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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Techno.Com: Jurnal Teknologi Informasi Elkom: Jurnal Elektronika dan Komputer Seminar Nasional Informatika (SEMNASIF) WARTA Emitor: Jurnal Teknik Elektro Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika INTECOMS: Journal of Information Technology and Computer Science Compiler KACANEGARA Jurnal Pengabdian pada Masyarakat The IJICS (International Journal of Informatics and Computer Science) Indonesian Journal of Business Intelligence (IJUBI) International Journal of Informatics and Computation Journal of Applied Engineering and Technological Science (JAETS) INFORMASI (Jurnal Informatika dan Sistem Informasi) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Pendidikan dan Teknologi Indonesia Emerging Information Science and Technology Proceeding ISETH (International Summit on Science, Technology, and Humanity) Jurnal Bakti Nusa Prosiding University Research Colloquium Abdi Teknoyasa Mestro Shahih : journal of islamicate multidisciplinary The Indonesian Journal of Computer Science Jurnal Pengabdian Teknik dan Sains (JPTS) ABDIMASTEK Computing and Information System Journal Dedikasi Nusantara Indonesian Journal on Learning and Advanced Education (IJOLAE) Proceeding of Informatics Collaborations and Dessimenation Meeting (Infocoding)
Aris Rakhmadi
Universitas Muhammadiyah Surakarta
Religion Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Deep Learning-Enhanced Kitabah Application for Inclusive and Adaptive Quranic Sign Language Education Rakhmadi, Aris; Yudhana, Anton; Sunardi, Sunardi; Rahmawati, Yuli
Indonesian Journal on Learning and Advanced Education (IJOLAE) Vol. 8, No. 2, May 2026
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/ijolae.v8i2.15390

Abstract

People with hearing and speech disabilities (PHSD) continue to face barriers in accessing Quranic literacy education due to the dominance of auditory–verbal instructional approaches and the limited availability of adaptive digital learning environments. Although sign language recognition (SLR) technologies have advanced significantly, most existing systems are not aligned with pedagogically and theologically grounded Quranic learning frameworks. This study aims to develop and evaluate a deep learning-enhanced Kitabah application to support inclusive, adaptive, and technology-enhanced Quranic sign language education for PHSD learners. The study employed two approaches: (1) the development of a Kitabah-based mobile learning application integrating interactive visual–motor learning features, and (2) the implementation of a deep learning-based SLR model using ResNet-18 with transfer learning for static Hijaiyyah gesture recognition. The mobile application was evaluated through black-box testing and the System Usability Scale (SUS), while the SLR model was assessed using accuracy, precision, recall, and F1-score metrics. Results showed that all application functionalities operated successfully, with the application achieving a SUS score of 78.06, indicating good usability and accessibility. The SLR model achieved 98% classification accuracy across 31 Hijaiyyah sign classes, demonstrating strong recognition performance. These findings indicate that integrating the Kitabah method with deep learning and mobile learning technology can support progressive, inclusive, and adaptive Quranic literacy education through AI-assisted and learner-centered educational experiences for PHSD learners.
Sistem Inventori Berbasis Web Pada CV. Tirtaria Perusahaan Penyedia Ikan Konsumsi Air Tawar Wahyu Akbar; Aris Rakhmadi
INFORMASI (Jurnal Informatika dan Sistem Informasi) Vol 18 No 1 (2026): INFORMASI (Jurnal Informatika dan Sistem Informasi)
Publisher : LPPM STMIK Indonesia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37424/informasi.v18i1.557

Abstract

Pengelolaan barang pada perusahaan penyedia ikan konsumsi yaitu CV. Tirtaria hingga kini masih dijalankan secara konvensional sehingga memunculkan ketidaktepatan data, ketidaktepatan waktu pelaporan, dan ketidaksesuaian stok yang berdampak pada efek- tivitas operasional serta kualitas pelayanan. Penelitian bertujuan membangun sistem in- formasi inventori berbasis web untuk meningkatkan akurasi manajemen stok dan efisiensi kerja. Pengembangan sistem menggunakan metode Waterfall dimana setiap fase pengerjaan wajib diselesaikan sebelum ke fase berikutnya. Pengembangan sistem dilaksanakan melalui serangkaian tahapan yang mencakup analisis kebutuhan, perancangan sistem, implementasi sistem, dan pengujian sistem agar sesuai dengan kebutuhan operasional perusahaan. Metode First In First Out (FIFO) digunakan untuk memastikan produk yang lebih awal diterima akan menjadi produk yang lebih awal didistribusikan sehingga kualitas produk tetap terjaga. Pengujian sistem menggunakan metode Black Box membuktikan bahwa keseluruhan fungsionalitas sistem telah berjalan sebagaimana mestinya. Selain itu, pengujian System Usability Scale (SUS) terhadap 23 responden menghasilkan skor 78,59 dengan kategori Good. Hasil penelitian memper- lihatkan bahwa sistem inventori yang dikembangkan berhasil mengoptimalkan efisiensi pengelolaan data dan meningkatkan kualitas layanan pada CV Tirtaria
PENGEMBANGAN ALAT MONITORING DAN PENDETEKSI KUALITAS UDARA BERDASARKAN PARAMETER CO DAN CO2 BERBASIS IOT Atha Rahmad Zulfikhar; Aris Rakhmadi
INTECOMS: Journal of Information Technology and Computer Science Vol. 9 No. 2 (2026): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/6xw9k946

Abstract

Polusi udara menjadi permasalahan serius di kota-kota besar di Indonesia seperti Jakarta, Bandung, Semarang, dan Surabaya akibat meningkatnya jumlah kendaraan bermotor dan aktivitas industri. Kondisi ini menyebabkan tingginya kadar gas berbahaya seperti karbon monoksida (CO) dan karbon dioksida (CO2) yang berdampak negatif terhadap kesehatan manusia. Penelitian ini mengembangkan sistem pemantauan kualitas udara berbasis Internet of Things (IoT) untuk memantau kadar polutan secara real-time menggunakan sensor MQ-135 dan mikrokontroler NodeMCU ESP8266. Hasil penelitian menunjukkan bahwa alat berhasil dikalibrasi dengan alat acuan, dengan rata-rata error sebesar 9,23% untuk CO dan 1,05% untuk CO2, sehingga pembacaan sensor dinyatakan akurat dan stabil. Data hasil pengukuran dikirim secara real-time ke platform ThingSpeak untuk visualisasi serta ke Telegram sebagai notifikasi otomatis. Sistem juga dilengkapi LCD 16x2 dan LED RGB sebagai indikator kondisi kualitas udara. Pengujian dilakukan menggunakan berbagai sumber polutan seperti asap pembakaran kertas, rokok, gas korek api, dan tisu, yang menunjukkan bahwa sensor mampu merespons perubahan kualitas udara dengan cepat. Selain itu, pengujian software membuktikan bahwa sistem dapat mengirimkan data secara konsisten setiap 10 menit dengan hasil yang sesuai antara Telegram dan ThingSpeak. Secara keseluruhan, sistem yang dikembangkan mampu bekerja dengan baik dan efektif sebagai alat monitoring kualitas udara, serta memberikan informasi yang cepat, akurat, dan mudah dipahami oleh pengguna.  
Integrasi Metode Farnsworth-Munsell pada Aplikasi Web untuk Identifikasi Gangguan Penglihatan Warna Muhammad Abdurrahman Hasan; Aris Rakhmadi
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 4 (2026): Juni 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i4.9725

Abstract

Gangguan penglihatan warna sering kali tidak disadari sehingga dapat menghambat aktivitas pendidikan maupun pekerjaan. Penelitian ini bertujuan mengembangkan aplikasi web sebagai instrumen skrining mandiri melalui integrasi metode Farnsworth-Munsell. Sistem dibangun menggunakan framework Laravel dengan pola arsitektur Model-View-Controller (MVC) dan model pengembangan Waterfall. Kontribusi utama penelitian ini adalah digitalisasi prosedur tes fisik ke dalam antarmuka web yang mampu melakukan kalkulasi Total Error Score (TES) secara otomatis dan sistematis berdasarkan posisi koordinat warna yang dimasukan pengguna. Evaluasi fungsional menggunakan metode Black Box menunjukkan bahwa seluruh fitur integrasi metode dan pemrosesan skor berjalan valid. Pengujian aspek kegunaan melalui instrumen System Usability Scale (SUS) menghasilkan skor rata-rata 72,50, yang menempatkan sistem pada kategori Good (Layak). Hasil penelitian menyimpulkan bahwa aplikasi ini efektif berfungsi sebagai alat pemindaian awal yang aksesibel bagi masyarakat umum tanpa memerlukan instalasi perangkat lunak tambahan, sekaligus menyediakan standarisasi perhitungan skor tes buta warna secara digital. Aplikasi ini dirancang sebagai sarana skrining awal secara mandiri dan tidak dimaksudkan untuk menggantikan hasil diagnosis medis profesional dari dokter spesialis mata.
Acoustic Pattern Classification in Female Voice Using K-Nearest Neighbor with MFCC Feature Extraction Aris Rakhmadi; Joko Handoyo; Irma Yuliana; Dimara Kusuma Hakim
Mestro: Jurnal Teknik Mesin dan Elektro Vol 8 No 01 (2026): Edisi Juni (In Progres)
Publisher : Fakultas Teknik Universitas 17 Agustus 1945 Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47685/mestro.v8i01.794

Abstract

This study investigates the classification of acoustic patterns in female voice signals using the K-Nearest Neighbors (KNN) algorithm and Mel-Frequency Cepstral Coefficients (MFCCs). Acoustic features derived from speech signals contain important spectral information that can be utilized to distinguish variations in voice characteristics. However, variability in speech signals and overlapping feature distributions present challenges for accurate classification. To address this issue, this study employs a structured approach comprising data preparation, MFCC feature extraction, and KNN classification. Each speech sample is represented as a 58-dimensional MFCC feature vector, and the dataset is split into testing and training subsets using a 20:80 ratio. The KNN model is trained using Euclidean distance and evaluated on precision, accuracy, recall, and F1-score. The results show that the proposed approach reaches an accuracy of 87.75%, indicating that MFCC features effectively capture acoustic characteristics in female voice signals. The confusion matrix analysis reveals that categories with distinct acoustic patterns, such as surprise and calm, achieve higher classification performance, whereas overlapping categories, such as happy and disgust, lead to increased misclassification. These findings demonstrate that KNN can serve as a reliable baseline method for acoustic pattern classification. However, further improvements can be achieved through enhanced feature representation and more advanced classification models.
Next-Gen Academic Workflow: Integrating LaTeX and AI in the DIKI Community Service Program Dimara Kusuma Hakim; Aris Rakhmadi
Jurnal Pengabdian Teknik dan Sains (JPTS) Vol. 6 No. 2 (2026): Juli 2026
Publisher : Lembaga Publikasi Ilmiah dan Penerbitan (LPIP)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perkembangan teknologi digital dan kecerdasan buatan (Artificial Intelligence/AI) telah membawa perubahan signifikan dalam dunia akademik, khususnya dalam proses penulisan, pengelolaan referensi, dan analisis data. LaTeX sebagai sistem penyusunan dokumen ilmiah tetap menjadi standar emas dalam penulisan akademik karena konsistensi dan fleksibilitasnya. Integrasi LaTeX dengan AI membuka peluang terciptanya Next-Gen Academic Workflow yang lebih efisien, produktif, dan adaptif terhadap kebutuhan akademisi. Kegiatan pengabdian masyarakat melalui Webinar Abdimas DIKI pada tanggal 26 Juni 2026 bertujuan memperkenalkan konsep integrasi LaTeX dan AI kepada dosen, mahasiswa, dan praktisi akademik. Metode pelaksanaan berupa workshop daring dengan tahapan perencanaan materi, persiapan teknis, demonstrasi langsung, serta dokumentasi dan evaluasi. Materi mencakup instalasi LaTeX, penulisan dokumen dasar, penyusunan tabel dan gambar, pengelolaan kutipan dengan BibTeX, serta pemanfaatan AI untuk pencarian referensi, interpretasi hasil analisis, dan koreksi sintaks. Hasil kegiatan menunjukkan ketercapaian indikator yang baik: tingkat kehadiran peserta mencapai 90%, partisipasi aktif dalam diskusi 73%, keberhasilan mencoba skrip LaTeX sederhana 68%, pemahaman integrasi AI 80%, dan motivasi mengadopsi workflow baru 84%. Hambatan yang muncul terutama terkait instalasi perangkat lunak dan isu etika penggunaan AI, namun hal ini justru memperkaya diskusi kritis. Kesimpulannya, kegiatan ini berhasil meningkatkan literasi digital, keterampilan teknis, serta motivasi peserta untuk mengadopsi workflow akademik generasi baru. Pengabdian masyarakat berbasis teknologi digital ini dapat menjadi model berkelanjutan untuk memperkuat kualitas publikasi ilmiah dan mendukung implementasi Tri Dharma Perguruan Tinggi.
Artificial Intelligence-Based Aircraft Detection for Enhanced Aviation Safety and Air Traffic Management Ayuningtyas, Astika; Novelia Gunawan, Saomi; Ira Candra Dewi Wulan, Puspa; Medianto, Rully; Winiarti, Sri; Rakhmadi, Aris
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 3 (2026): JUTIF Volume 7, Number 3, June 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.3.5661

Abstract

The rapid growth of international air traffic has made maintaining aviation safety and managing air traffic efficiently increasingly complex, particularly in identifying aircraft in constantly changing airspace. Traditional monitoring systems such as radar and Automatic Dependent Surveillance-Broadcast (ADS-B) have limitations in operating at low altitudes, in adverse weather, and in overcrowded environments, which can reduce the ability to understand surrounding conditions. This research proposes an artificial intelligence-based visual detection system aimed at enhancing real-time aircraft identification and improving air traffic monitoring. The system uses a YOLO-based deep learning model enhanced with a special attention mechanism and data augmentation to increase accuracy, flexibility, and operational resilience. The dataset used covers various flight situations, such as variations in light, viewing angles, and background complexity, to train the model. The model's test results show that it can correctly identify 95.24% of passenger planes, 92.4% of blimps, and 90% of fighter planes. The average overall precision (mAP) is over 90%. This system is also capable of real-time inference with precision and recall consistently above 85% under various conditions. Compared with conventional vision-based detection methods, this system demonstrates superior localization capabilities and robustness, making it suitable for use in real-world flight surveillance and air traffic management. In conclusion, this AI-based framework provides a practical and scalable solution that can improve flight safety and promote smarter air traffic management.
AUTOMATED ACNE TYPE IDENTIFICATION THROUGH FORWARD CHAINING APPROACH Aris Rakhmadi; Naura Fikamelyalla; Sri Winiarti; Esi Putri Silmina; Umi Fadlillah; Yusuf Sulistyo Nugroho
Indonesian Journal of Business Intelligence (IJUBI) Vol 8 No 1 (2025): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v8i1.5377

Abstract

Acne, a prevalent dermatological condition, poses significant physical and psychological challenges. Despite its widespread impact, timely and accessible diagnosis remained a barrier for many, emphasizing the need for innovative solutions. This study introduced an online consultation system for acne-type identification, leveraging a forward chaining approach within an AI-powered expert system. The system analyzed user-reported symptoms—such as severity, location, and appearance—using a rule-based inference mechanism to provide accurate diagnoses and tailored treatment recommendations. Developed using a prototype model, the system’s knowledge base was enriched through observations, literature reviews, and expert interviews, ensuring reliability and clinical relevance. Iterative testing, including black-box evaluations and a System Usability Scale (SUS) assessment, confirmed the system's functionality and user satisfaction, with a SUS score of 86.5, indicating high acceptance. The system bridged critical gaps in dermatological care, particularly for underserved communities, by enabling rapid, user-centric diagnostics and personalized recommendations. The research underscored the transformative potential of artificial intelligence and expert systems in healthcare. By integrating accessibility, scalability, and precision, the proposed system addressed the challenges of acne management and set a foundation for future advancements in dermatological diagnostics.
Implementation of an Integrated E-Learning Module for Academic Summarization in English for Academic Purposes Aris Rakhmadi; Yanti Haryanti
ABDIMASTEK Vol. 4 No. 2 (2025): Desember
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to develop and implement an integrated e-learning module to enhance academic summarization skills in English for students at Universitas Muhammadiyah Surakarta (UMS). The module was designed to support English for Academic Purposes (EAP) learning and was integrated into regular courses. Through a combination of online and face-to-face learning, the module covered four key areas: summary organization, grammatical accuracy, academic vocabulary, and summarization techniques. The implementation involved a series of workshops and guided practice sessions, supported by self-directed learning through an e-learning platform. Quantitative evaluation was conducted using the English Proficiency Exam (EPE) and the Computerized Assessment System (CAS) across three student groups, with assessments administered on three platforms: traditional, Schoology, and OpenLearning. The results showed that students using the Schoology platform achieved the highest average EPE score (422.99). In contrast, CAS results were comparable across platforms (3.20 for the traditional group, 3.16 for Schoology, and 3.15 for OpenLearning). These findings indicate that the e-learning module is efficacious in improving academic summarization skills and can be sustainably implemented to support academic literacy at UMS.
Introducing and Evaluating an E-Learning Platform for Hajj Guide Certification through Community Service Using the System Usability Scale Aris Rakhmadi; Syarifur Rizal Miftahul Hasan
ABDIMASTEK Vol. 5 No. 1 (2026): Juli
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/abdimastek.v5i1.5398

Abstract

The rapid advancement of information technology has driven digital transformation across various training and certification activities; however, the Hajj guide certification process is still conducted through fragmented, non-integrated platforms, leading to inefficiencies in material distribution, task management, and participant evaluation. This community service activity aims to evaluate the usability of an e-learning system as a potential digital solution for Hajj guide certification. The implementation method adopts a structured simulation-based approach, including needs assessment, system demonstration, user interaction, and usability evaluation using the System Usability Scale (SUS) involving 23 respondents with relevant certification experience. The results indicate an average SUS score of 71.13, which falls into the “acceptable” category, reflecting an adequate level of usability and suggesting that the system meets fundamental usability requirements. Therefore, the proposed e-learning system shows potential as a digital solution to more structurally support certification processes. However, further improvements in interface design and navigation are necessary to enhance the overall user experience.
Co-Authors Abdul Azis Ady Purna Kurniawan Agus Triyono Aji, Doni Kurnia Aldino Kemal Adi Gumawang Anshori Anshori, Anshori Anton Yudhana Anton Yudhana Ariyanto, Ragil Astika AyuningTyas, Astika Atha Rahmad Zulfikhar Dewi Soyusiawaty Dhimas Hidayat Dienulloh Ulil Abshar, Muhammad Dimara Kusuma Hakim Dimara Kusuma Hakim Esi Putri Silmina Fadlillah, Umi Fadlillah, Umi Fatah Yasin Fikamelyalla, Naura Gumawang, Aldino Kemal Adi Hartono, Susilo Ihsan Cahyo Utomo Iqbal Firdaus, Malvin Ira Candra Dewi Wulan, Puspa Irma Yuliana Joko Handoyo Khoirunnisa, Siska Lukito Edi Nugroho Mega Fatimah Rosana Muchlas Muchlas, Muchlas Muhammad Abdurrahman Hasan Muhammad Nashif, Haidar Naura Fikamelyalla Novelia Gunawan, Saomi Novilia Purwita Putri Nugroho, N Nurgiyatna Puspitasari, Yuliana Putri, Novilia Purwita Qanza, Aiza Fravy Ragil Ariyanto Rahmawati, Nila Dwi Ratnasari Nur Rohmah Rochmadi, Tri Rochmijatun, Siti Rully Medianto, Rully Safiq Rosad Sarmini Silmina, Esi Putri Siti Rochmijatun Sri Winiarti Sunardi Sunardi Sunardi Sunardi Syarifur Rizal Miftahul Hasan Ulva Erida Nur Rochmah Umi Fadlillah Wahyu Akbar Wahyusari, Retno Winiarti, Sri Wulandari, Novita Desi Yanti Haryanti Yuli Rahmawati Yusrifa, Khumaila Masfarina Yusuf Sulistyo Nugroho