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All Journal Jurnal Ilmiah Informatika Komputer Jurnal Ilmu Komunikasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding of the Electrical Engineering Computer Science and Informatics Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer JURNAL MEDIA INFORMATIKA BUDIDARMA SENTIA 2016 Astonjadro Jurnal Telematika Building of Informatics, Technology and Science bit-Tech Systematics Respati SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Algoritma, Logika dan Komputasi Abditeknika - Jurnal Pengabdian Kepada Masyarakat Decode: Jurnal Pendidikan Teknologi Informasi Kresna: Jurnal Riset dan Pengabdian Masyarakat Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Jurnal Algoritma Jurnal Ticom: Technology of Information and Communication Eduvest - Journal of Universal Studies Telematika MKOM AMMA : Jurnal Pengabdian Masyarakat Artinara Jurnal Ticom: Technology of Information and Communication IPSIKOM Jurnal Pengabdian Masyarakat Tekno
Hardjianto, Mardi
Budi Luhur University
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Peningkatan Kualitas Guru dengan Pelatihan Google Classroom sebagai Media Alternatif School From Home pada SMK Puspita Persada Jakarta Selatan Pudoli, Ahmad; Hardjianto, Mardi; Setiono, Devit
Abditeknika Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2021): April 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/abditeknika.v1i1.235

Abstract

The COVID-19 pandemic in early 2020 is causing major changes in community activities today. Starting from trade, economy, jobs as well as in the world of education. Schools must participate in preventing the spread of the COVID-19 virus by changing teaching patterns in accordance with the instructions of the Ministry of Education and Culture of the Republic of Indonesia, where teaching and learning activities are carried out from home. Puspita Persada Vocational High School participated in the success of the government program by changing the teaching pattern from home. However, because this instruction was given quickly, SMK Puspita persada has not prepared technically thoroughly in teaching and learning. Currently the teaching method is done using WhatsApp Group and email. Of course, this method still needs to be developed so that the delivery of teaching materials is more perfect. The purpose of this activity is to provide training using Google's facility, Google ClassRoom, to improve the ability of teachers to deliver and deliver materials to the maximum and based on better technology. The method that will be done in this activity is face-to-face training (if possible) but still apply physical distancing in the presentation of the material. This method will be adjusted at the time of implementation in accordance with existing conditions. Based on Abdimas activities, it can be concluded that google classroom training provides tremendous benefits for teachers. Teachers are very enthusiastic and interested in using google classroom, teachers know applications that can be used as a learning medium, teachers can be easier to manage classes, save time, and give examples to students to maintain the environment by reducing paper use.
Implementasi Tanda Tangan Digital Menggunakan Algoritme RSA dan SHA-512 Berbasis Web Agnes Aryasanti; Mardi Hardjianto; Goenawan Brotosaputro; Ririt Roeswidiah
Jurnal Ticom: Technology of Information and Communication Vol 10 No 3 (2022): Jurnal Ticom-Mei 2022
Publisher : Asosiasi Pendidikan Tinggi Informatika dan Komputer Provinsi DKI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70309/ticom.v10i3.36

Abstract

Dokumen adalah surat tercetak atau tertulis yang digunakan sebagai alat bukti. Seiring dengan perkembangan teknologi, saat ini dokumen juga diterbitkan dalam bentuk digital tidak hanya dalam bentuk fisik atau cetak. Dokumen digital memiliki fungsi yang sama dengan dokumen fisik, namun memiliki kelemahan yaitu sangat rentan terhadap kemungkinan dimodifikasi, dipindahtangankan oleh siapapun dan sulitnya pembuktikan keaslian dokumen. Salah satu cara untuk mencegahnya adalah dengan membuat tanda khusus untuk memastikan bahwa dokumen tersebut asli. Tanda khusus ini adalah tanda tangan digital. Penelitian ini menggunakan fungsi hash SHA-512 yang diulang sebanyak sepuluh kali dan disertai dengan salt agar tidak mudah untuk dimodifikasi oleh orang lain. Enkripsi kunci publik yang digunakan adalah algoritme RSA.  Hasil pengujian menunjukkan bahwa sistem tanda tangan digital menggunakan algoritme RSA dan SHA-512 dengan salt lebih dapat mengamankan dokumen penting dari perubahan oleh orang yang tidak bertanggung jawab. Jangka waktu pembuatan tanda tangan digital tidak terlalu lama. Ukuran file sebesar 5 megabyte hanya membutuhkan waktu sekitar 0,07 detik.
Pemodelan Mempercepat dan Meningkatkan Efisiensi Performa Kriptografi Menggunakan Metode RSA Power Eksponen - CRT - VMPC Putri, Aprilianti; Desmon Manalu, Perdinan; Hardjianto, Mardi
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2748

Abstract

Pesatnya perkembangan teknologi informasi meningkatkan risiko kebocoran data, sehingga diperlukan metode untuk menjaga kerahasiaan informasi. Kriptografi menyediakan mekanisme enkripsi dan deskripsi, salah satunya melalui algoritma RSA atau Rivest – Shamir - Adleman yang dikenal memiliki tingkat keamanan tinggi. Permasalahan efisiensi pada algoritma RSA telah menjadi topik penelitian selama lebih dari dua dekade. Berbagai studi dilakukan baik untuk menganalisis kelemahannya maupun mengoptimalkan kinerjanya. Tingkat keamanan RSA sendiri bertumpu pada kompleksitas faktorisasi bilangan komposit berukuran besar menjadi faktor prima, yang hingga kini masih sulit untuk dipecahkan secara efektif. Eksponen merupakan operasi perkalian suatu bilangan dengan dirinya sendiri secara berulang, untuk membagi perhitungan agar mengurangi running time dalam mengolah data eksponen dapat menggunakan power eksponen yang dioptimalkan dengan metode khusus fast eksponen. Dalam implementasinya, algoritma kriptografi RSA diimplementasikan dalam bentuk program yang dapat menjalankan proses enkripsi dan deskripsi teks. Karena algoritma RSA berbasis pada operasi modulo bilangan bulat, solusi yang ditawarkan untuk mengatasi permasalahan efisiensi adalah penerapan metode RSA yang dilakukan Power Eksponen, Chinese Remainder Theorem (CRT), Variably Modified Permutation Composition (VMPC). Tujuan ini yaitu untuk mempercepat proses waktu eksekusi deskripsi. Hasil dari penelitian ini, waktu eksekusi enkripsi menggunakan RSA lebih cepat dan waktu eksekusi deskripsi menggunakan RSA power eksponen -CRT- VMPC lebih cepat.
Pelatihan Komputer Untuk Santri Pondok Pesantren Tahfidzul Qur’an Wahidin Halim Mardi Hardjianto; Lis Suryadi; Dolly Virgian Shaka Yudha Sakti; Gandung Triyono
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 1 : Februari (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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

Abstract

This Community Service activity was carried out in collaboration with the Wahidin Halim Tahfidzul Qur'an Islamic Boarding School, an Islamic boarding school located on Jl. H. Gillan RT. 003/RW. 001, Pinang District. Pinang, Tangerang City, Banten 15145. Currently, our partners are struggling to overcome problems arising from the lack of computer training for students. To overcome this problem, we held face-to-face computer training sessions at the ICT Laboratory of Budi Luhur University. The survey evaluation showed that more than 85% of participants felt that the activity was useful, easy to understand, effective, and met their expectations. Therefore, it can be concluded that this activity provides the right solution to partner problems.
Analisis dan Evaluasi Search Engine yang Aman untuk Penggunaan Anak Usia Dini di Lingkungan Sekolah Dasar: Perspektif Rekayasa Komputasi Terapan dalam Meningkatkan Keamanan Online Rosi Ulibasa; Citra Fertia Anggraini; Mardi Hardjianto
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3250

Abstract

The use of search engines as a learning resource in elementary schools increases the risk of exposure to inappropriate content, necessitating a fast and accurate filtering mechanism from the very beginning of the search. This study aims to design and evaluate a Bloom filter-based pre-query filtering system to detect risky keywords as early as the first 1–2 characters of the input. The evaluation was conducted using a query dataset representing the search patterns of elementary school students in grades 1–5 with variations in Bloom filter size (1024, 2048, 4096 bits) and the number of hash functions (7, 10, 15). Experimental results show that the 1024-bit configuration with 7 hash functions yields an average filtering time of 15 ms, a false positive rate (FPR) of 1%, and a false negative rate (FNR) of 0%, thereby meeting real-time response requirements. The 2048–4096-bit configurations reduce the FPR to 0% but increase latency to 18–25 ms. These findings demonstrate a measurable trade-off between latency and filtering accuracy. This study empirically contributes to showing that Bloom filters are effective as a low-latency initial filtering mechanism. The proposed system has the potential to serve as the foundation for developing safer and more responsive educational search engines for elementary school students
Model Rekomendasi Mata Pelajaran Pemintaan Siswa dengan Multi-Label Classification Hibatul Azizi; Wahyu Widadi; Mardi Hardjianto
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3337

Abstract

Pemilihan mata pelajaran pemintaan di Sekolah Menengah Atas merupakan proses penting yang mempengaruhi perkembangan akademik dan karier siswa, namun masih sering dilakukan secara subjektif. Penelitian ini mengusulkan sistem prediksi pemintaan berbasis Data Mining menggunakan pendekatan multi-label classification, sehingga siswa dapat direkomendasikan lebih dari satu pemintaan yang sesuai. Dua algoritma yang dibandingkan adalah C4.5 dan K-Nearest Neighbor (K-NN) dengan memanfaatkan data nilai rapor, hasil tes IQ, gaya belajar, dan tipe kepribadian siswa kelas X SMAN 95 Jakarta. Hasil pengujian menunjukkan bahwa K-Nearest Neighbor (K-NN)  menghasilkan akurasi lebih tinggi sebesar 95%, sedangkan C4.5 memiliki performa yang kompetitif serta keunggulan dalam interpretabilitas melalui model pohon keputusan. Secara komparatif, K-NN lebih unggul dalam aspek prediksi, sementara C4.5 lebih mendukung pengambilan keputusan yang mudah dipahami. Sistem kemudian diimplementasikan dalam bentuk aplikasi web untuk membantu guru Bimbingan Konseling dalam memberikan rekomendasi pemintaan yang lebih objektif dan fleksibel. Temuan ini menunjukkan bahwa pendekatan multi-label classification efektif dalam merepresentasikan kompleksitas preferensi siswa
Recommendation of Vocational Major Recommendation Using Artificial Neural Networks with ADAM Optimization Fawwaz Dzakwan; Muhammad Hikmat Fathur Rahman; Mardi Hardjianto
Building of Informatics, Technology and Science (BITS) Vol 8 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v8i1.7472

Abstract

This study proposes an Artificial Neural Network (ANN)-based recommendation framework for vocational major selection using student academic-feature profiles and ADAM optimization. The dataset consisted of 9,984 student records from West Java, derived from the school proposal recapitulation linked to DAPODIK. The predictive task was formulated as a six-class classification problem covering major categories in vocational education. Data preprocessing included data checking, target encoding, feature standardization, and train-test splitting. The ANN model used two hidden layers with ReLU activation and a softmax output layer, and was trained for 50 epochs using the ADAM optimizer. To enhance practical usability, predicted class probabilities were combined with major-specific qualification thresholds to enable the system to produce both primary and alternative recommendations. Experimental results showed that the model achieved 82% accuracy, an average precision of 0.88, a recall of 0.82, and an AUC of 0.8748, indicating useful discriminative performance for vocational major recommendation. The study provides a clearer distinction among the recommendation basis, predictive model, and operational qualification screening in educational decision support. However, the system still relies mainly on academic features and has not yet been benchmarked against alternative classifiers. Future work should incorporate interest and aptitude variables, class-wise error analysis, and comparative baseline evaluation.
Implementation of Selection of Employee Candidates By Utilizing Social Media Using Linear Regression Algorithms and Topsis Methods: A Case Study of A Boarding School Robby Ilhamkusuma; Irwan Robi Prastomo; Mardi Hardjianto
Eduvest - Journal of Universal Studies Vol. 4 No. 8 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i8.1790

Abstract

Efficiency in the selection of prospective employees can have a significant impact on increasing costs and extending the time required in the recruitment process of HR Information Systems in boarding schools.  However, the hiring process is often still done manually and traditionally, resulting in high costs and time and lack of efficiency. Social media has become an important part of modern society, including in the employee recruitment and selection process. Social media can be used to obtain more comprehensive information about prospective employees, such as educational background, skills, work experience, and personality. This research investigates using Linear Regression Algorithm on social media classification and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method as ranking criteria in classifying prospective employees. One of the proposed solutions is to utilize information from social media to evaluate the potential and personality of prospective employees. This research specifically reviews the application of Linear Regression Algorithm and TOPSIS method in categorizing prospective employees based on information obtained from social media, focusing on HR Information System in a particular boarding school. The results showed that the application of social media classification system with linear regression algorithm with Mean absolute error 10.50, Residual sum of squares (MSE): 147.16, R-squared: 1.0 and TOPSIS method with an accuracy rate of 0.51238 for the first rank can improve the efficiency of the recruitment process
Pemberdayaan Kreativitas Remaja Petukangan Utara Dalam Pembuatan Visual Konten Sosial Media Menggunakan Canva Ahmad Pudoli; Irawan Irawan; Mardi Hardjianto; Purwanto Purwanto; Jan Everhard; Mohammad Syafrullah
Artinara Vol 5 No 2 (2026): Jurnal Artinara Juni 2026 (in press)
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/artinara.v5i2.448

Abstract

The rapid development of social media has significantly changed adolescents’ communication patterns and daily activities, yet it has not been fully matched by their ability to produce creative and useful visual content. Youth in Petukangan Utara are active social media users but mainly act as content consumers rather than creators. Based on this condition, this community service program aims to enhance youth creativity and digital skills through training in social media visual content creation using Canva. The method applied a participatory approach with a learning-by-doing model, including basic training, hands-on practice, mentoring, and group-based content production. The results show that around 85% of participants were able to operate Canva independently, 90% produced at least two visual designs, and 75% demonstrated improved understanding of basic visual communication principles. In addition, participants experienced increased confidence, creativity, and collaboration skills. The program also broadened participants’ awareness of using design skills to support social activities and MSME promotion. In conclusion, Canva-based training effectively improves youth digital skills and plays an important role in technology-based community empowerment
Pengenalan Wajah Secara Realtime Menggunakan Adaboost Viola-Jones dan 2D DWT-PCA dengan Struktur Index KNN-KD Tree Hasan; Mardi Hardjianto
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 4 No. 1: MARET 2024
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v4i1.300

Abstract

Tujuan dari deteksi wajah adalah untuk mengetahui ada atau tidaknya wajah dalam sebuah gambar atau video, walaupun terlihat mudah dilakukan oleh manusia, ternyata deteksi wajah sangat sulit dilakukan oleh komputer. Selain lingkungan sekitar juga terdapat beberapa hal yang dapat menjadi kendala dalam mendeteksi wajah, langkah ini menjadi sulit ketika terjadi variasi iluminasi, posisi, ekspresi wajah, orientasi, kriteria morfologi dan atribut yang melekat atau menutupi wajah seperti kacamata, topi, masker. Penelitian ini menerapkan metode algoritma Viola-Jones yang memiliki tiga keunggulan: Deteksi wajah secara real-time, Efisiensi Komputasi dan Deteksi Objek Lain. Metode 2D DWT-PCA digunakan untuk mengurangi dimensi data dan menghilangkan noise pada gambar, dan KNN-KD Tree digunakan untuk mengenali wajah berdasarkan fitur-fitur yang telah diekstraksi dari gambar. Hasil pengujian dengan total 78 variasi pada objek wajah yang dideteksi yaitu didapatkan hasil dengan keakuratan sebesar 80.77%.
Co-Authors Afdhal Rizki Yessa Agani, Nazori Agnes Aryasanti Ahmad Pudoli Alamsyah Nur Alif Ar-Rijalul Haq Aryasanti, Agnes Asep Wahyudi Zein Baehaqi Baihaqi, Kiki Ahmad Citra Fertia Anggraini Desmon Manalu, Perdinan Devit Setiono Dewi Kusumaningsih Dimas Ariyanto Dolly Virgian Shaka Yudha Sakti Dwi Achadiani Fadli Fairuz Ramadhan Farhannullah Farhannullah Fawwaz Dzakwan Febriani, Suci Indah Fiska Fadhilah Fiska Fadhilah Goenawan Brotosaputro Guntur Sarwo Trengginas Hasan Hasan Hibatul Azizi Imam Farisi Iman Permana Imelda Imelda Indah Puspasari Handayani Irawan Irawan Irwan Robi Prastomo Jan Everhard Jeremy Jonathan Joko Christian Chandra Juanita, Safitri Lis Suryadi Lukas Tommy M. Ainur Rony Mohammad Syafrullah Muh. Wildan Mauludy Muhamad Givari Ramadan Muhammad Dwi Nursansyah Muhammad Hikmat Fathur Rahman Nawiroh Vera Nazori AZ Noya, Muh. Mustafa Daniel Nugraha, Yogie Setiawan Nuri Wiyono Pradana, Rizky Pudoli, Ahmad Purwanto Purwanto Purwanto Purwanto Putra Panji Wicaksono Putra, Aldi Triavin Dwi Putri Hayati Putri, Aprilianti Ratna Kusumawardani Ratna Kusumawardani Ratna Ujiandari Ratna Ujiandari Rieska Prasetyani Riri Irawati Ririt Roeswidiah Ririt Roeswidiah Robby Ilhamkusuma Roeswidiah, Ririt Rosi Ulibasa Rulyana, Devita Ruwirohi, Jan Everhard Safrina Amini Samsinar Samsinar Suwarno, Damar Bambang Syawalludin, Syawalludin Triyono, Gandung Umaimah Wahid Utomo Budiyanto Wahyu Pramusinto Wahyu Widadi Wendi Usino Winudhapratama, Savero