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All Journal ILKOM Jurnal Ilmiah Madani : Indonesian Journal of Civil Society Jurnal Teknik Informatika (JUTIF) Mejuajua Journal Computer Science and Informatic Systems : J-Cosys Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Jurnal Pengabdian Pada Masyarakat Kapas: Kumpulan Artikel Pengabdian Masyarakat Jurnal Pengabdian Sosial Engagement: Jurnal Pengabdian Kepada Masyarakat
Muhaimin Hasanudin
Universitas Mercu Buana, Jakarta, Indonesia
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Pelatihan Komputer dan Penggunaan Microsoft Word Pada Siswa Berkebutuhan Khusus Di Homeschooling Lantaburo Kabupaten Tangerang Muhaimin Hasanudin; Muhammad Rifqi; Ifan Prihandi
Madani : Indonesian Journal of Civil Society Vol. 5 No. 2 (2023): Madani, Agustus 2023
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/madani.v5i2.1815

Abstract

Homeschooling (HS) Lantaburo is one of the alternative schools in the city of Tangerang which has a target of fostering and developing life skills for Students with Special Needs (ABK) so they can meet the basic needs of Activity of Daily Living (ADL) so that one day they can be independent and empowered in society. In implementing the ADL program, there are obstacles, namely the difficulty of keeping up with advances in computer technology as a medium for supporting the learning of ABK students. Based on these problems, this community service aims to introduce ABK students to operating computers and teach them how to use Microsoft Word features that can be used to learn typing and others. The method used is hands-on training on basic introduction to computers and Microsoft Word applications. Of the 26 students with special needs at HS Lantaburo who were given the opportunity by the teacher to take part in the training, there were 3 students namely Autism, Dyslexia, and Down Syndrome (DS) due to limited computer equipment and training time. The context of the training is based on the participant's ability to answer every question posed in the training, starting from managing text, fonts, data storage, etc. Meanwhile, making tables still requires frequent practice. The results of the training were that Autism and Dyslexia student participants had the same range of intelligence so they could follow the training well compared to DS participants. This can be seen from the results of the evaluation carried out after the training activities. ABK students can improve their ability to operate computer equipment and Microsoft Word software, including the ability to type, edit, and format documents. Increase motivation to study, more confidence and independent in operating computers and MS Word applications.
Pembelajaran Algoritma Naïve Bayes dan Apriori untuk Siswa SMK Media Informatika Jakarta Gunawan, Wawan; Hasanudin, Muhaimin; Ridwan, Wawan
Kapas: Kumpulan Artikel Pengabdian Masyarakat Vol 3, No 1 (2024)
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/ks.v3i1.2941

Abstract

Tujuan dari kegiatan pembelajaran ini untuk memperkenaklan pelajar SMK terhadap ilmu data sains yang saat ini sedang berkembang pesat. Masalah prioritas yang diatasi dalam kegiatan pengabdian kepada masyarakat ini adalah memberikan pengetahuan tambahan bagi siswa SMK Informatika Media mengenai algoritma ilmu data, mengingat siswa sangat membutuhkan pengetahuan tambahan tentang algoritma ilmu data. Kegiatan ini akan dibagi menjadi dua tahap: a) tahap pertama adalah pemberian materi oleh narasumber mengenai apa itu algoritma ilmu data dan penggunaan algoritma Naïve Bayes dan Apriori beserta kelebihan dan kekurangan penggunaannya; b) tahap kedua adalah sesi tanya jawab terkait ilmu data dan penggunaan algoritma ilmu data dalam mengklasifikasi dan mengelompokkan produk untuk penjualan. Sebanyak 86,67% peserta memberikan umpan balik positif terhadap pelatihan data sains dalam PKM, dan 73,33% responden memberikan penilaian sangat bagus. 48,28% peserta mengharapkan kegiatan ini diadakan lagi sesering mungkin dengan materi yang kekinian. 83,33% peserta yang menyatakan bahwa mereka belum pernah menggunakan algoritma yang digunakan untuk klasifikasi dan proses bundling produk dalam penjualan.
Budidaya Ikan Lele Dengan Metode Recirculating Aquaculture System Dipesantren Madarijul Mubtadien Untuk Mewujudkan Kemandirian Ekonomi Rusjdi, Halim; Putra, Rizki Pratama; Hendri, Hendri; Sulistyo, Eko; Wahyuningsih, Utami; Sany, Nasril; Alfalah, Win; Emilia, Emilia; Hasanudin, Muhaimin
Jurnal Pengabdian Sosial Vol. 1 No. 10 (2024): Agustus
Publisher : PT. Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/pfy4ra53

Abstract

Kemandirian ekonomi pesantren merupakan hal yang penting untuk diwujudkan agar pesantren dapat independent dalam menjalankan fungsinya sebagai tempat Pendidikan, dakwah dan pemberdayaan masyarakat. Untuk mewujudkan hal tersebut maka dalam program pengabdian ini kami membuat suatu unit usaha budidaya ikan lele menggunakan sistem Recirculating Aquaculture System untuk meningkatkan kualitas hidup dan mempercepat proses pembesaran ikan lele di pondok pesantren Madarijul Mubtadien. Tujuan yang hendak dicapai adalah mewujudkan suatu sitem budidaya ikan lele dengan metode RAS dan kontrol otomatis berbasis IoT. Untuk merealisasikan tujuan tersebut maka beberapa tahap dilakukan yakni dengan melakukan survey lokasi dan juga pangsa pasar ikan lele di lokasi tersebut. Pada sistem kolam RAS, untuk memudahkan operasional budidaya makan dibuat suatu sistem otomasi berbasis IoT dengan penjadwalan sirkulasi air dan kontrol dari jarak jauh melalui internet. Adapun hasil yang diperoleh dari kegiatan ini adalah program budidaya ikan lele dapat berjalan dengan baik sehingga dapat membantu pesantren untuk memulai bisnis budidaya ikan lele yang akan membantu mewujudkan kemandirian ekonomi pesantren. Selain itu penyuluhan Teknik budidaya dan perawatan kolam memberikan keterampilan bagi pengurus pesantren dan juga santri sehingga nantinya menjadi bekal pasca pendidikan pesantren untuk berkontribusi di masyarakat.
Pelatihan Datascience pada Pra-Pemrosesan Data untuk Siswa SMK Media Informatika - Jakarta Hasanudin, Muhaimin; Dwiasnati, Saruni; Gunawan, Wawan
Jurnal Pengabdian Pada Masyarakat Vol 9 No 4 (2024): Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Mathla'ul Anwar Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30653/jppm.v9i4.921

Abstract

Pengabdian Kepada Masyarakat (PKM) merupakan upaya untuk melengkapi siswa dengan keterampilan yang relevan dalam teknologi informasi. Meskipun kurikulum perguruan tinggi telah menekankan pada teknologi dan ilmu komputer, kurangnya pemahaman tentang data science dan pra-pemrosesan data masih menjadi masalah. PKM ini tidak hanya mengajarkan penggunaan alat seperti Python tetapi juga mendorong pemikiran analitis dan kritis saat menganalisis data. Proses pra-pemrosesan data, termasuk normalisasi dan penanganan outlier, berdampak langsung pada input data model machine learning. PKM berfokus pada pelatihan siswa SMK Media Informatika dalam machine learning dan eksplorasi perubahan pada data masukan untuk mempengaruhi akurasi model, melalui serangkaian eksperimen menggunakan berbagai jenis dataset, program ini menganalisis bagaimana modifikasi pada data dapat mempengaruhi performa model pembelajaran mesin. Tujuan PKM adalah meningkatkan pemahaman siswa tentang pentingnya pra-pemrosesan data dalam mencapai model machine learning yang akurat. Evaluasi keberhasilan PKM melibatkan peningkatan pemahaman siswa, pengembangan keterampilan praktis, dan umpan balik positif. Pelatihan PKM berhasil meningkatkan pemahaman peserta dengan jumlah yang tidak mengerti berkurang dari 3,3% menjadi 0% setelah post-test. Persentase peserta yang mengerti materi meningkat dari 46,7% menjadi 60%. Community service is an effort to equip students with relevant skills in information technology. Although the college curriculum has emphasized technology and computer science, the lack of understanding of data science and data Pre-Processing is still an issue. Community service not only teaches the use of tools such as Python but also encourages analytical and critical thinking when analyzing data. Data Pre-Processing, including normalization and outlier handling, has a direct impact on the input data of machine learning models. The Community Service focuses on training SMK Media Informatika students in machine learning and exploring changes to the input data to affect model accuracy. Through a series of experiments with varied datasets, the Community Service analyzes the effect of changes to the data on model performance. The aim of the project was to improve students understanding of the importance of data Pre-Processing in achieving accurate machine learning models. The project's success was evaluated based on increased student understanding, practical skill development, and positive feedback. PKM training succeeded in improving participants' understanding with the number of those who did not understand decreasing from 3.3% to 0% after the post-test. The percentage of participants who understood the material increased from 46.7% to 60%.
Improving Inclusive Students Competence through 3D Flashcard Animation-Based Animal Exploration Hasanudin, Muhaimin; Riskinanti, Karisma; Santoso, Hadi; Novrizal, Kevin; Lestari, Mulyati; Afiyati, Afiyati
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 9 No 1 (2025): May 2025
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/engagement.v9i1.1817

Abstract

Children with special needs often face challenges in recognizing animal shapes and sounds. This community service program (PKM), based on the Service Learning approach, developed an application called Teh Melati, which utilizes Augmented Reality (AR) by combining 3D animation with traditional 2D flashcards to aid in animal recognition. The PKM was conducted over one day with 32 students with disabilities aged 6–14 years (N=32) at HS-Lantaburo. The Service Learning methodology involved actively engaging the community (teachers, parents, and students) in the design, implementation, and evaluation of the learning intervention. Students participated in an interactive animal exploration game that focused on animal images and sounds. Pre-intervention test scores averaged 63.75, while post-intervention scores increased to 81.25. A total of 25 students (78% of the participants) showed significant improvement. The active participation of teachers and parents in hands-on workshops further extended the impact of the intervention. These results demonstrate that learning gaps in special needs education can be addressed through community involvement and the integration of 3D flashcard animation technology, with Service Learning serving as an effective framework for creating meaningful educational experiences for both the students and the community.
Studi Sentimen Masyarakat Terhadap Layanan FLIX Cinemas di Twitter dengan Pendekatan Naïve Bayes dan SVM Ridlan, Ahmad; Latumaerissa, Daniel Eliazar; Hasanudin, Muhaimin; Derisma, Derisma; Fadli, Muhamad
Journal Computer Science and Information Systems : J-Cosys Vol 5, No 1 (2025): Maret
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53514/jco.v5i1.631

Abstract

Penelitian ini melakukan analisis sentimen opini publik terhadap FLIX Cinemas dengan platform Twitter menggunakan metode Naïve Bayes dan Support Vector Machine (SVM). Tujuan utama dari penelitian adalah klasifikasi sentimen yang akurat - baik positif maupun negatif terkait layanan FLIX untuk memperoleh denyut respons publik terhadap layanan. Metodologi yang digunakan adalah pengumpulan twitter, praproses, pelabelan manual dan otomatis, pelabelan yang dibobot dengan TF-IDF. Klasifikasi menggunakan Naïve Bayes dan SVM dengan tiga skenario berbagi data pada 90:10, 80:20, dan 70:30. Hasilnya menyatakan bahwa SVM memiliki akurasi maksimum sebesar 92% untuk pelabelan otomatis dan Naïve Bayes sebesar 87% dalam pelabelan manual. Dari hasil penelitian ini menyatakan bahwa SVM lebih efektif untuk dataset besar sedangkan Naïve Bayes berlaku untuk data kecil sehingga dapat menjadi salah satu acuan bagi FLIX dalam upayanya meningkatkan pelayanan sesuai dengan hasil analisis sentimen
PENERAPAN APLIKASI TRELLO SEBAGAI ALAT BANTU MANAJEMEN PEMBELAJARAN BERBASIS PROYEK UNTUK GURU DI SMAN 85 Wulandari Sari, Dwi; Gusti Ayu, Kurnia; Hasanudin, Muhaimin; Wahab, Abdi
Mejuajua: Jurnal Pengabdian pada Masyarakat Vol. 5 No. 1 (2025): Agustus 2025
Publisher : Yayasan Penelitian dan Inovasi Sumatera (YPIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/mejuajuajabdimas.v5i1.245

Abstract

SMAN 85 terletak di Srengseng, Kecamatan Kembangan, merupakan lembaga pendidikan dengan jumlah siswa yang cukup banyak dan memiliki berbagai jurusan. Dengan didukung oleh sekitar 15 orang guru, SMA Negeri ini menerapkan kurikulum yang berlaku di Indonesia, yaitu kurikulum berbasis proyek. Untuk mendukung pembelajaran berbasis proyek, para guru di SMAN 85 perlu dibekali teknologi yang nantinya mendukung dalam Pendidikan abad ke-21 yang menekankan pada keterampilan kolaborasi, komunikasi dan literasi digital. Permasalahan: Hal utama yang dijadikan permasalahan di mitra adalah a) Sulitnya mengorganisasi tugas, kurangnya kolaborasi antar siswa, dan minimnya keterlacakan progres b) Kurangnya pengalaman belajar yang lebih terstruktur dan relevan dengan kebutuhan industri modern c) Belum adanya fasilitas kolaborasi antar siswa dan guru dalam pengelolaan tugas proyek. Solusi:  a) Memberikan pengalaman dengan mengenalkan teknologi untuk meningkatkan efisiensi manajemen pembelajaran berbasis proyek. b) Mengadakan pelatihan dan pendampingan penggunan aplikasi Trello yang menawarkan visualisasi tugas yang jelas, kemudahan kolaborasi, serta alat pelacakan progres yang efektif. Target capaian luaran adalah peningkatan pemahaman dan keterampilan para guru SMAN 85. Hasil dari kegiatan pengabdian Masyarakat yang telah dilakukan, para guru di SMAN 85 berdasarkan dari hasil pretest dan posttest menunjukkan peningkatan kemampuan dan keterampilan sebesar 88%. Untuk menjamin keberhasilan program pengmas maka akan dilakukan evaluasi saat pengmas dilaksanakan dan pemantauan penggunaan aplikasi selepas pelatihan pengmas dilakukan. Sehingga, kegiatan pengmas akan terus berkelanjutan.
Prediction of Student Major Selection at High School Using a Machine Learning Approach Sany, Nasril; Dody, Dody; Muchlis, Esa Firmansyah; Hasanudin, Muhaimin; Berlinton, Budi
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 4 No. 1 (2025): March 2025
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v4i1.4983

Abstract

The primary objective of this research was to develop and evaluate a machine learning prediction system that matches Senior High School (SMA) Nusa Putra Kota Tangerang students with their potential school majors based on their academic interests and performance levels. This research method employs machine learning algorithms, including Random Forest, Support Vector Machine (SVM), logistic regression, K-Nearest Neighbor (K-NN), and Naive Bayes, using academic records, interest tests, and questionnaires for data collection. The data was processed and analyzed to train and test the algorithm. The findings of this study indicate that the Random Forest algorithm achieved the best performance among the models, with an accuracy of 85%, a precision of 82%, a recall of 88%, and an AUC score of 0.92. The factors that affected the prediction of major selection were Grade XII Mathematics scores and Science Interest Test results. The research implications suggest that Random Forest technology within Machine Learning (ML) enhances major selection accuracy while promoting fairness, providing superior educational choices and increased student satisfaction. Future studies should investigate additional factors that influence this phenomenon.
Enhanced Violence Detection in CCTV Using LSTM Hasanudin, Muhaimin; Santoso, Hadi; Wahab, Abdi; Indrianto, Indrianto; Kuswardani, Dwina; Ridlan, Ahmad
ILKOM Jurnal Ilmiah Vol 17, No 2 (2025)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v17i2.2318.196-202

Abstract

Violence detection in CCTV footage remains a critical challenge for public safety, necessitating automated solutions to overcome human monitoring limitations. This study proposes an LSTM-based framework to improve detection accuracy by analyzing temporal patterns in surveillance videos. Using a dataset of 2,000 videos (1,000 violent/1,000 non-violent), the model extracts spatial-temporal features via optical flow and achieves 93% training accuracy and 91% test accuracy, with a precision of 92% and AUC of 0.94. Results demonstrate significant improvements over traditional methods, particularly in dynamic scenarios, though performance dips for occluded actions or weapon-related violence. The discussion highlights the model’s real-time applicability, computational efficiency (120 ms latency per segment), and alignment with smart city surveillance needs. Limitations include dataset diversity and environmental variability, suggesting future directions in multi-modal data fusion and edge computing. This research advances AI-powered security systems, offering a robust tool for proactive threat detection while underscoring the need for scalable, context-aware solutions.
Deep Learning-Based Autism Detection Using Facial Images and EfficientNet-B3 Hasanudin, Muhaimin; Afiyati, Afiyati; Budiarto, Rahmat; Wahab, Abdi; Jokonowo, Bambang; Indrianto, Indrianto; Yosrita, Efy; Hanifah, Nurul Afif
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 1 (2026): JUTIF Volume 7, Number 1, February 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.1.4574

Abstract

This study presents a novel deep learning approach for early detection of Autism Spectrum Disorder (ASD) using facial image analysis. Leveraging the EfficientNet-B3 model, the research addresses limitations in traditional diagnostic methods by autonomously extracting discriminative facial features associated with ASD. A balanced dataset of 2,940 facial images (1,470 autistic and 1,470 non-autistic children) from Kaggle was pre-processed to 200x200 pixels and evaluated under three dataset-splitting scenarios (80:10:10, 70:15:15, and 60:20:20) to assess generalisability. The model, trained with the Adam optimiser over 10 epochs, achieved optimal performance in the 80:10:10 scenario, with 84.67% precision, 84.35% recall, and 84.32% F1 score. Results demonstrate high confidence (>90% probability) in distinguishing autistic from non-autistic individuals on unseen data. The study underscores the potential of integrating deep learning into clinical decision-support systems for ASD detection, offering a robust, scalable, and efficient solution to improve diagnostic accuracy and reduce reliance on manual methods.
Co-Authors AA Sudharmawan, AA Abdi Wahab Afiyati, Afiyati Alfalah, Win Bambang Jokonowo Berlinton, Budi Dody, Dody Dwi Wulandari Sari Dwina Kuswardani, Dwina Efy Yosrita, Efy Emilia Emilia Hadi Santoso Hanifah, Nurul Afif Hendri Hendri Ifan Prihandi Indrianto Indrianto Karisma Riskinanti Kurnia Gusti Ayu Latumaerissa, Daniel Eliazar Lestari, Mulyati Muchlis, Esa Firmansyah Muhamad Fadli Muhammad Rifqi Nasril Sany Novrizal, Kevin Putra, Rizki Pratama Rahmat Budiarto Ridlan, Ahmad Rusjdi, Halim Saruni Dwiasnati Utami Wahyuningsih Wawan Gunawan Wawan Ridwan