Garuda - Garba Rujukan Digital

Pelatihan Penggunaan Teknologi Dalam Mengelola Dan Mempromosikan Acara Arwan, Asep; Muhtajuddin Danny; Andriani; Amat Damuri
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 2 No. 1 (2024): Juni 2024
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v2i1.82

Dalam era digital yang semakin maju, penggunaan teknologi menjadi krusial dalam berbagai aspek kehidupan, termasuk dalam pengelolaan dan promosi acara. Pelatihan ini bertujuan untuk membekali peserta dengan pengetahuan dan keterampilan praktis dalam memanfaatkan berbagai alat dan platform teknologi guna meningkatkan efisiensi dan efektivitas manajemen acara serta strategi pemasaran yang lebih luas dan terarah. Materi pelatihan mencakup penggunaan perangkat lunak manajemen acara, teknik pemasaran digital, analitik media sosial, serta pemanfaatan teknologi interaktif untuk meningkatkan keterlibatan peserta. Dengan mengikuti pelatihan ini, peserta diharapkan mampu merancang, mengelola, dan mempromosikan acara dengan lebih profesional dan inovatif, sesuai dengan tuntutan zaman. Studi kasus dan praktik langsung akan menjadi bagian integral dari pelatihan untuk memastikan transfer pengetahuan yang aplikatif dan relevan.

Transformasi Sistem Administrasi Masjid Miftahul Huda Blok E KSB Berbasis Website Effendi, Muhammad Makmun; Rifa’i, Anggi Muhammad; Arwan, Asep; Pradini, Purnama Sakhrial
Jurnal Pelita Pengabdian Vol. 2 No. 2 (2024): Juli 2024
Publisher : DPPM Universitas Pelita Bangsa

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

Masjid merupakan tempat ibadah dan juga kegiataan keagamaan umat Islam, selain itu masjid juga kegiatan sosial. Salah satu masjid yang ada di desa Sukaragam kecamatan Serang Baru kabupaten Bekasi yang tepatnya di Perumahan KSB Blok E memiliki Masjid yang bernama Masjid Miftahul Huda, di dalam menjalankan sistem administrasi masih dengan metode tradisional yaitu menggunakan desktop komputer untuk pengelolaan keuangan dan ketika ada kegiatan keagaamaan masih menggunakan informasi melalui informasi di masjid ataupun di pasang di dinding masjid, sehingga dengan cara tersebut informasi tidak tersampaikan secara menyeluruh, hanya para jamaah yang hadir di masjid saja yang mengetahui kegiatan masjid dan laporan keuangan terkini. Untuk itu maka Masjid Miftahul Huda memerlukan sistem administrasi yang dapat diketahui oleh para jamaah secara luar dari sisi kegiatan keagamaan maupun juga laporan keuangan secara realtime dan juga untuk mencegah terjadinya korupsi keuangan ataupun untuk mengurangi prasangka yang tidak baik terhadap keuangan masjid. Untuk itulah dalam menghadapi era digitalisasi maka Masjid Miftahulhuda melakukan rancang bagun sistem administrasi dalam menghadapi era digitalisasi yaitu membuat rancang bangun sistem informasi masjid berbasis Web sehingga mempermudah jamaah mengetahui secara mudah setiap kegiatan keagamaan di masjid maupun data keuangan secara realtime yang juga didukung dengan database melalui metode Prototyping sehingga pengelolaan data masjid dan keuangan dapat lebih efisien, akurat dan terkoordinir dengan baik.

Design of Mask Detection Application Using Tensorflow Lite based on Android Mobile Effendi, M Makmun; Turmudi, Ahmad; Arwan, Asep
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4329

A mask is a type of personal protective equipment (PPE) that is essential for protecting the nose and mouth from contamination by droplets or airborne particles. The use of masks became highly popular during the Covid-19 pandemic, which began in December 2019 in China and peaked in Indonesia in 2020. Despite the pandemic subsiding and vaccinations increasing immunity, some companies still require masks to prevent the spread of illnesses such as colds and flu, especially in work processes that produce smoke, such as soldering and welding. To ensure employees comply with mask usage, effective supervision is necessary. Manual supervision is less efficient, thus a digital detection method is needed. This study developed a mask detection application using deep learning algorithms and the TensorFlow Lite framework on an Android platform. The application can detect mask usage with 100% accuracy at a distance of 1 to 5 meters. The system was tested under various lighting conditions and environments to ensure reliability. Additionally, the implementation of this technology can be extended to other public areas to ensure compliance with health protocols. This tool helps companies easily monitor and enforce mask-wearing discipline among employees, thereby enhancing workplace safety and health. Future work could explore the integration of this system with other health monitoring tools to create a comprehensive safety solution.

Analisis Sentimen Media Sosial Twitter Terhadap Calon Presiden RI Tahun 2024 Menggunakan Klasifikasi Algoritma Naïve Bayes Effendi, Muhammad Makmun; Zy, Ahmad Turmudi; Arwan, Asep
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5210

The progress of social media is currently being felt by many Indonesian people, one of the social media that is often used is Twitter, which is a media for posting information. Currently the viral post is the election of Presidential Candidates (capres) of the Republic of Indonesia which will be held in 2024, in line with this, the General Election Commission (KPU) is holding a presidential candidate debate which will be held on various television media in Indonesia and from the results of this debate the Indonesian people usually give opinions or comments on the debate from the positive and negative sides of the presidential candidates who appeared at that time, namely Anis, Prabowo and Ganjar Pranowo. To find out the results of sentiment towards the presidential candidates, the researchers carried out an analysis using a classification of tweets containing public sentiment towards the 2024 presidential candidacy, namely Anis, Prabowo and Ganjar with the classification method used in this research is Naive Bayes Classification (NBC). Anies Baswedan dataset 61.35% of Twitter users have negative comments and 39.65% of Twitter users have positive comments, Ganjar Pranowo dataset 59.12% of Twitter users have negative comments and 41.88% of Twitter users have positive comments, Ganjar Prabowo Subianto dataset 49.25% Twitter users commented negatively and 51.75% of Twitter users commented positively. Comparing the results of the three presidential candidates, Anies Baswedan's accuracy value is smaller than the other two candidates because Anies Baswedan has more negative comments than the other two candidates. Anies Baswedan got an accuracy value of 67.23%, Prabowo Subianto 83.42% and Ganjar Pranowo 88.15%. The amount of data affects the results of sentiment analysis, the more data the better the accuracy value obtained.

Design of Mask Detection Application Using Tensorflow Lite based on Android Mobile Effendi, M Makmun; Turmudi, Ahmad; Arwan, Asep
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4329

A mask is a type of personal protective equipment (PPE) that is essential for protecting the nose and mouth from contamination by droplets or airborne particles. The use of masks became highly popular during the Covid-19 pandemic, which began in December 2019 in China and peaked in Indonesia in 2020. Despite the pandemic subsiding and vaccinations increasing immunity, some companies still require masks to prevent the spread of illnesses such as colds and flu, especially in work processes that produce smoke, such as soldering and welding. To ensure employees comply with mask usage, effective supervision is necessary. Manual supervision is less efficient, thus a digital detection method is needed. This study developed a mask detection application using deep learning algorithms and the TensorFlow Lite framework on an Android platform. The application can detect mask usage with 100% accuracy at a distance of 1 to 5 meters. The system was tested under various lighting conditions and environments to ensure reliability. Additionally, the implementation of this technology can be extended to other public areas to ensure compliance with health protocols. This tool helps companies easily monitor and enforce mask-wearing discipline among employees, thereby enhancing workplace safety and health. Future work could explore the integration of this system with other health monitoring tools to create a comprehensive safety solution.

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