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All Journal snimed Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI J I M P - Jurnal Informatika Merdeka Pasuruan PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat JISA (Jurnal Informatika dan Sains) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Sistem Informasi dan Sistem Komputer Djtechno: Jurnal Teknologi Informasi JUTECH : Journal Education and Technology JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Artificial Intelligence and Digital Business Mekongga: Jurnal Pengabdian Masyarakat
Fadil Indra Sanjaya
Universitas Teknologi Yogyakarta
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts 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 Public Health Social Sciences Veterinary Other

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Deteksi Tingkat Stres Mahasiswa Dengan Logika Fuzzy Tsukamoto Aryanto, Fajar Hanggoro Dwi; Syuhada, Arya Firgi; Putra, Fajar Permana; Mahardika, Setiawan Putra; Jayanegara, Adi Prabu; Sanjaya, Fadil Indra
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.1042

Abstract

Stres pada mahasiswa merupakan permasalahan serius yang dapat berdampak negatif terhadap kesehatan mental dan performa akademik apabila tidak ditangani dengan baik. Dampak tersebut tidak hanya terbatas pada penurunan prestasi akademik, tetapi juga dapat mengarah pada gangguan psikologis jangka panjang yang menghambat proses pembelajaran dan perkembangan pribadi mahasiswa. Penelitian ini bertujuan untuk mengembangkan sistem deteksi tingkat stres mahasiswa menggunakan metode logika fuzzy Tsukamoto. Sistem ini dirancang untuk mengelola data subjektif dan tidak pasti berdasarkan lima parameter utama, yaitu kualitas tidur, performa akademik, hubungan mahasiswa-dosen, dukungan sosial, dan kondisi lingkungan. Proses inferensi dilakukan melalui pembentukan himpunan fuzzy dan 48 aturan IF-THEN yang disusun berdasarkan kombinasi kelima parameter tersebut. Penelitian ini melibatkan penyebaran kuesioner kepada mahasiswa Program Studi Informatika Universitas Teknologi Yogyakarta untuk memperoleh data yang kemudian diproses dalam sistem fuzzy. Hasil akhir dari sistem ini berupa nilai crisp yang menunjukkan tingkat stres mahasiswa, yang dikategorikan dalam level normal hingga tinggi. Diharapkan sistem ini dapat menjadi alat bantu bagi institusi pendidikan dalam mendeteksi dan menangani gejala stres mahasiswa secara cepat dan tepat.
Classification of Nutritional Status Using the Fuzzy Mamdani Method : Case Study at Banjar City Hospital Nugraha, Muhammad Satria; Sanjaya, Fadil Indra
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9893

Abstract

The problem of nutritional status in adults requires accurate and adaptive classification methods. This study aims to develop a decision support system using the Fuzzy Mamdani method to classify nutritional status based on Body Mass Index (BMI). A dataset consisting of 237 anthropometric records from Banjar City Regional General Hospital was utilized. The system applies five fuzzy rules to map BMI values into nutritional categories: malnutrition, underweight, normal, overweight, and obesity. The classification process involves fuzzification, inference, and defuzzification using the centroid method. System performance evaluation shows an overall accuracy of 91.13%, with the highest classification precision achieved in the normal category (98.54%) and the lowest in the malnutrition category (30.77%). The results demonstrate that the Fuzzy Mamdani method is effective for nutritional classification, although refinement is needed for underrepresented categories. This system can serve as a useful tool for supporting clinical decision-making in public health services.
Implementasi Sistem Monitoring Potensi, Ancaman, dan Demografi Desa Wisata Jatimulyo Berbasis Data Driven: Implementation of Data-Driven Monitoring System for Potential, Threats, and Demographics of Jatimulyo Tourism Village Zakariyah, Muhammad; Sanjaya, Fadil Indra; Kalifia, Anna Dina; Ar-Razi Ab, Fariddudin; Hidayah, Taufik; Khoeri, Elfan Fanhas; Nurjaman, Muhammad
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 9 No. 2 (2024): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v9i2.5946

Abstract

Village development and regional governance are central to Indonesia's national development agenda. However, in practice, monitoring demographic data, potential resources, and potential threats often transpires without the utilization of technology, yielding less accurate information. Furthermore, numerous villages, including Jatimulyo Tourism Village in Kulon Progo, have yet to fully embrace technology to harness the full potential of their local resources. Within this context, a pressing need exists for technological innovations to leverage the power of data in facilitating informed decision-making. The primary objective of this community engagement endeavor is to establish a data-driven village monitoring system to enhance the efficacy and efficiency of village monitoring processes while simultaneously promoting transparency, accountability, and community participation. The data-driven approach facilitates the collection of precise, automated data. Technology is anticipated to play a pivotal role in rectifying inaccuracies in information, offering crucial support to local government authorities and tourism managers in making well-informed decisions. This community service initiative's tangible outcome is creating a village monitoring system dashboard designed to facilitate decision-making processes and foster greater community involvement. Moreover, it is envisioned that this undertaking will maximize rural development and regional governance, instigate data-driven decision-making practices, foster the development of a robust village ecosystem, and ultimately enhance the overall well-being of the residents of Jatimulyo Tourism Village.
PENERAPAN METODE FUZZY MAMDANI DALAM PENILAIAN KUALITATIF VISIBILITAS WARNA DAN KETERBACAAN TEKS PADA SISTEM DESAIN BERDASARKAN STANDAR AKSESIBILITAS WCAG 2.1 Putra, Muhammad Ali Ali Pratama; Riyadi, Akhmad Zaqi; Pratama, Rizki Purnomo; Adriansyah, M. Ridha Ansari; Qalam, Mouhammad Tariqoul; Sanjaya, Fadil Indra
JUTECH : Journal Education and Technology Vol 6, No 1 (2025): JUTECH JUNI
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v6i1.4944

Abstract

Aksesibilitas digital, khususnya visibilitas warna dan keterbacaan teks, menjadi elemen krusial dalam desain antarmuka yang inklusif. Namun, evaluasi konvensional berbasis WCAG 2.1 cenderung kuantitatif dan kaku, gagal menangkap persepsi visual manusia yang subjektif. Penelitian ini menghasilkan FuzzChecker, aplikasi web berbasis metode Fuzzy Mamdani yang mengintegrasikan standar WCAG 2.1 untuk mengevaluasi aksesibilitas visual pada sistem desain. Sistem ini menawarkan pendekatan human-centered yang lebih fleksibel dibandingkan metode konvensional yang bersifat deterministik. Dengan model pengembangan waterfall, FuzzChecker memproses variabel input seperti dimensi perangkat, ukuran teks, luminositas, dan saturasi melalui tahapan fuzzifikasi, inferensi berbasis aturan, dan defuzzifikasi metode centroid. Aplikasi ini, yang telah di-deploy di Vercel, menghasilkan dua output: skor kontras sesuai WCAG dan visibilitas kontekstual berdasarkan kondisi perangkat. Pendekatan fuzzy logic ini efektif dalam membantu desainer menciptakan desain digital yang inklusif, terutama bagi pengguna dengan keterbatasan visual, secara intuitif dan adaptif.
Deteksi Kematangan Buah Tomat Menggunakan Convolutional Neural Network Berdasarkan Ekstraksi Fitur Warna dan Tekstur Jayanegara, Adi Prabu; Sejati, Rr. Hajar Puji; Sanjaya, Fadil Indra
TIN: Terapan Informatika Nusantara Vol 6 No 6 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i6.8580

Abstract

Determining the ripeness level of tomatoes is a crucial aspect in ensuring consumption quality. However, the methods commonly used by the public are still manual and subjective, relying on visual observations of color and surface texture. This limitation leads to a high rate of errors in selecting fruits suitable for consumption or processing purposes, potentially resulting in food waste, economic loss, and decreased efficiency within the agricultural supply chain. Without the development of a technology-based assistance system, these impacts will continue to recur and may threaten food security on both micro and macro scales. As a solution, this study develops an intelligent system based on digital image processing to detect tomato ripeness levels. The system utilizes color feature extraction using the HSV histogram and texture feature extraction using the Local Binary Pattern (LBP), which are then processed through a Convolutional Neural Network (CNN) model for image classification. The results show that the system achieves an accuracy of 95.12%, outperforming (or matching) state-of-the-art end-to-end CNN-based methods on the same or similar datasets, demonstrating the effectiveness of HSV-LBP features. The implementation of this system is expected to help users make more accurate decisions when selecting tomatoes according to their needs, reduce waste, and improve consumption 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.
Golden Goal Futsal Court Rental Mobile Application Using the First Come First Serve (FCFS) Algorithm and Payment Gateway Integration Sirajudin, Sirajudin; Sanjaya, Fadil Indra; Waluyo, Anita Fira
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2545

Abstract

The futsal pitch rental process at Golden Goal is still done manually through direct communication or text messages, which often results in various problems such as unstructured booking queues, schedule conflicts due to the lack of a clear queuing system, and late payments. These problems result in low operational efficiency and an increased potential for scheduling errors. This research aims to develop a mobile-based futsal pitch rental application equipped with the implementation of the First Come First Serve (FCFS) algorithm to ensure the booking process is carried out based on the user's arrival time in a fair and orderly manner. The system development method used is the Waterfall model, which includes requirements analysis, design, implementation, testing, and maintenance. The application was developed using the Flutter framework because it has the ability to produce Android and iOS applications with only a single codebase, faster development time, and stable and responsive interface performance. These advantages make Flutter suitable for building a real-time booking system that requires fast interaction and a consistent user experience. Furthermore, the application is integrated with Midtrans services as a payment gateway to facilitate automatic digital payment transactions. Testing results using the black-box method indicate that all key features, including schedule selection, FCFS-based queuing mechanism, payment processing, and rental data management, have run well as needed. The implementation of this system has proven to be able to reduce schedule conflicts, improve the accuracy of the booking process, and increase the efficiency of rental management at Golden Goal. Thus, this application can be an effective and modern solution to address the problem of futsal field rentals that have been handled manually.
PENGEMBANGAN APLIKASI RESERVASI PEMANCINGAN ONLINE BERBASIS ANDROID STUDI KASUS PEMANCINGAN KATINENUNG: DEVELOPMENT OF AN ANDROID-BASED ONLINE FISHING RESERVATION APPLICATION. KATINENUNG FISHING CASE STUDY Hamdani Hamdani; Fadil Indra Sanjaya
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 1 (2025): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i1.5511

Abstract

Katineung Fishing Pond is a fishing venue that currently still uses a conventional booking process. Customers must come in person or call to reserve a spot, which often leads to uncertainty regarding availability and booking errors. Additionally, limited promotion has resulted in a lack of information about the fishing services available to the public. To address these issues, a more efficient and modern online reservation system is needed. This study utilizes the Rapid Application Development (RAD) method, which allows for rapid and iterative application development. The project aims to build an online reservation application that simplifies the booking process for customers and helps the management in handling reservation data. The application is developed using Dart programming language with the Flutter framework for the frontend and PHP with the Laravel framework for the backend, along with MySQL as the database. This system is expected to improve booking efficiency, provide real-time availability information, and enhance customer satisfaction. With this system, operational efficiency is anticipated to increase, customer experiences to improve, and the competitiveness of Katineung fishing pond to strengthen.
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.
PENGENALAN AKSEN SUARA INDONESIA JAWA DAN SUNDA MENGGUNAKAN METODE LONG SHORT-TERM MEMORY Fajar Permana Putra; RR. Hajar Puji Sejati; 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.v7i4.6829

Abstract

Teknologi pengenalan suara saat ini masih menghadapi beberapa tantangan dalam mengenali aksen lokal Indonesia. Sedangkan pengenalan suara menjadi bagian penting dari berbagai aplikasi, termasuk asisten virtual, chatbot, dan sistem dengan interaksi berbasis suara lainnya. Penyebabnya adalah keanekaragaman aksen di Indonesia. Model konvensional sering kesulitan dalam mengenali variasi aksen karena hanya dilatih menggunakan bahasa Indonesia standar. Sehingga diperlukan pelatihan model dengan aksen baru untuk meningkatkan akurasi. Penelitian ini bertujuan untuk mengembangkan model pengenalan aksen Indonesia khususnya Jawa dan Sunda menggunakan deep learning, serta mengimplementasikannya ke dalam sistem berbasis web. Model dibangun menggunakan algoritma LSTM, dengan ekstraksi fitur MFCC dan untuk sistem akan dikembangkan dengan menggunakan framework Flask. Pendekatan ini diharapkan dapat meningkatkan akurasi pengenalan aksen di Indonesia serta mendukung pengembangan teknologi suara yang lebih inklusif dan adaptif. Hasil sementara menunjukkan hasil yang positif dalam hal akurasi pengenalan aksen. Pelatihan model LSTM dengan ekstraksi fitur MFCC dapat menghasilkan model dengan ketepatan dalam mengenali pola dan karakteristik dari suara setiap aksen dengan akurasi sebesar 89,66% dengan nilai loss yang tergolong rendah yaitu 0,1980. Selain itu model dapat diimplementasikan dengan baik pada sistem berbasis web yang dikembangkan dan dapat digunakan oleh pengguna dengan mudah dan efisien.
Co-Authors Adriansyah, M. Ridha Ansari Al Firdaus, Muhammad Rafi Amrizal Novianto Anna Dina Kalifia Ar-Razi Ab, Fariddudin Aryanto, Fajar Hanggoro Dwi Astrianty, Ledy Elsera Dadang Heksaputra Dadang Heksaputra Dini Erlinawati Fajar Permana Putra Fajar Permana Putra Febri Liantoni Hamdani Hamdani Heksaputra, Dadang Jayanegara, Adi Prabu Kalifia, Anna Dina Khoeri, Elfan Fanhas Mabruri, Abdul Basith Mahardika, Setiawan Putra Muhammad Fachrie Mulia Sulistiyono Nugraha, Muhammad Satria Nurjaman, Muhammad Nuzula Afini Pramudwiatmoko, Arif Pratama, Mohammad Bayu Pratama, Rizki Purnomo Putra, Muhammad Ali Ali Pratama Qalam, Mouhammad Tariqoul Rahmatullah, Andi Ristianto, Andika Riyadi, Akhmad Zaqi Rodhiyah Mardhiyyah Rr. Hajar Puji Sejati Setiawan Putra Mahardika Sirajudin Sirajudin Sulistyo Dwi Sancoko Syuhada, Arya Firgi Taufik Hidayah Waluyo, Anita Fira Yuliana Rizki Ikhsanty Zahra Septa Hati