Article Per Year (5 Year)
p-Index From 2021 - 2026
3.757
P-Index
This Author published in this journals
All Journal Syntax Jurnal Informatika Jurnal TAM (Technology Acceptance Model) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Aisyah Journal of Informatics and Electrical Engineering Journal of Information Systems and Informatics SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Jurnal Pengabdian Kepada Masyarakat Ungu ( Abdi Ke Ungu) Yumary: Jurnal Pengabdian kepada Masyarakat Jurnal Abdimas Bina Bangsa Jurnal Maternitas Aisyah (JAMAN AISYAH) Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal Algoritma Jurnal Informatika Polinema (JIP) Jurnal Rekayasa Perangkat Lunak Jurnal TAM (Technology Acceptance Model)
Zulkifli
Prodi Sistem Informasi STMIK Pringsewu, Lampung
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Public Health Social Sciences Other

Published : 35 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 35 Documents
Search

 1   2   3   4 
Agile-Scrum Methodology for Hospital Information System Development Zulkifli, Zulkifli; Ratnasari, Ratnasari; Arifin, Yulyani; Habib, Cahya
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1148

Abstract

Hospitals face significant challenges in managing large and complex data, and Hospital Information Systems (SIRS) are essential for supporting hospital operations. However, many SIRS projects experience delays and failures due to rigid development approaches. Agile-Scrum is proposed as a more flexible and adaptive solution, emphasizing collaboration and iterative processes to enhance the quality of healthcare services. This qualitative case study, conducted in a hospital with an internal development team, used observations, document analysis, and semi-structured interviews with 10 participants, including developers, a Scrum Master, and key hospital stakeholders. The findings indicate that implementing Agile-Scrum led to a 35% increase in team collaboration, a 40% improvement in responsiveness to changing requirements, and a 30% boost in overall project efficiency. The study highlights the effectiveness of Agile-Scrum in managing the complexities of SIRS development, especially through backlog organization, sprint planning, and stakeholder feedback. The study suggests further research to assess the long-term impact of Agile-Scrum in other information system development contexts.
Technical Guidance on Attendance List Management Applications and Updating SIASN Data for Civil Servant Lecturers Zulkifli, Zulkifli; Bintoro, Panji; Yana Ayu Andini, Dwi; Eko Setiawan, Agustinus; Herdia Andika, Tahta; Ardhy, Ferly
SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Vol. 6 No. 1 (2025)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/spekta.v6i1.11013

Abstract

Background: The implementation of the AMANDA (Attendance Management and SIASN Data Updating Application) has significantly improved educational administration, especially for civil servant lecturers. Contribution: AMANDA serves as a model for future public sector innovations, improving efficiency, accountability, and adaptability. Method: The background to the development of this application comes from challenges in manual processes which tend to be time consuming, prone to errors, and less efficient in terms of data processing. Results: It has reduced time spent on administrative tasks by 30% and decreased errors by 25%, enhancing accuracy and efficiency. User feedback has been positive, with 85% of lecturer satisfied, highlighting its ease of use. Conclusion: The application has also demonstrated the power of digital tools to streamline operations, improve data integrity, and promote user engagement. Furthermore, user satisfaction and training outcomes suggest that continued investment in technology and training is essential for optimizing administrative processes.
Pengembangan Chatbot AI untuk Informasi Pendaftaran Mahasiswa Baru di FTI UAP Habib, Cahya; Zulkifli, Zulkifli; Aminudin, Nur; Ayu Andini, Dwi Yana
Jurnal Rekayasa Perangkat Lunak Vol. 4 No. 2 (2025): Jurnal Rekayasa Perangkat Lunak (J-Rapa)
Publisher : Universitas Aisyah Pringsewu

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

Abstract

Penelitian ini mengembangkan chatbot berbasis kecerdasan buatan (AI) bernama Asvira untuk menyediakan informasi pendaftaran mahasiswa baru di Fakultas Teknologi dan Informatika Universitas Aisyah Pringsewu (FTI UAP). Sistem ini dirancang untuk menjawab pertanyaan umum seperti jadwal pendaftaran, persyaratan, biaya kuliah, dan fasilitas kampus secara otomatis dan real-time, menggantikan sistem konvensional yang mengandalkan staf administrasi. Asvira dibangun menggunakan framework Laravel untuk backend, Blade dan Tailwind CSS untuk antarmuka, serta OpenAI GPT-4.1 API sebagai mesin pemroses bahasa alami. Basis pengetahuan disusun dalam format JSON dari sumber resmi universitas. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan pendekatan prototipe dan evaluasi kualitatif melalui umpan balik pengguna. Hasil pengujian menunjukkan Asvira mampu memberikan respons yang akurat dan cepat dengan antarmuka yang responsif. Evaluasi pengguna juga menunjukkan sistem ini mudah digunakan dan meningkatkan efisiensi layanan informasi pendaftaran. Sistem ini diharapkan mengurangi beban kerja staf dan menjadi model untuk chatbot serupa di layanan akademik lainnya.
A Multi-Algorithm Approach for Predicting OSCE Exam Passing Status Zulkifli; Panji Bintoro; Fitriana; Muhammad Galih Ramaputra; Hafsah Mukaromah
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1518

Abstract

This study provides a paradigm for using a digital decision support system to automate OSCE evaluation. The effectiveness of this model is restricted to the scope of small-scale data and particular educational situations at Aisyah University, despite the results demonstrating great accuracy. As a result, additional modifications are needed for its practical implementation at other institutions. However, this research provides a crucial basis for the creation of digital assessment systems that might assist teachers in identifying students who want extra aid prior to final exams. Five machine learning algorithms Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), Naive Bayes (NB), and K-Nearest Neighbors (kNN) are assessed experimentally in this study. A dataset of 439 clinical competency data from Aisyah Pringsewu University midwifery students was used to create the model. Eight clinical skill factors were used as input, including baby massage, newborn care, and family planning services. To guarantee result stability, the 5-fold cross-validation approach was used for model validation. According to the test findings, every algorithm performs well, with an accuracy of more than 90%. On this particular dataset, SVM achieved a 100% classification accuracy, whereas Random Forest and SVM showed the most efficacy. With an average validation accuracy of 95%, neural networks also demonstrated excellent performance. This study provides a paradigm for using a digital decision support system to automate OSCE evaluation. The effectiveness of this model is restricted to the scope of small-scale data and particular educational situations at Aisyah University, despite the results demonstrating great accuracy. As a result, additional modifications are needed for its practical implementation at other institutions. However, this research provides a crucial basis for the creation of digital assessment systems that might assist teachers in identifying students who want extra aid prior to final exams.
Development and Evaluation of a Multi-Algorithm Application for Predicting Breast Cancer Patient Survival Zulkifli; Kraugusteeliana; Sukarni; Ikna Awaliyani; Nur Asini; Fitriana
Journal of Information System and Informatics Vol 8 No 3 (2026): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i3.1665

Abstract

This study developed a multi-algorithm machine learning prototype for multiclass breast cancer survival prediction using 1,980 patient records, classifying patients as Living, Died of Disease, or Died of Other Causes. The framework integrated NN, SVM, RF, NB, and KNN algorithms within a decision-support monitoring application, with preprocessing steps including data cleaning, normalization, feature preparation, and dataset partitioning. To prevent target leakage, survival-related variables were excluded from the predictor set. The revised evaluation results indicated that NB and KNN delivered the strongest performance, achieving weighted average F1-scores of 0.93 and 0.92, respectively, while NN and RF showed comparatively lower results. These findings highlight the potential of machine learning for breast cancer survival status monitoring, although the proposed system is designed as a decision-support prototype rather than a clinical diagnostic tool. Therefore, before actual healthcare deployment, more research incorporating explainable AI techniques, external validation, and real-world clinical testing is needed.
Co-Authors Abdullah Abdullah Adi Prasetia Nanda Agus Wantoro Ahmad Ahlun Nazar Andika, Tahta Herdian Andino Maseleno Ani Kristianingsih Aras, Irsan Arifin, Yulyani Aviv Fitria Yulia Ayu Andini, Dwi Yana Azri Afdhalluddin Bintoro, Panji Candra Irawati Desni Sagita, Yona Dwi Feriyanto Dwi Yana Ayu Andini Eko Setiawan, Agustinus El Hanif, Azka Fadzlan Thoriq Fadzlan Thoriq Fahlul Rizki Ferly Ardhi Ferly Ardhy Fitra Endi Fernanda, Fitra Endi Fitriana Fitriana Gustianing, Defy Habib, Cahya Hafsah Mukaromah Hany, Hany Zahra Nabbilla Herdia Andika, Tahta Ikna Awaliyani Ilham Ubaidillah Joko Triloka Kraugusteeliana Kraugusteeliana M. Galih Ramaputra M. Islamahdi Muhammad Ahsan Jamal Muhammad Arifin Muhammad Galih Ramaputra Mulyono, Andi Nasrullah Nopi Anggista Putri, Nopi Anggista Nur Aminudin Nur Asini Nurul Isti Fada Ockhy Jey Fhiter Wassalam Pasaribu, Alfredo Ramadhanti, Dinda Ratnasari Ratnasari Rendy Yudha Pratama Rini Wahyuni Salman Alfarisi Salimu Sarifuddin Sarifuddin Septika Yani Veronica Sodikin Sodikin Sukarni Sukarni Sukarni Sunarmi Syazili Mustofa Tahta Herdian Andika Tri Ayu Septiana Yana Ayu Andini, Dwi Yana Ayu, Dwi Yani Veronica, Septika Yona Desni Sagita