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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Query : Jurnal Sistem Informasi JURIKOM (Jurnal Riset Komputer) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JATI (Jurnal Mahasiswa Teknik Informatika) INFOKUM Jurnal Tunas Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing JiTEKH (Jurnal Ilmiah Teknologi Harapan) JIKEM: Jurnal Ilmu Komputer, Ekonomi dan Manajemen Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) EXPLORER Prosiding Snastikom Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Prioritas : Jurnal Pengabdian Kepada Masyarakat Insight Power (Kekuatan Wawasan) - Jurnal Pengabdian Kepada Masyarakat Digital (JUPED) Jurnal Pengabdian Masyarakat Bangsa JUDIS : Jurnal Multidisiplin dan Sains
Siregar, Rosyidah
Universitas Harapan Medan
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Aplikasi Inverse Backpropagation Pada Penskalaan Citra Menggunakan Bilinear Interpolation Siregar, Rosyidah; Syahputri, Nenna Irsa; Harahap, Herlina
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 5 No. 1 (2023): Edisi April
Publisher : Universitas Harapan Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35447/jikstra.v5i1.756

Abstract

Bilinear interpolation is a method that is widely used in image scaling where bilinear interpolation can be applied to upscaling and downscaling processes. Several previous researches have shown that bilinear interpolation provides low quality reconstruction results compared to other scaling methods but is still a good alternative considering the lower process complexity compared to other scaling methods. For this reason, a mechanism or model is needed that can be juxtaposed with bilinear interpolation scaling so that the reconstruction results have better quality. Referring to previous research, neural networks can be used in the reconstruction process where artificial neural networks are used to learn features or information that is lost during the downscaling process so that it can be reused during the reconstruction or upscaling process. This research applies inverse backpropagation to help improve the quality of image reconstruction results on bilinear interpolation. The test results show a much better MSE value of up to 40.25% compared to reconstruction using ordinary bilinear interpolation. Meanwhile, the increase in PSNR obtained ranged from 0.4% - 9.7%.
Dari Data ke Informasi: Pengantar Sistem Informasi untuk Siswa Tommy, Tommy; Lubis, Ihsan; Lubis, Husni; Lubis, Imran; Syahputri, Nenna Irsa; Elhanafi, Andi Marwan; Siregar, Rosyidah; Khairani, Mufida; Riza, Ferdy
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 5 (2025): Juli
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i5.2675

Abstract

Pemahaman tentang sistem informasi merupakan kompetensi dasar yang penting bagi lulusan sekolah menengah kejuruan (SMK), khususnya pada bidang Teknik Komputer dan Jaringan (TKJ) serta Rekayasa Perangkat Lunak (RPL). Namun, materi mengenai sistem informasi secara konseptual dan aplikatif masih belum banyak dijumpai dalam kurikulum pembelajaran di tingkat SMK. Pengabdian kepada masyarakat ini bertujuan untuk mengenalkan konsep dasar sistem informasi kepada siswa SMK Nurul Amalia Tanjung Morawa melalui pendekatan edukatif dan interaktif. Kegiatan ini melibatkan beberapa tahap, mulai dari koordinasi dengan sekolah, penyusunan materi, pelaksanaan pelatihan, hingga evaluasi sederhana. Metode pembelajaran yang digunakan memadukan penyampaian teoritis, pemutaran video edukatif, diskusi kelompok, serta simulasi alur kerja sistem informasi yang relevan dengan lingkungan sekolah dan dunia kerja. Hasil kegiatan menunjukkan bahwa pelatihan ini mampu meningkatkan pemahaman siswa terhadap konsep dan penerapan sistem informasi, serta menumbuhkan minat mereka terhadap profesi di bidang teknologi informasi. Siswa juga menunjukkan antusiasme tinggi dalam sesi interaktif. Berdasarkan hasil ini, disarankan agar topik sistem informasi diperkenalkan secara lebih terstruktur dalam pembelajaran vokasional serta diikuti dengan kegiatan lanjutan yang mendorong pengembangan keterampilan aplikatif di bidang tersebut.
Adaptive Categorical Dictionary Implementation for Payload Reduction in AJAX Server-side DataTables Communication Siregar, Rosyidah; Lubis, Husni; Lubis, Ihsan
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 2 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i2.26015

Abstract

Efficient data transmission is a critical aspect of modern web applications, particularly in scenarios involving large tabular datasets rendered through server-side DataTables. This study proposes an adaptive categorical dictionary approach to reduce the payload size transmitted between the server and client. The strategy leverages the high frequency of categorical values within datasets by encoding them into shorter symbolic representations stored in a dynamically generated dictionary. The dictionary is constructed on the server during the initial request and maintained throughout the session, while the client retains a synchronized copy in memory. The research utilizes a publicly available college student dataset containing 1,545 records, focusing on columns with repetitive categorical values such as major, gender, and enrollment status. Experimental simulations were conducted under varying DataTables page lengths (10, 25, 50, and 100) to evaluate the impact of dictionary encoding on request and response payload sizes. Results demonstrate consistent payload reductions across all configurations, with significant improvements observed in larger page lengths—exceeding 12% in some cases. These findings confirm the effectiveness of the adaptive dictionary in minimizing response payloads, thereby improving communication efficiency in AJAX-based data-driven applications. The approach maintains compatibility with native PHP and JavaScript implementations and introduces minimal overhead, making it suitable for integration into existing server-side processing architectures.
Analisis Pengaruh Indeks Pembangunan Manusia dan Pertumbuhan Ekonomi terhadap Kemiskinan Winanda, Icha; Rahman, Sayuti; Siregar, Rosyidah
JIKEM: Jurnal Ilmu Komputer, Ekonomi dan Manajemen Vol 4 No 2 (2024): JIKEM: Jurnal Ilmu Komputer, Ekonomi dan Manajemen
Publisher : Universitas Muhammadiyah Enrekang

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

Abstract

Kecepatan kendaraan yang tinggi di jalan raya merupakan salah satu penyebab terjadinya kecelakaan lalu lintas dan sangat berpengaruh bagi keamanan pengendara lain dan demi terciptanya keselamatan terhadap pengendara lain, timbul gagasan untuk merancang sebuah sistem yang mampu mengukur dan memantau kecepatan kendaraan yang melewati jalan raya. Saat ini sedang ramai marak teknologi yang dikembangkan dengan tujuan dapat melakukan pendeteksian di jalan raya, teknologi tersebut diharuskan untuk dapat mengetahui kondisi dan situasi yang ada di sekelilingnya, karena di jalan raya melintas berbagai jenis kendaraan yang berbeda. Oleh karena itu dibuatlah program yang dapat mendeteksi kecepatan pada kendaraan yang melintas dijalan raya. Algoritma yangditerapkan pada penelitian ini adalah algoritma YOLO ( You Only Look Once) versi V3. Algoritma tersebut diterapkan karena mampu melakukan klasifikasi kendaraan secara efektif dan efisien. Algoritma tersebut diterapkan karena mampu melakukan klasifikasi kendaraan secara efektif dan efisien. Hasil dari penelitian ini adalah agar system dapat mendeteksi dan mengklasifikasikan kendaraan yang melintas di jalan raya dengan akurasi yang tinggi. Objek yang diklasifikasikan yaitu pada kendaraan mobil, bus, dan truk
Implementasi Color Quantization pada Kompresi Citra Digital dengan Menggunakan Model Clustering Berdasarkan Nilai Max Variance pada Ruang Warna RGB Tommy, Tommy; Siregar, Rosyidah; Elhanafi, Andi Marwan; Lubis, Imran
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 6: Desember 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021863490

Abstract

Kompresi citra dapat dilakukan dengan menggunakan color quantization di mana dengan mengurangi jumlah warna yang terdapat pada citra maka akan dapat mengurangi jumlah bit yang digunakan untuk merepresentasikan warna – warna tersebut. Semakin rendah jumlah warna yang dikurangi dalam rangka mencapai rasio kompresi yang optimal berdampak pada terdegradasinya kualitas dari citra. Secara umum color quantization menggunakan model clustering dalam proses pembentukan color palette yang akan digunakan sebagai referensi pada saat kuantisasi. Penelitian ini menggunakan model clustering berdasarkan nilai max variance pada channel RGB secara terpisah. Proses clustering dilakukan dengan membelah populasi cluster sebelumnya menggunakan nilai mean dari channel RGB yang memiliki nilai variance tertinggi. Color palette kemudian dibentuk menggunakan centroid hasil dari proses clustering. Percobaan pada beberapa citra uji dengan format 32bpp yang kemudian dikompresi menggunakan kuantisasi warna pada format 8bpp dan 4bpp memberikan kualitas dan rasio kompresi yang cukup baik yang diukur menggunakan ukuran MSE, PSNR dan CR di mana nilai MSE yang diperoleh berkisar 3.87 sampai 6.3 pada kuantisasi 8bpp dan 13.39 sampai 19.62 pada kuantisasi 4bpp. Sedangkan rasio kompresi yang diperoleh adalah sebesar 1.44 sampai 2.09 pada kuantisasi 8bpp dan 2.87 sampai 4.23 pada kuantisasi 4bpp. AbstractImage compression can be done by using color quantization where by reducing the number of colors contained in the image it can reduce the number of bits used to represent the colors. The lower the number of colors reduced in order to achieve the optimal compression ratio has an impact on the quality of the image. In general, color quantization uses clustering models in the process of constructing color palette that will be used as a reference during quantization. This study uses a clustering model based on the max variance value on the RGB channel separately. The clustering process is done by dividing the previous cluster population using the mean value of the RGB channel which has the highest variance value. The color palette is then formed using centroids resulting from the clustering process. Experiments on some test images in 32bpp format which are then compressed using color quantization in 8bpp and 4bpp formats provide a fairly good quality and compression ratio with MSE, PSNR and CR assessment where the MSE values obtained ranged from 3.87 to 6.3 at 8bpp quantization and 13.39 to 19.62 at 4bpp quantization. While the compression ratio obtained is 1.44 to 2.09 at 8bpp quantization and 2.87 to 4.23 at 4bpp quantization
Base-Delta Dynamic Block Length and Optimization on File Compression Tommy; Riza, Ferdy; Siregar, Rosyidah; Yeni, Manovri; Elhanafi, Andi Marwan; Nurmadi, Ruswan
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 1 (2023): Article Research Volume 5 Issue 1, January 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i1.1993

Abstract

Delta compression uses the previous block of bytes to be used as a reference in the compression process for the next blocks. This approach is increasingly ineffective due to the duplication of byte sequences in modern files. Another delta compression model uses the numerical difference approach of the sequence of bytes contained in a file. Storing the difference value will require fewer representation bits than the original value. Base + Delta is a compression model that uses delta which is obtained from the numerical differences in blocks of a fixed size. Developed with the aim of compressing memory blocks, this model uses fixed-sized blocks and does not have a special mechanism when applied to file compression in general. This study proposes a compression model by developing the concept of Base+Delta encoding which aims to be applicable to all file types. Modification and development carried out by adopting a dynamic block size using a sliding window and block header optimization on compressed and uncompressed blocks giving promising test results where almost all file formats tested can be compressed with a ratio that is not too large but consistent for all file formats where the ratio compression for all file formats obtained between 0.04 to 12.3. The developed compression model also produces compression failures in files with high uncompressed blocks where the overhead of additional uncompressed blocks of information causes files to become larger with a negative ratio obtained of -0.39 to -0.48 which is still relatively small and acceptable.
Low-Resolution Face Image Reconstruction Using Multi-Stage FSRCNN to Improve Face Detection and Tracking Accuracy in CCTV Surveillance Tommy, -; Siregar, Rosyidah; Rahman Syahputra, Edy
JOIV : International Journal on Informatics Visualization Vol 9, No 3 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.3.3160

Abstract

Face detection and tracking under real-world condition remain challenging under different illumination, crowded scenes, partial occlusions and small or low-resolution face images. In traditional face tracking schemes, these factors often cause the false positive rate to be high and the accuracy to be low. Specifically, little or no detailed information is presented for small or distant faces, here the reliability of detection is diminished and non-face-object can provoke false alarms thus degrading the performance of a system in general. Such problems are not unclear and need a sophisticated solution to improve the resolution and detection performance in various scenarios. In this paper, a new face tracking system based on a cascade classifier, a two-step model of Fast Super-Resolution Convolutional Neural Network (FSRCNN) and DLib face validator is presented. The low-resolution facial parts are first enhanced by the FSRCNN to optimize the detection by the cascade classifier. The DLib face validator improves the approach by validating the discovered faces, and reducing false positives. The system was tested over a CCTV scenario video corpus of several challenging conditions represented by crowded environments, dynamic object and human faces of different sizes and locations. The performance analysis focused on performance metrics such as precision, recall, and false positive rate, which provided a comprehensive overview of the system's robustness. The results demonstrate a significant improvement in face detection accuracy, as high as 98% precision and very few false positive detections. The synergy between the FSRCNN method and the DLib validation was especially effective on small and far-away faces, which are normally difficult to perceive. Whilst their improvements on memory consumption were small, they proved effective for face detection in challenging conditions. The ability of the system to maintain high measurement accuracy while avoiding errors makes it well suited for use in surveillance, security and monitoring systems. In conclusion, this research highlights the effectiveness of combining super-resolution techniques with traditional face detection methods to address the limitations of existing systems. The future work will focus on increasing recall rate and constantly maturing the extraction system to work well in various realistic conditions, thus making it effective and general for different applications.
ANALISIS KRIPROGRAFI DALAM PENGAMANAN DATA PENERIMAAN DANA BANTUAN PADA KECAMATAN PAMATANG SILIMAHUTA DENGAN ALGORITMA RC4 Jawak, Otniel Efrata; Siregar, Rosyidah; Rismayanti, Rismayanti
JUDIS : Jurnal Multidisiplin dan Sains Vol 2, No 1 (2025): September
Publisher : Compart Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63854/jms.v2i1.60

Abstract

Penelitian ini menganalisis penggunaan algoritma kriptografi RC4 dalam pengamanan data penerimaan dana bantuan di Kecamatan Pamatang Silimahuta. Dengan meningkatnya ancaman keamanan digital, penting bagi institusi pemerintah untuk menerapkan teknologi enkripsi untuk melindungi informasi sensitif. Studi ini memfokuskan pada implementasi algoritma RC4, yang dikenal karena kecepatannya dalam mengenkripsi dan mendekripsi data, serta kemampuannya dalam mengatasi berbagai jenis serangan kriptografi. Metode penelitian yang digunakan adalah studi kasus, di mana data penerimaan dana bantuan dianalisis sebelum dan setelah diterapkan algoritma RC4. Hasil penelitian menunjukkan bahwa RC4 mampu memberikan tingkat keamanan yang signifikan terhadap data penerimaan dana bantuan, walaupun terdapat beberapa kelemahan yang perlu diperhatikan, seperti kerentanannya terhadap serangan kunci panjang. Kesimpulan dari penelitian ini adalah bahwa algoritma RC4 dapat digunakan sebagai solusi efektif untuk pengamanan data di sektor pemerintahan, khususnya dalam konteks penerimaan dana bantuan. Namun demikian, disarankan untuk dilakukan pengawasan dan pembaruan rutin terhadap sistem keamanan untuk menjaga integritas dan kerahasiaan data.
Co-Authors Ainun Naimah Pulungan Amir Mahmud Husein, Mawaddah Harahap, Amir An-nissa, Shahira Andi Marwan Elhanafi Andi Marwan Elhanafi Andi Marwan Elhanafi, Andi Marwan AULIA, RAHMAT Damayanti, Fera Edy Rahman Syahputra, Edy Rahman Fera Damayanti Ferdy Riza Gultom, Fransko Harahap, Herlina Herlina Andriani Simamora Herlina Harahap Ilham, Fauzi Imran Lubis IRWAN, DEDY Jawak, Otniel Efrata Khairani, Mufida Kharunnisa Kharunnisa Liza Novietta Lubis, Husni lubis, husni lubis, ihsan M F Verri Anggriawan Manovri Yeni Mawaddah Harahap Muhammad Zen Nenna Irsa Syahputri Rahman Syahputra, Edy Rahman, Sayuti Rismayanti Rismayanti Ruswan Nurmadi Sembiring, Arnes Siregar, Riska Novasari Siti Sundari Syahputri, Nenna Irsa Tommy Tommy Tommy Tommy Tommy Tommy, - Tommy, Tommy Winanda, Icha Yessi Fitri Annisah Lubis Yusmai, Yusmaifany