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All Journal International Conference on Engineering and Technology Development (ICETD) Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Ilmiah Sinus bit-Tech Jurnal Informatika Ekonomi Bisnis Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer System and Informatics (JoSYC) Jurnal Ilmiah Intech : Information Technology Journal of UMUS Jurnal Teknik Informatika (JUTIF) Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal Automation Computer Information System (JACIS) Bulletin of Information Technology (BIT) International Journal Software Engineering and Computer Science (IJSECS) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB Journal of Practical Computer Science (JPCS) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Pengabdian Mandiri Universal Raharja Community (URNITY Journal) Jurnal Lentera Pengabdian Jurnal Informatika Ekonomi Bisnis Proceeding Mercu Buana Conference on Industrial Engineering Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Riwayat: Educational Journal of History and Humanities International Journal of Applied Research and Sustainable Sciences (IJARSS) International Journal of Sustainable Applied Sciences (IJSAS) VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian SAINTEK International Journal of Integrated Science and Technology EduBase: Journal of Basic Education
Muhamad Fatchan
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Pemanfaatan AI untuk Penyusunan Modul Ajar Guru di MI Unggulan Al Kahfi Ermanto, Ermanto; Fatchan, Muhamad; Aprila Hardi, Resty
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 2 (2024): Desember 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i2.107

Abstract

Pemanfaatan kecerdasan buatan (AI) dalam dunia pendidikan semakin berkembang dan memberikan berbagai kemudahan bagi pendidik dalam menyusun materi ajar. Penelitian ini bertujuan untuk menganalisis efektivitas penggunaan AI dalam penyusunan modul ajar bagi guru di Madrasah Ibtidaiyah (MI) Unggulan Al Kahfi. Metode yang digunakan dalam penelitian ini adalah deskriptif kualitatif dengan teknik pengumpulan data melalui wawancara, observasi, dan studi literatur. Hasil penelitian menunjukkan bahwa penggunaan AI membantu guru dalam menyusun materi ajar yang lebih sistematis, interaktif, dan sesuai dengan kebutuhan kurikulum. Selain itu, AI juga mempercepat proses pembuatan materi, memberikan rekomendasi konten yang relevan, serta membantu dalam personalisasi pembelajaran sesuai dengan karakteristik siswa. Namun, terdapat beberapa tantangan dalam implementasi AI, seperti keterbatasan pemahaman guru terhadap teknologi dan kebutuhan akan pelatihan lebih lanjut. Kesimpulannya, AI dapat menjadi alat bantu yang efektif dalam meningkatkan kualitas modul ajar di MI Unggulan Al Kahfi dengan syarat adanya dukungan dan pelatihan yang memadai bagi tenaga pendidik. Kata Kunci: kecerdasan buatan, AI, modul ajar, pendidikan, Madrasah Ibtidaiyah.
Pelatihan Pemanfaatan Aplikasi Canva untuk Pembelajaran Interaktif di Bimbingan Belajar Anak Hebat Cabang Cibarusah Ermanto, Ermanto; Fatchan, Muhamad; Aprila Hardi, Resty; Suryadi
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 3 No. 1 (2025): Juni 2025
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v3i1.132

Abstract

The "Utilization of the Canva Application for Interactive Learning" training was held at the Cibarusah Branch of the Great Children's Tutoring Center (Bimbingan Belajar Anak Hebat) as an effort to improve educators' competency in utilizing digital technology to support the learning process. This activity was motivated by the need for teachers and tutors to provide learning media that are more engaging, interactive, and easy for students to understand. The training method was a workshop approach, combining theory and hands-on practice using the Canva application. Participants were guided in creating various interactive media, such as presentations, infographics, visual materials, and evaluation content tailored to children's learning needs. The training results demonstrated improved skills in designing creative learning media and increased motivation to integrate technology into teaching and learning activities. This training is expected to make the learning process at the Cibarusah Branch of the Great Children's Tutoring Center more effective, enjoyable, and able to encourage active student participation. Keywords: Canva, Interactive Learning, Digital Media, Tutoring, Teacher Training.
WEBSITE PONDOK PESANTREN YATIM PIATU ANAK SHOLEH AL-HIDAYAH Edy Widodo; Muhamad Fatchan; Andri Firmansyah; Sifa Fauziah; Andrian, Andrian
JURNAL PENGABDIAN MANDIRI Vol. 4 No. 9 (2025): September 2025
Publisher : Bajang Institute

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

Abstract

Dalam mengembangkan duia pendidikan itu tidak mudah dan banyak sekali kendala-kendala yangmemang harus kita hadapi bersama, terutama terkait dengan begitu pesatnya perkembangan Teknologi Informasi yang saat ini memang sangat dibutuhkan dan sangat berpengaruh dalam dunia pondok pesantren yang memang begitu monoton dalam agama. Penguasaan ilmu pengetahuan dan teknologi serta semangat kompetitif juga meruapakan hal penting bagi para ustad yang profesional karena diharapkan mereka dapat membawa atau mengantarkan para santri didiknya mengarungi dunia ilmu pengetahuan dan teknologi untuk memasuki era global yang melek ilmu pengetahuan dan teknolog, dan sangat kompetiti.f Manfaat website bagi pondok pesantren adalah meningkatkan jangkauan informasi dan dakwah, mempermudah administrasi seperti pendaftaran dan pengelolaan keuangan, meningkatkan kepercayaan dan citra lembaga, serta menjadi sarana untuk sosialisasi, promosi, dan penggalangan dana. Selain itu, website juga menjadi langkah awal digitalisasi pendidikan dan menunjukkan pesantren mampu beradaptasi dengan perkembangan zaman dan menjadi lebih relevan di era digital. Website dapat menjadi jembatan komunikasi antara pesantren dengan para alumni, orang tua santri, dan masyarakat umum, mempererat tali silaturahm.
Model Prediksi Ketercapaian Learning Outcome Based Education Mahasiswa di Program Studi Teknik Informatika Menggunakan Algoritma Machine Learning Danny, Muhtajuddin; Fatchan, Muhamad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1259

Abstract

The Informatics Engineering Undergraduate Program, Faculty of Engineering, Pelita Bangsa University, implements Outcome Based Education (OBE) by emphasizing the achievement of student Learning Outcomes (LO) as an indicator of the quality of learning in higher education. LO achievement measurement has been mostly done manually through academic assessments, so it is less than optimal in predicting student performance comprehensively. This study aims to build a prediction model for student Learning Outcomes achievement using machine learning algorithms. Research data were obtained from academic results, attendance, lecture activities, and student skill indicators. The prediction model was developed by comparing the Support Vector Machine (SVM), Random Forest, Decision Tree, and Artificial Neural Network (ANN) algorithms, with performance evaluation using accuracy, precision, recall, and F1-score metrics. The results showed that the Random Forest algorithm provided the best performance with more stable accuracy compared to other algorithms. Furthermore, the distribution of Program Learning Outcomes (PLO) in the curriculum shows: PLO 1 (57 courses), PLO 2 (10 courses), PLO 3 (3 courses), PLO 4 (27 courses), PLO 5 (8 courses), PLO 6 (20 courses), PLO 7 (33 courses), PLO 8 (10 courses), PLO 9 (54 courses), and PLO 10 (57 courses). Based on student scores in 57 courses, the distribution of assessment categories is as follows: Very Good 38.1%, Good 46.3%, Fair 8.4%, and Fail 7.2%. Thus, the PLO achievement of the Informatics Engineering Undergraduate Study Program reached 84.4% in the Good and Very Good categories. This finding provides a significant contribution to efforts to monitor and plan strategies for improving the quality of OBE-based learning adaptively and data-driven.
Model Prediksi Ketercapaian Learning Outcome Based Education Mahasiswa di Program Studi Teknik Informatika Menggunakan Algoritma Machine Learning Danny, Muhtajuddin; Fatchan, Muhamad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1259

Abstract

The Informatics Engineering Undergraduate Program, Faculty of Engineering, Pelita Bangsa University, implements Outcome Based Education (OBE) by emphasizing the achievement of student Learning Outcomes (LO) as an indicator of the quality of learning in higher education. LO achievement measurement has been mostly done manually through academic assessments, so it is less than optimal in predicting student performance comprehensively. This study aims to build a prediction model for student Learning Outcomes achievement using machine learning algorithms. Research data were obtained from academic results, attendance, lecture activities, and student skill indicators. The prediction model was developed by comparing the Support Vector Machine (SVM), Random Forest, Decision Tree, and Artificial Neural Network (ANN) algorithms, with performance evaluation using accuracy, precision, recall, and F1-score metrics. The results showed that the Random Forest algorithm provided the best performance with more stable accuracy compared to other algorithms. Furthermore, the distribution of Program Learning Outcomes (PLO) in the curriculum shows: PLO 1 (57 courses), PLO 2 (10 courses), PLO 3 (3 courses), PLO 4 (27 courses), PLO 5 (8 courses), PLO 6 (20 courses), PLO 7 (33 courses), PLO 8 (10 courses), PLO 9 (54 courses), and PLO 10 (57 courses). Based on student scores in 57 courses, the distribution of assessment categories is as follows: Very Good 38.1%, Good 46.3%, Fair 8.4%, and Fail 7.2%. Thus, the PLO achievement of the Informatics Engineering Undergraduate Study Program reached 84.4% in the Good and Very Good categories. This finding provides a significant contribution to efforts to monitor and plan strategies for improving the quality of OBE-based learning adaptively and data-driven.
Ethno-Edutainment Electronic Module (EMEE) to Strengthen Local Cultural Character in Elementary School Students Titin Sunaryati; Muhamad Fatchan; Muhamad Sudharsono; Pipin Angela
EduBase : Journal of Basic Education Vol. 6 No. 1 (2025): EduBase : Journal of Basic Education
Publisher : LJPI UI Bunga Bangsa Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47453/edubase.v6i1.3186

Abstract

The erosion of local cultural values due to globalization poses a significant challenge to the development of character in Indonesian students, who are expected to uphold tolerance, ethics, and mutual respect. Objective: This study aims to develop an Android-based ethno-edutainment electronic module to strengthen local cultural character among elementary school students. Novelty: The module integrates ethno-edutainment and local cultural values into a digital learning platform, offering an innovative approach to character education. Methods: The module was developed using the ADDIE model (Analysis, Design, Development, Implementation, Evaluation) within a Research and Development (R&D) framework. The product was validated by media, content, and language experts, and tested on 55 students at Pondok Bambu 06 Duren Sawit State Elementary School, East Jakarta. Results: The validation results showed that the module was categorized as "very good" across all aspects. The practicality test revealed positive student responses, and the effectiveness test demonstrated a significant improvement in learning outcomes, with an average pre-test score of 70.54 and a post-test score of 87.45. Conclusion: The module is effective in supporting character education, with interactive features and local cultural content that enhance student engagement and strengthen their national identity.
Drinking Water Platform System Design (OTODRINK) Fatchan, Muhamad; Firmansyah Putra, Dandy; Suwarno, Agus
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 6 No. 2 (2023)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32832/inovatif.v6i2.648

Abstract

This research aims to address the issue of availability of safe drinking water in densely populated urban areas through the implementation of Internet of Things (IoT). The background of the study is based on the rapid population growth and its impact on the demand for water, as well as the increasing consumption of safe drinking water in society. The study utilizes the Otodrink system, which integrates ESP8266 microcontroller and RFID technology to distribute clean water automatically to user's tumblers. The research methodology includes system design, hardware and software development, and functional testing of the system. The findings indicate that the Otodrink system successfully distributes water efficiently and in a controlled manner, while reducing the use of plastic-packaged mineral water. The implications of this research are increased accessibility and availability of safe drinking water in urban areas, as well as a reduction in the negative environmental impact of plastic waste.
PREDICTION OF 2024 PRESIDENTIAL ELECTION USING K-NN WITH METRIC APPROACHES CHEBYSHEV AND EUCLIDEAN BASED ON TWITTER DATA INVESTIGATION Darmawan, Steven Ryan; Fatchan, Muhamad; Maulana, Donny
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.2.1720

Abstract

The potential difference between the popularity of presidential candidates on social media and in the general public poses a serious challenge in predicting the outcome of the 2024 presidential election. Technical constraints in collecting, cleaning and analyzing dynamic and large-scale social media data can threaten the accuracy and validity of predictions. To overcome this problem, careful steps and in-depth understanding are needed. Therefore, this study aims to predict the winner of the 2024 presidential election from the popularity of presidential candidates Anies Baswedan, Ganjar Pranowo, and Prabowo Subianto on Twitter. The K-Nearest Neighbor (K-NN) method with the Both Metric approach (Euclidean and Chebyshev) was used to analyze 51,192 tweet data through the Knowledge Discovery in Database (KDD) stage using Orange software. The evaluation results show almost the same performance, with AUC values of 0.725 for Euclidean and 0.720 for Chebyshev. The CA result was 55.6% for Euclidean and 55.4% for Chebyshev. Although F1, precision, and recall were almost the same, overall, the Euclidean metric was better. The prediction shows Prabowo Subianto as the most popular candidate on Twitter. Nonetheless, these results need to be interpreted with caution and strengthened with further analysis and additional data to get a more comprehensive conclusion. This research shows that K-NN with both metrics can provide predictions above 50%, reliable enough to be able to predict the most popular candidates on Twitter.
Optimasi Pencatatan Dan Perhitungan Barang NG Di CV Anugrah Ikhasn Keluarga menggunakan Metode Agile Ramadhan, Reza Rizky; Fatchan, Muhamad; Wiyanto, Wiyanto; Edy, Sarwo Edy; Riyanto, Kuwat Riyanto
Jurnal SIGMA Vol 16 No 1 (2025): Juni 2025
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v16i1.6051

Abstract

Dalam industri manufaktur, kualitas produk menjadi faktor krusial yang menentukan keberhasilan perusahaan. CV Anugrah Ikhsan Keluarga, yang bergerak dalam produksi komponen logam, menghadapi tantangan dalam pencatatan barang Not Good (NG) secara manual yang rentan terhadap kesalahan dan manipulasi data. Hal ini menyebabkan ketidaksesuaian antara laporan produksi dan data gudang, serta kurangnya monitoring real-time yang menghambat pengambilan keputusan. Penelitian ini bertujuan mengembangkan sistem pencatatan dan perhitungan barang NG secara otomatis menggunakan metode Agile. Sistem dibangun dengan JavaScript dan framework Next.js yang mendukung server-side rendering (SSR) dan static site generation (SSG) untuk performa optimal. Metode Agile dipilih guna memfasilitasi iterasi cepat dan umpan balik berkelanjutan. Hasil penelitian diharapkan meningkatkan efisiensi pencatatan, mencegah manipulasi data, dan memungkinkan monitoring real-time, serta memberikan kontribusi dalam pengembangan sistem serupa dan referensi akademik di bidang teknik informatika.
Detect the Activity of Benign and Malignant Breast Cancer Ayu Fitriyani; Muhamad Fatchan; Wahyu Hadikristanto
International Journal of Integrated Science and Technology Vol. 2 No. 5 (2024): May 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i5.1870

Abstract

Breast cancer detection is an important stage for early cancer diagnosis. In this study, a Convolutional Neural Network (CNN) algorithm is used to detect breast cancer. The dataset used consists of MRI scan images of benign and malignant breast cancer, which are processed through breast image cropping and data augmentation. The model was trained using CNN architecture with transfer learning method of VGG-16 model. The results of the model training showed good performance with an accuracy of 62%. These findings show the potential of using CNN and transfer learning in improving early detection of breast cancer.
Co-Authors . Ermanto . Suratman Abdul Halim Anshor Abdul Hasyim Abizar Ar Rifa’i Rifa’i Afriantoro, Irfan Agus Suwarno, Agus Aguswin, Ahmad Ahmad Turmudi Zy al fiyan Alfarizi, Muhammad Farhan Andri Firmansyah Andrian Andrian Anisa Rahmawati Annisa Maulana Majid Aprila Hardi, Resty Apriyandi M Ardimansyah Ardimansyah Ariza, Rini Asep Hidayat Asep Suprianto Ayu Fitriyani Aziz, Faruq B.M.A.S. Anaconda Bangkara Bagoes Ramadhan Bagus Dwi Saputro Butsianto, Sufajar Clarita, Anggita Risqi Nur Dahyoung Yenuargo Darmawan, Steven Ryan Dendy K. Pramudito Doni, Muhamad Edora Edora Edora Edy Widodo Edy Widodo Edy Widodo Edy, Sarwo Edy Elkin Rilvani Endah Yaodah Kodratilah Fadhillah, Faizah Via Faris Muzaki, Moch. Nauval Firmansyah Putra, Dandy Fitriani Hadiansyah, Zikri Halim Anshor, Abdul Hari Sugeng Hendra Lesmana Herdyanto, Febro Hidayat, Chaerul Indra Permana, Indra Irfan Afriantoro Irsyad Syhruddin Jamroni, A. Reza Baehaqa Jamroni Linda Marlinda Listanto, Firgiawan Marayasa, I Gde Bayu Priyambada MAULANA, AFFAN Maulana, Donny Muhamad Ekhsan Muhamad Sudharsono Muhtajuddin Danny Najwa Sabilla, Nurul Nanang Tedi Kurniadi Nasution, Annio Indah Lestari Naufal Muyassar Naya, Candra Ngudi Wiyatno, Tri Nuraeniah, Iin Nurhadi Surojudin Nurhaliza, Zahra Nur’Aeni, Nur’Aeni Oktavianto, Rainal Zulian Pakpahan, Wyjentiadi Pengestu, Rayendra Pipin Angela Pratama, Galang Rintang Widya Purwanto Purwanto Putri Nabila Amir Qori yumansyah Qori Ramadhan, Reza Rizky Retno Purwani Setyaningrum Reza Maulana, Muhammad Rika Anugrahaini, Savariana Rindiani Tri Lestari Riyanto, Kuwat Riyanto Rozikin, Zaenur Sifa Fauziah Siti Rahayu Sri Indriyani Sugiarto, Jumat Azzam SUPRAPTO suratman Surya Bintarti Suryadi Tedi, Nanang Tiani Ayu Lestari TITIN SUNARYATI Tri Ngudi Wiyatno Turmudi Zy, Ahmad Valentin*, M Ryan Bagus Wahyu Hadi Kristanto Wahyu Hadikristanto Wahyu Indrarti Widi Winjani Widiyawati , Widiyawati Wiyanto - Yumansyah, Qori Yupita Fitria Riyanti