Smart Al Muhsin: Pengabdian Ari Sugiharto; Rodhiyah Mardhiyyah; Al Musa Karim
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 3 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 3 (Januari 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i3.3902

Abstract

Kegiatan pengabdian kepada masyarakat ini dilaksanakan di SMK Smart Al Muhsin dengan tujuan meningkatkan kualitas pembelajaran praktik dan kedisiplinan siswa di lingkungan pesantren. Permasalahan yang dihadapi adalah keterbatasan sarana pembelajaran, rendahnya minat belajar, serta belum adanya sistem presensi terintegrasi. Solusi yang diterapkan meliputi penerapan Augmented Reality (AR) sebagai media pembelajaran interaktif, sistem presensi berbasis Internet of Things (IoT) untuk pemantauan kehadiran, serta pendampingan sosial berupa seminar, workshop desain poster, dan sosialisasi bijak menggunakan gadget. Hasil kegiatan menunjukkan peningkatan keterampilan guru dan siswa dalam penggunaan AR, kemampuan tenaga pendidik dalam mengelola sistem presensi IoT, serta meningkatnya kesadaran siswa mengenai kedisiplinan dan penggunaan gadget secara bijak. Luaran berupa perangkat AR, mesin presensi IoT, poster, dan banner diharapkan dapat dimanfaatkan secara berkelanjutan.
ANALISIS SENTIMEN PUBLIK TERHADAP BADAN INVESTASI DANANTARA PADA MEDIA SOSIAL X MENGGUNAKAN MODEL INDOBERT Setiawan Putra Mahardika; Rodhiyah Mardhiyyah; Fadil Indra Sanjaya
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 4 (2025): EDISI 26
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i4.6804

Abstract

Pembentukan Badan Pengelola Investasi Daya Anagata Nusantara (Danantara) sebagai lembaga pengelola investasi nasional telah memicu beragam reaksi masyarakat Indonesia. Persepsi publik memainkan peran penting dalam kepercayaan dan keberhasilan lembaga ini, sehingga diperlukan analisis sentimen yang objektif dan sistematis. Penelitian ini bertujuan menganalisis sentimen publik terhadap Danantara menggunakan model IndoBERT, sebuah model trafo yang dioptimalkan untuk Bahasa Indonesia. Data opini publik dikumpulkan dari platform media sosial melalui teknik scraping , kemudian diproses melalui tahapan preprocessing (cleaning, normalisasi, tokenisasi, translasi) sebelum dilakukan pelabelan otomatis dan sebagian manual. Model dibor dan dievaluasi menggunakan metrik akurasi, presisi, recall , dan F1-score . Hasil menunjukkan IndoBERT mampu mengklasifikasikan sentimen dengan akurasi 88,77% dan rata-rata F1-score 88,76%. Hasil analisis menemukan sebagian besar opini masyarakat terhadap Danantara bersifat negatif (58,6%), sedangkan 41,4% positif. Penelitian ini memberikan kontribusi pada pengembangan penerjemahan bahasa alami (NLP) berbahasa Indonesia serta menjadi masukan bagi pemerintah dalam menyebarkan persepsi publik terhadap kebijakan strategis nasional.
Co-Authors Abadi, Anis Susila Abdul Haris Kuspranoto Achmad Agim Machfud Adelia Octora Pristisahida Ahmad Syaifudin Akhmad Fakhrurrozi Al Firdaus, Muhammad Rafi Al Musa Karim Alfatih, Muhammad Fa’iz Ali Habibie, Raihan Ghifari Aryanto, Putri Marceliana Bayu Ari Pratama Bledug Kusuma Prasaja Devi Ratnasari Evodi, Gabriel Jevon Fadil Indra Sanjaya Fauzi, Yoga Dwi Rizki Haaerun, Hazim Althaf Hayati, Nuvita Nur Heni Pujiastuti Hidayat, Rizki Indriaswari, Raden Ayu Janica Rahmaditha Junanda, David Bagus Machfud, Achmad Agim Nur Istiqomah Nuryadi, Satyo Prasetya, R. Imam Budi Pratiwi, Chyntia Elsa Salsabilla, Nazwa Aila Setiawan Putra Mahardika Subrata, Febrina Cinta Sugiharto, Ari Tamam, Muhammad Mundzir Taruno, Restiadi Bayu Totok Sarwi Amiyanto Utomo, Ragil Gigih Van Bawono, Maganda Jannati Yakti, Ikhwan Kuncoro Yana Hendriana Zulkhairi Zulkhairi Sofyan Zulkhairi Zul