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All Journal Communications in Science and Technology Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Aptisi Transactions on Management Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming JURSIMA (Jurnal Sistem Informasi dan Manajemen) ADI Bisnis Digital Interdisiplin (ABDI Jurnal) JPM: JURNAL PENGABDIAN MASYARAKAT Dharma Sevanam : Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi dan Manajemen jabdimasunipem Proletarian : Community Service Development Journal
Hendriyati, Penny
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Pendampingan Testing Aplikasi Pembelajaran Terintegrasi Artificial Intelligence untuk Meningkatkan Keterlibatan Siswa di Kabupaten Tangerang Prihastomo, Yoga; Winanti, Winanti; Prabowo, Yulius Denny; Sidik, Achmad; Hendriyati, Penny; Luthfian, Muhamad; Setiawan, Rizky; Wardiansyah, Wardiansyah; Isbah, Latif Palikal; Chandra, Zaki Ma'rufan
Dharma Sevanam : Jurnal Pengabdian Masyarakat Vol 4 No 2 (2025): Desember 2025
Publisher : IAHN Gde Pudja Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53977/sjpkm.v4i2.3127

Abstract

Problems faced by students in learning include boredom and monotony with conventional learning methods. Some schools have not yet utilized AI technology due to several factors, including the lack of a stable internet connection, teachers' concerns about AI technology causing student dependency, and low literacy regarding AI technology. The purpose of testing this AI-integrated learning application was to ensure that the application could be used by users without any problems. The method used in this activity was a hands-on practice using the Insan AI application by teachers and students. The results of the practice identified several things that needed to be improved, both technically, in terms of feature suitability and application reliability. This activity is expected to help the development team in ensuring that the application has no significant problems and is ready for use by users. It is hoped that this activity will soon be available for use by teachers and students in Tangerang Regency
Kegiatan Evaluasi Development Sistem Pembelajaran Terintegrasi Artificial Intelligent Untuk Meningkatkan Keterlibatan Siswa dalam Belajar Winanti, Winanti; Prihastomo, Yoga; Prabowo, Yulius Denny; Sidik, Achmad; Hendriyati, Penny; Luthfian, Muhammad; Setiawan, Rizky; Wardiansyah, Wardiansyah; Isbah, Latif Palikal; Budiadyana, Gusti Nyoman
Proletarian : Community Service Development Journal Vol 3 No 2 (2025): November 2025
Publisher : PT. BERBAGI TEKNOLOGI SEMESTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61098/proletariancomdev.v3i2.271

Abstract

Kegiatan ini dilakukan sebagai tindak lanjut dari kegiatan sebelumnya yaitu kegiatan Focus Group Discussion (FGD) dan tindak lanjut rancang bangun aplikasi pembelajaran berbasis Artificial Intelligent (AI) untuk mendukung pembelajaran berkelanjutan. Kegiatan ini bertujuan untuk mengetahui progress pembuatan platform pembelajaran berbasis AI yang akan diimplementasikan pada sekolah yang ada di Kabupaten Tangerang. Metode yang digunakan adalah diskusi secara interaktif antara peserta sehingga dihasilkan sebuah kesimpulan yang tertuang dalam notulen rapat hasil evaluasi. Peserta sebanyak 6 orang yang terdiri dari ketua tim, dan anggota baik dari dosen maupun dari mahasiswa. Kegiatan berlangsung satu hari dan berjalan dengan lancar dengan hasil yang telah disepakati bersama bahwa ada perubahan atau perbaikan pada fitur perpustakaan diganti dengan materi pembelajaran, fitur komunitas akan direvisi menjadi group atau kelompok belajar. Setelah semua fitur disesuaikan maka langkah selanjutnya akan dilakukan ujicoba sistem yang melibatkan user secara langsung yaitu guru, operator sekolah dan siswa. Harapannya dengan adanya evaluasi ini dapat dihasilkan platform pembelajaran yang telah tervalidasi sesuai dengan kebutuhan user dan dapat digunakan secara maksimal oleh user
Progres Keberlanjutan Perancangan Platform Pembelajaran Adaptif berbasis Artificial Intelligence melalui Monitoring dan Evaluasi Internal Prihastomo, Yoga; Winanti, Winanti; Prabowo, Yulius Denny; Sidik, Achmad; Hendriyati, Penny; Luthfian, Muhamad; Setiawan, Rizky; Wardiansyah, Wardiansyah; Isbah, Latif Palikal; Chandra, Zaki Ma'rufan; Fernando, Erick
Proletarian : Community Service Development Journal Vol 3 No 2 (2025): November 2025
Publisher : PT. BERBAGI TEKNOLOGI SEMESTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61098/proletariancomdev.v3i2.297

Abstract

Guna memastikan kegiatan rancang bangun aplikasi telah sesuai dengan usulan / perencanana awal baik dari segi, proses, tema dan luaran yang dihasilkan maka perlu dilakukan monitoring dan evaluasi (Monev). Monev dilakukan dengan metode tanya jawab secara langsung serta diskusi interaktif antara peserta, ketua LPPM dan reviewer yang telah ditunjuk. Hasil monev berupa laporan mengenai kesesuaian kegiatan dengan usulan awal, ketercapaian luaran wajib, keberlanjutan kegiatan dengan kegiatan tahun berikutnya dan keterserapan anggaran sesuai dengan rencana anggaran belanja (RAB). Semua kriteria dan proses telah dijalankan dengan baik dan rekomendasinya adalah project ini dapat tindaklanjuti untuk kegiatan tahun berikutnya dan anggaran telah terserap dengan baik. Harapan dari kegiatan monev ini adalah ketercapaian luaran yang sesuai dengan perencanaan awal dan keberlanjutan kegiatan berikutnya
Classification of Heart Disorders Using Deep Learning and Machine Learning Approaches Sumiati; Hendriyati, Penny; Dafa, Abdullah Hasan; Yusta, Afrasim; Sianturi, Susy Katarina
Communications in Science and Technology Vol 10 No 2 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.2.2025.1773

Abstract

Heart disorders persist a primary cause of mortality worldwide, underscoring the necessity for precise and effective diagnostic support systems. The objective of this study is to classify heart disorders employing a combination of deep learning and machine learning approaches based upon electrocardiogram (ECG) image data., The model’s performance was evaluated through 5-fold cross-validation per patient to ensure robust generalizability. The dataset comprised 486 ECG images from 284 patients. A total of six models were subjected to comparative analysis, including Support Vector Machine (SVM), VGG16, ResNet50, Custom CNN, Xception, and Inception-V3, by utilizing key evaluation metrics including accuracy, precision, recall, specificity, F1-score, and AUC-ROC. The experimental results demonstrated that Inception-V3 achieved the optimal overall performance, demonstrating a balance between sensitivity and precision. Furthermore, deep learning models generally outperformed traditional methods such as support vector machines (SVM). The mean performance across all models yielded an accuracy of approximately 78.6% and an AUC-ROC of 0.83, demonstrating reliable discrimination in cardiac disorder classification. Deep learning-based architectures, particularly Inception-V3 and Xception, demonstrated considerable potential in the development of automated and accurate diagnostic systems for the early detection of cardiac disorders. Future research could explore hybrid approaches and larger and more diverse datasets to enhance clinical applicability. This study provides improved accuracy and reliability in cardiac disorder classification by leveraging and comparing machine learning and deep learning approaches. The proposed model has been demonstrated to effectively capture complex patterns in medical data, thereby supporting early diagnosis and improving clinical decision-making.
AM Design of E-Budget with SAP Integration Using the Design Thinking Method for Budget Management Optimization at PT. Krakatau Steel Megayanti, Anita; Ritonga, Roy Amrullah; Gustina; Hendriyati, Penny
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 8 No. 3 (2025): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jtsi.v8i3.48299

Abstract

Integrated budget management is a crucial aspect of enhancing efficiency and accuracy in corporate budget planning and realization. One of the innovations developed to address this need is the E-Budget system, an application designed to automate the processes of budget submission, evaluation, implementation, and monitoring in a more systematic manner. However, the implementation of this system still faces several challenges, such as a time-consuming and error-prone budget data input process, lack of integration with the SAP system, which hampers data processing, and limited access that is only available through the intranet network. Additionally, the lack of transparency in the budget evaluation process also hinders data-driven and more accurate decision-making. To overcome these challenges, the Design Thinking approach is applied in the development of the E-Budget system to better align with user needs. This method enables the design of a more intuitive, flexible, and easily accessible system, thereby improving efficiency in budget management. This study aims to design an E-Budget system integrated with SAP using the Design Thinking method to optimize data collection and enhance user accessibility. The expected outcome of this system development is to simplify the budget data input process at PT. Krakatau Steel, improve the effectiveness of budget planning and supervision, and accelerate real-time data access. With a more transparent and efficient system, the company is expected to optimize financial management.
Co-Authors Ahmad Sofan Ansor Budiadyana, Gusti Nyoman Chandra, Zaki Ma'rufan Dafa, Abdullah Hasan Devi, Putri Ayu Permata Erick Fernando B311087192 Farida Agustin, Farida Gustina Isbah, Latif Palikal Luthfian, Muhamad Luthfian, Muhammad Megayanti, Anita Prabowo, Yulius Prakasa, Weni Adela Aulia Ramadhan, Tarisya Reni Haerani Ritonga, Roy Amrullah Setiawan, Rizky Sidik, Achmad Sumiati Susy Katarina Sianturi Untung Rahardja Wardiansyah Wardiansyah, Wardiansyah WINANTI, WINANTI Yoga Prihastomo Yulius Denny Prabowo, Yulius Denny Yusta, Afrasim Yusuf Yusuf