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All Journal Techno.Com: Jurnal Teknologi Informasi Syntax Jurnal Informatika Telematika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Mantik Penusa IJISTECH (International Journal Of Information System & Technology) Jurnal Riset Informatika ENGLISH EDUCATION: JOURNAL OF ENGLISH TEACHING AND RESEARCH TRIDARMA: Pengabdian Kepada Masyarakat (PkM) Jurnal Tunas Jurnal Pengabdian kepada Masyarakat Nusantara IJISTECH International Journal of Social and Management Studies (IJOSMAS) J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Abdimas Ekonomi dan Bisnis Jurnal Abdi Masyarakat Multidisiplin Vertex Jurnal Pengabdian Masyarakat dan Riset Pendidikan Prawara Jurnal Pengabdian Masyarakat
Enok Tuti Alawiah
Universitas Bina Sarana Informatika
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Pelatihan Implementasi Pendaftaran Peserta Didik Baru Pada Yayasan Pendidikan Islam Purnama Cendekia Yunandar, Rahmat Tri; Alawiah, Enok Tuti; Apriyani, Helina; Sulistia, Viki
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 7 No. 1 (2026): Edisi Januari - April
Publisher : Lembaga Dongan Dosen

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

Abstract

Pengabdian kepada masyarakat merupakan salah satu kewajiban dosen dalam melaksanakan Tridharma Perguruan Tinggi, yaitu dengan berbagi ilmu pengetahuan dan keterampilan kepada masyarakat yang membutuhkan. Mitra dalam kegiatan ini adalah Yayasan Purnama Insan Cendekia yang menghadapi permasalahan pada sistem informasi pendaftaran peserta didik. Proses pendaftaran yang masih dilakukan secara manual sering menimbulkan kesalahan dalam pengolahan data siswa baru, sehingga menghambat efektivitas manajemen administrasi. Selain itu, yayasan belum memiliki website yang dapat berfungsi sebagai media informasi dan portofolio lembaga untuk mempermudah masyarakat dalam memperoleh informasi secara cepat dan efisien. Berdasarkan permasalahan tersebut, kegiatan pengabdian ini dilaksanakan dengan tujuan memberikan pelatihan serta implementasi sistem informasi pendaftaran peserta didik berbasis web yang dapat digunakan secara berkelanjutan. Dengan adanya sistem ini, diharapkan yayasan mampu meningkatkan kinerja organisasi, transparansi informasi, serta kualitas layanan pendidikan. Kegiatan dilaksanakan secara tatap muka di Aula Yayasan Purnama Insan Cendekia, Kalideres, Jakarta Barat, dengan target luaran berupa publikasi hasil kegiatan pada media elektronik maupun cetak berskala nasional.
Artificial Intelligence in Decision Support Systems for Job Promotions Enok Tuti Alawiah; Sunarti Sunarti
Telematika Vol 18, No 2: August (2025)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v18i2.3169

Abstract

Educational Personnel have an important role in supporting the success of education. Educational Personnel have a role in carrying out administration, management, development, supervision, and technical services to support the educational process in educational units. The declining performance of education personnel at the junior high school level in West Jakarta, particularly due to the ineffectiveness of the promotion system, demonstrates the need for an objective, data-driven assessment mechanism. Education personnel play a crucial role in the administration, management, and technical services of education, thus a transparent promotion system is essential. This study aims to develop a promotion recommendation model using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method integrated with artificial intelligence (AI) to improve the accuracy, objectivity, and efficiency of the decision-making process. The study involved 112 civil servant education personnel respondents from 53 junior high schools in eight sub-districts in West Jakarta, selected through multistage random sampling. Analysis was conducted using five main criteria: educational background, performance, technical skills, length of service, and work motivation. AI was used to automate normalization, weighting, and pattern analysis. The results showed that TOPSIS was able to produce an objective candidate ranking, with respondent R099 having the highest Closeness Coefficient (≈0.7704), making him the most suitable for promotion. The integration of TOPSIS and AI has been proven to increase analysis speed, reduce human bias, and provide more consistent and accurate recommendations for education staff promotion.
Decision Support System for Provision of Natural Disaster Victim Logistic Assistance with TOPSIS Method Enok Tuti Alawiah; Sefrika Sefrika
Jurnal Riset Informatika Vol. 2 No. 2 (2020): March 2020 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v2i2.43

Abstract

At the beginning of 2020, a natural disaster caused many people to lose their homes, damage to public facilities and infrastructure, and the breakdown of transportation links connecting villagers, especially in 3 districts, namely Sukajaya, Nanggung, and Cigudeg. As a result of the disaster, many villages are isolated, and residents need a lot of logistical support to meet their needs. To overcome these problems, we need a system that can help the government and volunteers interested in the decision-making process so that assistance for victims of natural disasters can be right on target and by the urgency of basic needs and logistics needed. Decision support systems using the TOPSIS method are used to solve multicriteria problems by offering various alternative solutions to solve problems. The results obtained a final preference value of 0.68 from C3 criteria to prioritize residents with closed transportation access to channel disaster relief funds for victims of natural disasters in Bogor Regency.
Analysis of the Impact of Backpropagation Hyperparameter Optimization on Heart Disease Prediction Models Nita Syahputri; Putrama Alkhairi; Enok Tuti Alawiah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6473

Abstract

Heart disease is a major global health issue, highlighting the need for early and accurate prediction to reduce complications and improve patient outcomes. The Backpropagation Neural Network (BPNN) is a widely used method for heart disease prediction, but its performance relies heavily on proper hyperparameter selection, including neuron count, activation function, optimizer, and batch size. This study analyzed the impact of hyperparameter optimization on BPNN performance. A standard BPNN model was compared with an optimized version, where key hyperparameters were fine-tuned to enhance predictive accuracy and stability. Both models were trained and tested on the same dataset, and their performance was evaluated using Accuracy, Precision, Recall, Mean Squared Error (MSE), and Mean Absolute Error (MAE). The results show that the optimized model achieves a slightly better accuracy (99.11% vs. 99.09%) and lower error rates (MSE and MAE of 0.0089 vs. 0.0091). It also demonstrates higher precision, reflecting an improved capability in correctly identifying heart disease cases. Although the performance gap was small, the optimized model showed a more balanced and consistent outcome. These findings highlight the importance of hyperparameter tuning for improving neural network models for medical prediction. This study contributes to the development of more accurate and reliable AI tools for the early diagnosis of heart disease. Future studies may apply advanced optimization techniques, such as Bayesian Optimization or Genetic Algorithms, and use larger and more diverse datasets to enhance model generalization.
Co-Authors A Apriyanto Apriyanto, A dewi, tati mar Dicky Hariyanto Dicky Haryanto Dini Setyorini Dinin Setyorini Dwi Andini Putri Embun Fajar Wati Hari Gursida Hari Muharam Haryanto, Dicky Hasanudin Hasanudin Hasanudin Helina Apriyani Helina Apriyani Apriyani Herlin Widasiwi Setianingrum Isnurrini Hidayat Susilowati Isnurrini hidayat, Isnurrini Lydia Salvina Helling Martinus Tukiran Martua Hami Siregar Martua Hami Siregar Nita Syahputri Omar Pahlevi Putrama Alkhairi Rahmat Tri Yunandar Ririn Restu Aria S Sefrika Sefrika Sefrika sefrika sefrika Sefrika Sefrika Setyorin, Dini Sulistia, Viki Sunarti Sunarti Sunarti Susi Susilowati Taupiqurahman Taupiqurahman Tuslaela Widasiwi, Herlin Wiwik Widiyanti, Wiwik