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All Journal TEKNIK INFORMATIKA Jurnal Simetris Speed - Sentra Penelitian Engineering dan Edukasi CESS (Journal of Computer Engineering, System and Science) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Network Engineering Research Operation [NERO] Jurnal Komtika (Komputasi dan Informatika) JMM (Jurnal Masyarakat Mandiri) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Jurnal Media Elektro : Journal of Electrical Power, Informatics, Telecommunication, Electronics, Computer and Control System Adimas : Jurnal Pengabdian Kepada Masyarakat KOMPUTEK Journal of Information Systems and Informatics GANESHA: Jurnal Pengabdian Masyarakat Formosa Journal of Computer and Information Science NERO (Networking Engineering Research Operation) Kenduri: Jurnal Pengabdian Dan Pemberdayaan Masyarakat Jurnal ilmiah teknologi informasi Asia Jurnal Komtika (Komputasi dan Informatika) Mathematics, Informatics, Knowledge, And Information Research
Mohammad Bhanu Setyawan
Universitas Muhammadiyah Ponorogo
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Penerapan Model Literasi Digital Berbasis Sekolah Untuk Membangun Konten Positif Pada Internet Karaman, Jamilah; Widaningrum, Ida; Setyawan, Mohammad Bhanu; Sugianti, Sugianti
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 5 No 1 (2021): Februari
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v5i1.3701

Abstract

Tidak bisa dipungkiri bahwa internet membawa dampak positf bagi kehidupan anak dan remaja karena memudahkan untuk mendapatkan informasi terbaru, informasi terkait tugas dan pelajaran sekolah, meningkatkan kreatifitas, memperat komunikasi antar teman dan lain-lain. Seperti dua sisi mata uang, teknologi internet juga memberi dampak negatif yang mempengaruhi martabat kedirian dan kehidupan generasi remaja sekarang ini. Munculnya beragam kasus cybercrime, adiksi terhadap pornografi dan games online, menjadi bukti nyata sangat rentannya pengaruh negatif perkembangan internet terhadap dunia anak. Kecakapan literasi digital, merupakan salah satu langkah preventif dan edukatif untuk menyadarkan dampak positif dan meminimalisir dampak negatif internet. Sekolah, bisa menjadi pengerak utama untuk mengkampanyekan dan memberikan kecakapan literasi digital kepada anak didiknya. Namun ada beberapa permasalahan untuk menerapkan literasi digital di sekolah. Pertama, belum adanya kurikulum kecakapan literasi digital dengan acuan standar. Kedua, hilangnya pelajaran Teknologi Informasi dan Komunikasi yang seharusnya bisa menjadi media penyuluhan literasi digital. Ketiga, masih minimnya kecakapan literasi digital yang dimilliki oleh para guru. Hal ini juga terjadi di Madrasah Aliyah Negeri (MAN) 2 Ponorogo, sehingga perlu diadakan pelatihan atau workshop literasi digital berbasis sekolah untuk menunjang keberhasilan budaya gerakan literasi sekolah. Berdasarkan evaluasi workshop literasi digital, peserta merespon dengan baik materi dan evaluasi kompetensi standard. Peserta mampu mengikuti dengan baik dan memahami semua materi informasi personal dan privasi, jejak digital dan kemanan Wi-Fi.Kata Kunci: cybercrime; literasi digital; madrasah.  Application of School Based Digital Literacy Model To Build Positive Content On The Internet ABSTRACT It is undeniable that the Internet has a positive impact on the lives of children and adolescents because it facilitates obtaining the latest information, information related to school tasks and increases creativity, strengthens communication between friends and others. Like the two sides of a coin, Internet technology also has a negative impact that affects the dignity of oneself and the lives of today's teenagers. The emergence of several cases of cybercrime, pornography addiction, and online games, is a real test of the very vulnerable negative influence of Internet development in the world of children. Digital literacy skills are one of the preventive and educational steps to achieve positive impacts and minimize the negative impacts of the Internet. Schools can be the main drivers for campaigning and providing digital literacy skills to their students. But there are some problems to implement digital literacy in schools. First, there is no curriculum for digital literacy skills with standard references. Secondly, the loss of Information and Communication Technology lessons that should have been a means for digital literacy advice. Third, the lack of digital literacy skills that teachers possess. This also happened in Madrasa Aliyah Negeri (MAN) 2 Ponorogo, so there must be a training or digital literacy workshop at the school to support the cultural success of the school literacy movement. Based on the evaluation of the digital literacy workshop, participants responded well to the material and the assessment of standard skills. Participants can follow well and understand all personal information and privacy material, fingerprints and Wi-Fi security..Keywords: cybercrime; digital literacy; madrasah. 
Sistem Pendukung Keputusan Siswa terbaik MAN 2 Ponorogo berbasis Website menggunakan Metode Simple Additive Weight (SAW) Bimantoro, Alfin Dien; Bhanu Setyawan, Mohammad; Litanianda, Yovi
KOMPUTEK Vol. 9 No. 2 (2025): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v9i2.2868

Abstract

Proses seleksi siswa terbaik di MAN 2 Ponorogo merupakan tahap kritis dalam mempertahankan kualitas pendidikan dan reputasi Madrasah. Namun, dalam beberapa kasus, proses seleksi tersebut masih dilakukan secara manual dan kurang terstruktur, menyebabkan potensi terjadinya ketidakpastian dan ketidakadilan dalam penentuan siswa terbaik, maka dibutuhkan sebuah sistem yang bisa mengakomodir kebutuhan tersebut. Penggunaan metode Simple Additive Weighting (SAW) merupakan alternatif jalan keluar dalam membantu sekolah dalam memilih siswa terbaik. Metode pengembangan aplikasi untuk membuat sistem pendukung keputusan siswa terbaik  menggunakan metode waterfall dan pada pengujian akhir sistem menggunakan pengujian blackbox. Hasil akhir dari penelitian ini Pengujian fungsionalitas aplikasi dengan uji blackbox tidak ditemukan kesalahan dan berjalan sesuai dengan rancangan yang di inginkan serta sistem bisa memberikan rekomendasi  siswa terbaik dengan tingkat akurasi dan efisiensi yang baik.
Rekayasa Aplikasi Eposal Menggunakan Algoritma Base64 Untuk Menyimpan Data Pengguna Cobantoro, Adi Fajaryanto; Setyawan, Mohammad Bhanu; Oktavianto, Hardiyan
Jurnal Komtika (Komputasi dan Informatika) Vol 7 No 1 (2023)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v7i1.8711

Abstract

E-commerce merupakan kegiatan jual beli yang menggunakan media internet. Kerap ditemukan adanya data pribadi pelanggan yang bersifat rahasia seperti nama lengkap, alamat dan nomor telepon tersimpan pada database E-commerce. Selain itu data-data credential lain juga sering kali bocor pada aplikasi berbasis internet. Kebocoran data dapat disebab oleh, konfigurasi perangkat lunak yang salah, social engineering, Recycled Passwords, Physical Theft of Sensitive Devices, Software Vulnerabilities, dan Use of Default Passwords. Banyak kasus kebocoran data di Indonesia disebabkan oleh konfigurasi perangkat lunak yang salah, sehingga untuk mengamankan data harus memiliki keahlian dibidang keamanan. Salah satu langkah pencegahan kebocoran data adalah Encrypt All Data. Yang dimaksud Encrypt All Data disini adalah mengenkripsi semua data yang ada di dalam database. Metode enkripsi tersebut salah satunya adalah Algoritma Base64. Algoritma Base64 merupakan algoritma yang menggunakan kode ASCII dalam proses encoding maupun decodingnya. Pada proses Enkripsi dan Dekripsi, Algoritma Base64 menggunakan dua buah tabel bantu yaitu tabel ASCII dan tabel index Base64. Pada tahap awal dilakukan proses perubahan kata menjadi kode ASCII. Tahap kedua, kode ASCII tersebut akan diubah ke dalam kode biner 8bit. Tahap ketiga, kode biner 8bit dibagi menjadi kode biner 6 bit. Tahap keempat, blok-blok tersebut dikembalikan lagi ke bentuk desimal, kemudian disesuaikan dengan tabel Index Base64. Sedangkan untuk proses dekripsi, merupakan kebalikan dari proses enkripsi dengan proses yang sama. Tahap kedua, dilakukan perubahan dari kode Index ke dalam kode biner 6. Tahap ketiga, membuat kode biner 6bit menjadi kode biner 8bit. Tahap keempat yaitu mengubah biner 8 ke ASCII. Tahapan selanjutnya adalah mengubah kode ASCII ke kode desimal. Alur algoritma Base64 pad apenelitian ini akan diimplementasikan pada aplikasi Eposal di Toko Mina Alumunium. Proses implementasi ini dengan menambahkan satu fungsi “base64_encode” untuk setiap data yang masuk ke dalam database. Fungsi tersebut dimasukkan kedalam salah satu proses yang ada pada aplikasi Eposal yaitu proses simpan data konsumen Mina Alumunium. hasil yang diperoleh adalah bahwa setiap data yang dimasukkan ke dalam Eposal Mina Alumunium atau karakter yang diinputkan tersebut disimpan didalam database berbentuk enkripsi data acak. Sehingga jika ada penyusup yang berhasil masuk ke dalam database, penyusup tersebut tidak bisa membaca data yang ada di dalam database.
Implementasi Algoritma Convolutional Neural Network (CNN) Untuk Identifikasi Jenis Tanaman Rimpang (Zingiberaceae) Rani Dwi Kartikasari; Mohammad Bhanu Setyawan; Fauzan Masykur; Adi Fajaryanto Cobantoro
MIKIR : Mathematics, Informatics, Knowledge And Information Research Vol. 1 No. 1 (2025): OKTOBER
Publisher : PT Mekar Research and Publishing

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

Abstract

Rhizomes (Zingiberaceae) are modified plant stems that grow horizontally beneath the soil surface and can produce shoots and new roots from their nodes. Rhizome plants (Zingiberaceae) are known as ginger or spice plants. This research article discusses the identification of rhizome plant species using Convolutional Neural Network (CNN) algorithm with VGG19 architecture, involving a total of 10 classes of data samples. The rhizome images underwent data preprocessing, resizing them from 500 x 500 to 200 x 200 pixels. During the model design phase, three different scenarios were tested, considering variations in dataset proportions, number of epochs, and batch sizes. The results of the three scenarios showed that the second scenario performed the best, achieving an accuracy of 90%, a loss of 0.285, precision of 93%, recall of 89%, and F1-Score of 91%. The first scenario obtained an accuracy of 88%, and the third scenario achieved an accuracy of 82%. However, when applying the model to test images and achieving the highest accuracy of 90% during training, the accuracy dropped to 40% when evaluated on 100 testing data. This drop in accuracy can be attributed to several factors, including noise in the dataset used and insufficient amount of training data, leading to the model being less effective in learning and recognizing data patterns.
The Road Safety Literacy Strengthening Assistance For The Lentera Community (Orderly And Safe Literacy On The Highway) In Ponorogo Regency Ida Yeni Rahmawati; Mohammad Bhanu Setyawan; Adi Fajaryanto Cobantoro; Susi Darihastining; Tri Wahyono; Siti Khoirul Bariyah
KENDURI : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 6 No. 1 (2026): January-April
Publisher : Yayasan Darussalam Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62159/kenduri.v6i1.2150

Abstract

The high number of traffic accidents, especially among students and novice drivers, indicates a low level of road safety literacy in the community. The LENTERA (Orderly and Safe Literacy on the Road) community in Ponorogo Regency was formed as an effort to build collective awareness of the importance of safe driving. This study aims to assist and strengthen the capacity of this community through structured interactive training. The method used in this activity is a participatory descriptive approach, with stages of socialization, training, and evaluation using pre-test and post-test instruments, as well as observation of participant involvement. The results showed a significant increase in participants' understanding of traffic safety principles, with an average pre-test score of 62.06 increasing to 85.12 in the post-test. Observations also showed an increase in participants' enthusiasm, analytical skills, and reflective awareness. The conclusion of this activity is that strengthening safety literacy through a community approach can encourage constructive and sustainable behavioral changes. It is recommended that this community-based training model be replicated in other regions, with cross-sector collaboration and the development of more contextual modules. Furthermore, the outreach materials presented should be based on factual data on frequent accidents and should provide insights into each incident, with the goal of reducing the number of road accidents, particularly among students. Materials supplemented with simulations of road traffic engineering provide knowledge that will be easier to understand in everyday practice and, of course, be more memorable.
Building an Annotated Corpus of Advice-Giving in Indonesian Thesis Supervision for Educational Text Mining Elok Putri Nimasari; Adi Fajaryanto Cobantoro; Mohammad Bhanu Setyawan; Ismail Abdurrozaq; Ariyanti Ariyanti; Navila Uliya Sahidah
Formosa Journal of Computer and Information Science Vol. 5 No. 1 (2026): March 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjcis.v5i1.16529

Abstract

While educational text mining has widely examined student feedback and institutional evaluation, little attention has been paid to advice-giving in thesis supervision as an interactional and power-relational practice. Therefore, this present study aims to analyze and build a domain-sensitive annotated corpus of advice-giving in Indonesian thesis supervision for future educational text mining. Using a qualitative-informed corpus development research design, the study collected and analyzed 155 annotated utterances drawn from authentic thesis supervision transcripts across Indonesian universities. The results identified six advice-giving labels classified into three interactional modes: power-over, power-gaining, and power-maintaining following Zhang and Hyland’s theoretical of power and roles. Cohen’s Kappa reached 1.00, indicating perfect annotation agreement. The corpus contributes a reliable methodological foundation for AI-assisted analysis of supervisory discourse and inclusive academic supervisory.
Student Engagement Detection Based on Visual Behavior Indicators Using YOLOv8 on a Public Classroom Dataset Mohammad Bhanu Setyawan; Angga Prasetyo; Fauzan Masykur
MIKIR : Mathematics, Informatics, Knowledge And Information Research Vol. 2 No. 2 (2026): JUNE
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/sser8h18

Abstract

Student engagement is an important indicator for evaluating the quality of the learning process; however, its measurement in conventional classrooms still largely relies on subjective and labor-intensive manual observation. This study aims to establish a reproducible baseline for student engagement detection based on visual behavioral indicators using the YOLOv8 model on a public dataset. The working dataset was constructed from two subsets of the Student Class Behavior (SCB) Dataset and restructured into five behavioral classes: hand_raising, reading, writing, bowing_head, and turn_head, resulting in 9,274 image-label pairs split into 6,491 training, 1,854 validation, and 929 test samples. The experiment used YOLOv8n with an image size of 416, a batch size of 8, and 50 effective epochs in Google Colab. Performance was evaluated using precision, recall, mAP@0.5, and mAP@0.5:0.95. The results show that the model achieved a precision of 0.4429, a recall of 0.5393, mAP@0.5 of 0.4630, and mAP@0.5:0.95 of 0.3211. The best class-level performance was observed for writing (AP 0.635) and hand_raising (AP 0.597), while bowing_head (AP 0.288) and turn_head (AP 0.332) remained comparatively weak. These findings indicate that YOLOv8n is feasible as a reproducible baseline for visual student behavior detection, although annotation refinement, comparative experiments, and architectural optimization are still required to strengthen the scientific contribution and the feasibility of real-world classroom deployment
Co-Authors ., Sugianti Aang Kisnu Darmawan Agustin, Nely Dwi Angga Prasetyo Angga Prasetyo Arief Rahman Yusuf Ariyanti Aslan Alwi Bimantoro, Alfin Dien Cobantoro, Adi Fajaryanto Cobantoro, Adi Fajaryanto DWI RAHMAWATI Elok Putri Nimasari Fauzan Fasykur Fauzan Masykur Hardiyan Oktavianto Hoiriyah, . Ida Widaningrum, Ida Ida Yeni Rahmawati Ismail Abdulrazzaq Zulkarnain Ismail Abdurrozaq Jamilah Karaman Karaman, Jamilah Kuntang Winangun Miftahudin Agung Budi Wibowo Mita Bela Franciska Mohammad Waail Al Wajieh Munirah Munirah Navila Uliya Sahidah Nurfitri, Khoiru Oktavianto, Hardiyan Permana Putra, Angga Dian Prasetyo, Angga Rani Dwi Kartikasari Siti Khoirul Bariyah Sugianti, Sugianti Susi Darihastining Sussolaikah, Kelik Tri Wahyono Tri Yandi Yovi Litanianda, Yovi Zulkarnain, Ismail Abdurrozaq