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All Journal Majalah Forum Teknik UGM Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) SPEKTRUM INDUSTRI Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Teknofisika Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Martabe : Jurnal Pengabdian Kepada Masyarakat Journal of Information Systems and Informatics Buletin Ilmiah Sarjana Teknik Elektro Jurnal Computer Science and Information Technology (CoSciTech) Emerging Information Science and Technology Jurnal Informatika Polinema (JIP)
Kartika Firdausy
Program Studi Teknik Elektro Fakultas Teknologi Industri Universitas Ahmad Dahlan
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Physics Social Sciences

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PERANCANGAN DAN IMPLEMENTASI PAPERLESS OFFICE BERBASIS WORDPRESS DI ITTC UAD Kartika Firdausy; Muhammad Artha
Spektrum Industri Vol. 10 No. 1: April 2012
Publisher : Universitas Ahmad Dahlan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v10i1.1623

Abstract

Perlu dilakukan satu upaya untuk mengurangi limbah kertas yang dihasilkan oleh perkantoran. Era kemajuan teknologi informasi dan komunikasi memiliki peluang dikembangkannya komunikasi secara online melalui jaringan komputer, sehingga dapat mengurangi penggunaan kertas untuk surat menyurat dan pembuatan dokumen. Untuk keperluan administrasi perkantoran dapat dilakukan dengan cara menerapkan paperless office system. Tujuan penelitian ini adalah merancang suatu sistem paperless office berbasis WordPress yang dapat diterapkan dalam lingkup perkantoran, khususnya di ITTC UAD. Penelitian ini mengambil subjek tentang sistem pengelolaan dokumen elektronik berbasis WordPress yang menyediakan sarana pengelolaan dokumen dalam format digital, sehingga diharapkan dapat mengurangi pemakaian kertas. Beberapa plug in ditambahkan seperti themes, bookmark, dan pengamanan pada situs, yaitu: Post Protect Quiet, dan Password Protect WordPress Blog. Selain admin, ada beberapa level user yang memiliki wewenang yang berbeda-beda pada sistem ini, yaitu: author, editor, dan contributor. Dokumen digital yang dikelola dalam sistem ini adalah surat-menyurat, informasi pelatihan, tutorial, dan Surat Keputusan (SK), yang dapat didistribusikan melalui media e-mail maupun jejaring sosial. Sistem diuji untuk setiap level user. Hasil pengujian menunjukkan bahwa semua fitur/menu pada sistem dapat berjalan dengan baik. Hasil rata-rata persentase dari pengujian diperoleh responden yang menyatakan sangat setuju = 26,5%, setuju = 71%, kurang setuju = 2,5%, dan tidak setuju = 0%. Kata kunci : paperless office system, administrasi perkantoran, WordPress.
Perbandingan Unjuk Kerja Library Optical Character Recognition (OCR) dalam Pengenalan Teks pada Dokumen Digital Darpito, Muhammad Noko; Kartika Firdausy; Abdul Fadlil
Jurnal Informatika Polinema Vol. 11 No. 3 (2025): Vol. 11 No. 3 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v11i3.7025

Abstract

Optical Character Recognition (OCR) merupakan teknologi yang digunakan untuk mengubah teks dalam dokumen digital menjadi teks yang dapat dikenali oleh mesin. Pemilihan metode OCR yang tepat sangat bergantung pada efisiensi pemrosesan dan akurasi pengenalan teks, terutama dalam penerapan yang membutuhkan kecepatan tinggi dan tingkat kesalahan minimal. Dalam penelitian ini, dilakukan perbandingan performa antara Tesseract dan EasyOCR melalui metode penelitian yang mencakup tahapan pengumpulan data, ekstraksi teks, implementasi OCR menggunakan kedua library tersebut, dan evaluasi hasil ekstraksi teks kedua library OCR tersebut menggunakan Word Error Rate (WER), Character Error Rate (CER) dan akurasi ekstraksi OCR keseluruhan. Dataset yang digunakan yang terdiri dari 50 dokumen formulir dengan variasi tata letak dan ukuran font, serta 10 dokumen artikel dengan variasi format huruf (standar dan kapital). Hasil penelitian menunjukkan bahwa Tesseract secara konsisten lebih cepat dalam memproses dokumen, dengan waktu rata-rata 0,34 detik per dokumen formulir dibandingkan EasyOCR yang memerlukan 1,81 detik. Namun, EasyOCR memperlihatkan performa yang lebih baik dalam akurasi pengenalan teks, dengan nilai WER rata-rata yang lebih rendah sebesar 25,78% dibandingkan Tesseract sebesar 49,69% pada dokumen formulir. Dengan demikian, Tesseract lebih sesuai untuk pemrosesan cepat dalam jumlah besar, sedangkan EasyOCR lebih direkomendasikan untuk dokumen dengan kompleksitas tinggi yang membutuhkan akurasi lebih baik.
Peningkatan Kualitas Citra Hilal Berdasarkan Kontras Menggunakan Metode Histogram Equalization, AHE, dan CLAHE Suprayitno, Ady; Murinto; Kartika Firdausy
Computer Science and Information Technology Vol 6 No 3 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i3.10376

Abstract

The determination of the beginning of the Hijri month is often aided by digital imaging technology, but the quality of the crescent images produced often faces the challenge of very low contrast. The faint light of the crescent is difficult to distinguish from the still bright background of the evening sky, exacerbated by atmospheric conditions and camera sensor noise that reduce visual quality. To improve the image, many still perform manual contrast enhancement. On the other hand, the selection of contrast enhancement methods is often without a measurable basis. This study aims to conduct a comparative performance evaluation between three contrast enhancement methods: Histogram Equalization (HE), Adaptive Histogram Equalization (AHE), and Contrast Limited Adaptive Histogram Equalization (CLAHE). The goal is to identify the most suitable technique for improving the quality of crescent images, the specific application of which has not been widely explored. A total of 30 crescent images were tested through a quantitative evaluation approach using the Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) metrics. The results show that CLAHE provides the best performance with the lowest average MSE (89.97) and the highest PSNR (30.92 dB), demonstrating the best ability to balance contrast enhancement and distortion reduction. In contrast, the HE and AHE methods produce high MSE and low PSNR values, indicating significant visual distortion. Thus, CLAHE is recommended as the most reliable method for improving the quality of crescent images based on contrast in digital technology-based observation systems. For further research, it is recommended to explore the automatic determination of CLAHE parameters and the use of additional evaluation metrics such as SSIM (Structural Similarity Index Measure).
IMPLEMENTASI TEKNIK ELEKTRO DALAM SMART ENERGY DAN SAFETY DI KEHIDUPAN SEKOLAH Yudhasakti, Imam; Anas, Syafrial; Widodo, Sugeng; Ali Akbar, Son; Ardiansyah, Ardiansyah; Firdausy, Kartika
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 9, No 3 (2026): MARTABE : JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v9i3.%p

Abstract

Kegiatan pengabdian masyarakat ini bertujuan meningkatkan pemahaman siswa tentang konsep smart energy dan keselamatan kelistrikan (safety), serta menumbuhkan minat terhadap teknologi melalui demonstrasi sistem otomasi sederhana. Kegiatan dilaksanakan di SMP Negeri 2 Purbalingga dengan total 240 peserta yang dibagi dalam dua sesi. Metode pelaksanaan meliputi presentasi interaktif mengenai pengelolaan energi berbasis data (monitoring, analisis pola konsumsi, pengendalian beban, dan efisiensi), materi safety, serta demonstrasi prototipe palang parkir otomatis berbasis Arduino. Prototipe menggunakan sensor RFID untuk membaca kartu akses dan membuka palang, sensor ultrasonik untuk mendeteksi kendaraan/objek melintas sebagai pemicu penutupan, serta motor servo sebagai aktuator. Evaluasi dilakukan menggunakan kuesioner retrospective posttest skala 1–4 pada sampel 60 siswa kelas sembilan, sehari setelah kegiatan. Hasil menunjukkan peningkatan pemahaman pada tiga aspek berpasangan: smart energy (? +0,81), safety (? +0,45), dan pemahaman demo palang parkir otomatis (? +0,40). Dokumentasi dan observasi juga menunjukkan keterlibatan siswa meningkat pada sesi demonstrasi dan tanya jawab. Kegiatan ini berkontribusi pada pengembangan pembelajaran kontekstual di sekolah melalui integrasi teori–praktik dan penguatan pendekatan STEM yang dapat direplikasi untuk meningkatkan literasi energi dan teknologi
Multi-Seed Robustness Benchmark of Lightweight YOLO Models for Young Crescent Moon Detection under Limited-Data Conditions Bayu Krisna Murti; Kartika Firdausy; Murinto
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1653

Abstract

Visual observation of the young crescent moon is challenging due to its thin and low-contrast appearance. Although YOLO-based object detectors are promising for image-based crescent localization, newer architectures do not automatically generalize well to small grayscale datasets, and prior studies rarely report robustness across repeated training runs. This study benchmarks YOLOv8n, YOLO11n, and YOLO26n for young crescent moon detection under limited-data conditions. A grayscale dataset of 697 images was resized to 640 × 640 pixels, annotated with the single class crescent_moon, and split into training, validation, and test subsets at a fixed 70:20:10 ratio. The three models were trained using the same configuration across five random seeds. Validation results were used to analyze multi-seed robustness, while the fixed 71-image test set was used for CPU-only inference evaluation. YOLO26n achieved the highest validation mAP@50-95 and fitness with the lowest variability, and also achieved the lowest CPU pipeline latency and highest throughput on the test set. These findings show that YOLO26n offers the best trade-off between accuracy and efficiency across the evaluated dataset and CPU-only inference setting. The reported throughput reflects low-frame-rate image-based inference, not real-time video performance. This study provides a reproducible benchmark protocol that combines fixed data splitting, grayscale preprocessing, data integrity checking, multi-seed robustness analysis, and CPU inference profiling.
Fuzzy Logic-Based Classification of Crescent Moon Images Using Contrast and Thickness Yudhiakto Pramudya; Kartika Firdausy; Adi Jufriansah; Okimustava Okimustava; Itsnaini Irvina Khoirunnisa; Bayu Krisna Murti; Rihmah Alifah Hidayah; Murinto Murinto; Muhammad Maulidan
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 2 (2026): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i2.14964

Abstract

Accurate determination of the crescent moon (hilal) is crucial for establishing the start of lunar months in the Islamic calendar; however, observations are frequently hindered by daylight conditions, atmospheric disturbances, and subjective visual interpretation. This research proposes a fuzzy logic-based classification system to evaluate crescent moon images using contrast and arc thickness as input parameters, providing a transparent, rule-based alternative to black-box machine learning models for hilal visibility assessment. Images were collected on four distinct observation dates (May 28, 2025, August 5, 2024, September 16, 2023, and May 9, 2021) under varying atmospheric conditions and crescent appearances. Each image underwent pre-processing to extract quantitative measures of arc contrast and thickness, which were subsequently fuzzified using triangular and trapezoidal membership functions. A fuzzy inference system employing expert-defined rules was then used to compute a visibility score for each observation. The resulting visibility scores of 0.4691, 0.4604, 0.4689, and 0.4154, respectively, placed all four observations within the “partially visible” category. These findings demonstrate the system's capability to manage observational ambiguity in daylight conditions, showing potential for reliable classification while still requiring validation on larger datasets and clear non-visibility cases, and offering a transparent and interpretable framework to support more consistent and standardized hilal classification for calendrical purposes.
Comparative Evaluation of Thresholding Methods for Optimized Digital Document Parsing Accuracy Muhammad Noko Darpito; Kartika Firdausy; Abdul Fadlil
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 2 (2026): April 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i2.6982

Abstract

Automated parsing of semi-structured documents has become increasingly important, particularly in standardized formats like SATS-LN, which contain fixed-layout fields such as permit number, addresses, validity period, and item types. This study investigates the impact of two thresholding methods Otsu and Sauvola on object detection accuracy using Faster R-CNN with Detectron2. A dataset of 200 SATS-LN documents, captured via scanner and camera, was augmented into 3,600 images and labeled for seven key fields. Image quality was evaluated using PSNR, SSIM, and MSE, while detection performance was measured through mAP, AP50, AP75, AR@100, precision, recall, and F1-score. Results showed that Sauvola preserved structural layout more effectively (SSIM: 0.76 for scanner, 0.47 for camera), although Otsu achieved higher PSNR on scanned images. Sauvola attained the highest macro and weighted F1-score (0.998), with near-perfect label detection and consistent performance across augmentations. Overall, Sauvola is more reliable for enhancing segmentation and detection in layout-based document processing.
Deteksi Objek Sampah Organik dan Non-Organik Menggunakan YOLO26n Silviana, Yorissa; Murinto; Firdausy, Kartika
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol. 12 No. 2 (2026): Volume 12 No 2
Publisher : Program Studi Informatika

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

Abstract

Pemilahan sampah secara manual membutuhkan waktu yang lama dan tingkat konsistensi pengamatan yang tinggi, terutama ketika objek memiliki bentuk, warna, dan tekstur yang beragam. Penelitian ini bertujuan untuk mengevaluasi kinerja YOLO26n dalam mendeteksi dan melokalisasi sampah organik dan non-organik. Dataset yang digunakan terdiri atas 2.000 citra dengan distribusi seimbang, yaitu masing-masing 1.000 citra organik dan non-organik yang diperoleh dari pengumpulan mandiri dan dataset publik. Data dianotasi menggunakan bounding box dan dibagi menjadi data pelatihan, validasi, dan pengujian dengan rasio 80:10:10. Model dilatih selama 100 epoch menggunakan citra berukuran 640 × 640 piksel dengan batch size 32. Hasil evaluasi menunjukkan nilai precision sebesar 0,9292, recall sebesar 0,8488, F1-score sebesar 0,8870, mAP@0.5 sebesar 0,8967, dan mAP@0.5:0.95 sebesar 0,8034. Kelas non-organik memperoleh performa lebih tinggi dengan mAP@0.5 sebesar 0,928 dan mAP@0.5:0.95 sebesar 0,894, dibandingkan kelas organik yang masing-masing sebesar 0,865 dan 0,713. Perbedaan tersebut menunjukkan bahwa variasi bentuk, tekstur, dan batas visual objek organik masih menjadi tantangan dalam proses deteksi dan lokalisasi. Model juga mencatat waktu inferensi sebesar 0,7 ms per citra pada GPU NVIDIA RTX PRO 6000. Secara keseluruhan, YOLO26n mampu mendeteksi dan melokalisasi sampah organik dan non-organik dengan kinerja yang baik, namun masih memerlukan pengujian lebih lanjut pada data independen dan perangkat edge sebelum diterapkan pada sistem pemilahan sampah secara real-time.
Audio Noise Reduction Using a U-Net Convolutional Neural Network Architecture Ikhwal, Ikhwal; Pranolo, Andri; Firdausy, Kartika
Emerging Information Science and Technology Vol. 7 No. 1 (2026): May
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v7i1.33075

Abstract

Audio quality can be degraded by noise contamination, while conventional noise reduction methods such as the Wiener Filter may have limitations in preserving audio spectral characteristics. This study develops an audio noise reduction system using a U-Net Convolutional Neural Network (CNN) based on Short-Time Fourier Transform (STFT) spectrograms to reduce white noise. The dataset consisted of seven accompaniment audio files from the Indonesian Robot Dance Art Contest (KRSTI), with five used for training and two for testing. Clean audio was contaminated with white noise at SNR levels of 0, 5, 10, and 15 dB and transformed into STFT spectrograms, while phase information was retained for reconstruction. The U-Net was trained to learn the mapping between noisy and clean spectrograms and compared with the Wiener Filter as a conventional baseline using SNR, MSE, MAE, LSD, and SI-SDR. The results show that U-Net achieves lower average MSE (0.002453), MAE (0.032514), and LSD (9.663 dB), while the Wiener Filter achieves higher average ΔSNR (3.327 dB) and SI-SDR (12.251 dB) than U-Net, which achieves 1.915 dB and 10.073 dB, respectively. These findings indicate that the two methods exhibit different strengths depending on the evaluation metric. Further research should investigate larger and more diverse datasets, particularly real-world noise conditions, to improve model robustness and generalization.
Co-Authors Abdul Fadlil Abdul Fadlil Adi Jufriansah Ali Akbar, Son Anas, Syafrial Andri Pranolo Anton Yudhana ARDIANSYAH ARDIANSYAH Artha, Muhammad Bayu Krisna Murti Cahya Utama Purwa Negara Cahya Utama Purwa Negara Darpito, Muhammad Noko Daryono Daryono Eka Rahmat B Eko Prasetyo Fathoni, Listya Febri Fauzi Hermawan Fiandono, Ibnu Hanung Adi Nugroho Ibnu Fiandono Ikhsan Sugianto Ikhwal, Ikhwal Ikhwan Hawariyanta Itsnaini Irvina Khoirunnisa Khaironi Dwi Septiaji Listya Febri Fathoni Lutfatul Kholifah M. Hana Mirza Kholis M. Riza Ferdiansyah M. Taufik Setiawan Muchlas, Muchlas Muhammad Artha Muhammad Bayu Sasongko Muhammad Maulidan Muhammad Noko Darpito Murinto Murinto Murinto Mushlihudin Mushlihudin Mushlihudin, Mushlihudin Nuryono Satya Widodo Okimustava Okimustava Oyas Wahyunggoro P. Eko Prasetyo Rahmansyah Rahmansyah Regi Regi Regi Regi Rihmah Alifah Hidayah Robi Edwarsyah Samadri Samadri Sefindra Purnama Selamat Riyadi Septiaji, Khaironi Dwi Silviana, Yorissa Sugeng Widodo sunardi sunardi Suprayitno, Ady Tofik Nurochman Tole Sutikno Yudhasakti, Imam Yudhiakto Pramudya Yusron Saudi