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All Journal Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi JURTEKSI Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Media Informatika International Journal of Public Health Excellence (IJPHE) Internet of Things and Artificial Intelligence Journal International Journal of Community Service (IJCS) Jurnal Manajemen Informatika dan Bisnis Digital COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi International Journal of Health, Engineering and Technology Journal of Innovative and Creativity Sevaka: Hasil Kegiatan Layanan Masyarakat Jurnal Pengabdian Pada Masyarakat IPTEKS
Riszki Fadillah
Institut Teknologi Dan Kesehatan Ika Bina
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Implementation of Password Validation using a Combination of Letters, Numbers and Symbols in the New Student Registration Application Sentosa Pohan; Putri Ramadani; Riszki Fadillah; Yusril Iza Mahendra Hasibuan; Baginda Restu Al Ghazali
International Journal of Health Engineering and Technology Vol. 3 No. 1 (2024): IJHET May 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v3i1.282

Abstract

This research aims to evaluate the implementation of password validation using a combination of letters, numbers and symbols in new student registration applications in increasing the level of application security. This research method involves implementing a password validation system with strict criteria, as well as testing password strength using brute force attacks. The test results show that passwords that meet the criteria take time 150 seconds to be broken using brute force, while passwords that only use letters only take time 10 seconds. Surveys of users show that 70% feel comfortable with this validation system, though 40% find it difficult to create a valid password. As much 85% users consider this system to improve application security. This research suggests that new student registration applications adopt a strict password validation system to increase the protection of users' personal data, while providing solutions for users to create more secure passwords.complex but easy to remember. The implementation of this system is expected to strengthen application security and increase user confidence in the protection of their personal data.
Perbandingan Algoritma Naïve Bayes, C4.5, dan K-Nearest Neighbor untuk Klasifikasi Kelayakan Program Keluarga Harapan Ramadani, Putri; Fadillah, Riszki; Adawiyah, Quratih; Suerni, Suerni; Al Ghazali, Baginda Restu
Jurnal Media Informatika Vol. 6 No. 1 (2024): Jurnal Media Informatika Edisi September - Desember
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jumin.v6i1.6083

Abstract

Penelitian ini bertujuan membandingkan kinerja tiga algoritma klasifikasi—Naïve Bayes, C4.5, dan K-Nearest Neighbor (K-NN)—dalam menentukan kelayakan penerima Program Keluarga Harapan (PKH) di Rantau Prapat. Dataset terdiri dari 109 data keluarga dengan variabel seperti pendapatan, jumlah tanggungan, status pekerjaan, dan kepemilikan aset. Pengolahan dan analisis data dilakukan menggunakan RapidMiner Studio, dengan evaluasi kinerja berdasarkan akurasi, presisi, recall, dan Area Under Curve (AUC). Hasil penelitian menunjukkan bahwa algoritma C4.5 memberikan kinerja terbaik dengan akurasi 91,8%, presisi 90,7%, recall 92,3%, dan AUC 0,944. Naïve Bayes mencatat akurasi 87,2% dan recall 88,9%, sedangkan K-NN menghasilkan akurasi 89,9% dan recall 91,1%, namun memerlukan komputasi lebih tinggi. Temuan ini menunjukkan bahwa C4.5 lebih efektif dalam mengklasifikasikan kelayakan penerima PKH secara akurat dan efisien. Penelitian ini menegaskan potensi algoritma machine learning dalam mendukung pengambilan keputusan pada program bantuan sosial. Studi lanjutan disarankan untuk memperluas cakupan data dan mengeksplorasi metode klasifikasi lainnya guna optimalisasi distribusi bantuan.
Socialization and Implementation of a Midwifery Education Chatbot at the Rantauprapat City Community Health Center Fadillah, Riszki; Ramadani, Putri; Adawiyah, Quratih; Fitriyani, Intan Nur
International Journal of Community Service (IJCS) Vol. 4 No. 1 (2025): January-June
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijcs.v4i1.1080

Abstract

Improving the quality of maternal healthcare requires an innovative, technology-based approach, particularly in providing midwifery education. This community service project aimed to introduce and train pregnant women at the Rantauprapat City Community Health Center (Puskesmas) in the use of an educational chatbot based on the Recurrent Neural Network (RNN) algorithm. This chatbot was designed to provide fast, relevant, and accessible pregnancy health information. The activity involved coordination with partner health centers, outreach, hands-on training on the use of the chatbot, and evaluation of its effectiveness. The evaluation results showed that more than 90% of participants felt the chatbot helped them understand their pregnancy status, with the majority of questions related to early symptoms, diet, and safe activities during pregnancy. Furthermore, health workers stated that the chatbot could ease the burden of answering repetitive questions from patients. The implementation of this technology has significantly contributed to improving digital-based midwifery literacy and strengthening the role of community health centers as primary health care centers that are adaptive to technological developments. Going forward, the development of additional features and the expansion of local content are expected to strengthen the use of the chatbot on a broader scale.
Utilization of RNN Chatbots for Midwifery Education for Pregnant Women at Rantauprapat City Community Health Centers Fadillah, Riszki; Tanjung, Rani Darma Sakti; Tusakdiyah, Halimah; Jolyarni D, Novica; Purwanto, Juni
International Journal of Public Health Excellence (IJPHE) Vol. 4 No. 2 (2025): January-May
Publisher : PT Inovasi Pratama Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55299/ijphe.v4i2.1469

Abstract

The application of information technology in the healthcare sector has been rapidly advancing with the development of artificial intelligence. One of its potential applications is the use of chatbots powered by the Recurrent Neural Network (RNN) algorithm to enhance maternal health education access for pregnant women. Although health information is increasingly accessible, pregnant women often face challenges in obtaining accurate education about pregnancy due to limitations in time, location, and access to medical professionals. Puskesmas, as a primary healthcare center, plays a crucial role but is limited by the number of healthcare workers and operational hours, reducing the effectiveness of maternal health education delivery. Therefore, AI-powered chatbots can provide instant, personalized information that can be accessed anytime and anywhere. In this study, the developed chatbot using the RNN algorithm is capable of processing conversations contextually, providing relevant answers according to the stage of pregnancy and the specific needs of the pregnant woman. The implementation of this chatbot at Puskesmas Kota Rantauprapat is expected to improve the accessibility of maternal health education, reduce anxiety among pregnant women, and minimize the need for physical visits for common questions. The results of this study demonstrate the potential of RNN-based chatbots as an efficient tool in supporting maternal health education through digital platforms.
PREDIKSI METODE PERSALINAN DENGAN BIG DATA DAN ALGORITMA GRADIENT BOOSTING CLASSIFIER Fitriyani, Intan Nur; Fadillah, Riszki; Adawiyah, Quratih; D, Novica Jolyarni
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 8 No 1 (2025)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v8i1.1557

Abstract

This study aims to develop a prediction model to determine the method of delivery (normal or cesarean) using the Gradient Boosting algorithm based on maternal examination data. This model was evaluated using precision, recall, F1-score, and accuracy metrics. The results showed that the Gradient Boosting model had an accuracy of 48%, with better performance in predicting Normal delivery compared to Caesarean. Although this model is effective, there is an imbalance in precision and recall for the Caesarean class, indicating the need for improvement in identifying cases of cesarean delivery. Comparison with other algorithms such as Random Forest, Logistic Regression, and SVM showed that Random Forest gave the best performance with an accuracy of 55%. To improve performance, this study recommends hyperparameter optimization, application of class balancing techniques, and enrichment of medical features. The developed model has the potential to be used as a tool in medical decision-making related to delivery methods, which is expected to improve the safety of mothers and babies, and reduce dependence on subjective factors in medical decisions.
Edukasi Dan Pendampingan Pekerja Informal Dalam Optimalisasi Kepesertaan Sistem Jaminan Sosial Kesehatan Rina Anggraini; Riszki Fadillah
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 2 No. 2 (2024): Mei : Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v2i2.563

Abstract

Informal
COUNSELING MODEL BASED ON BACKWARD CHAINING OF STUDENT BEHAVIOR AT SMK 10 MUHAMMADIYAH KISARAN Amin, Muhammad; Supriyanto, Boby; Tamaza, Muhammad Abyanda; Asy’ari, Ilham; Fadillah, Riszki
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 1 (2023): Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i1.2811

Abstract

Student development includes conduct as a key component. Student behavior becomes crucial in deciding how successful students will be in different spheres of life. The variety of student behavior can hinder the learning process and personal development of students. Through the development of an expert system-based counseling model based on backward chaining, this study seeks to discover trends in student behavior. The research process starts with problem analysis, goal setting, literature study, data collection, system design and implementation, and results analysis. It then moves on to counseling model development and implementation in the school setting. To determine the reasons for the unruly behavior of the kids, data were analyzed using a backward chaining methodology. UML Usecase diagrams are used in system design to define the roles of actors and users. The established counseling model, which consists of 14 behaviors, 67 phenomena/symptoms, and 14 rules, focuses on goals and methods to modify student behavior. Three students underwent system testing based on previously achieved goals from therapy. The findings revealed "Smoking," "Emotional Problems," and "Fighting" among the student behaviors. When the Backward Chaining-based counseling model is used, it is simpler for homeroom teachers to gather information about students' conduct from them and to offer remedies based on the transfer of professional knowledge without having to wait for the counselor guidance procedure
Perkiraan Pola Permintaan Paspor di Kantor Imigrasi dengan Menggunakan Metode Exponential Smoothing untuk Memaksimalkan Layanan Riszki Fadillah; Fitriyani, Intan Nur; Ramadani, Putri; Mardivta, Hafizhah
JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital Vol. 4 No. 2 (2025): November 2025
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/jumintal.v4i2.6789

Abstract

This study aims to analyze the passport application patterns at the Immigration Office and forecast the number of applications for the coming years using the Exponential Smoothing (Holt-Winters) model. The data used includes the number of passport applications from 2022 to 2024. The analysis shows a significant increase in applications in the coming years, with predictions for 2025, 2026, and 2027 indicating a consistent growth pattern. While the model demonstrates good accuracy, the Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) calculations indicate overestimation for the 2024 forecast. The application of the Holt-Winters model in forecasting passport applications in the Immigration field is a novel contribution to the literature, as this method is rarely used in this context. The model provides a systematic quantitative approach to predict long-term trends in application data, which is crucial for more efficient service capacity planning. The implications of these findings suggest that, although the model can predict a consistent growth pattern, the overestimation in 2024 highlights the need for model adjustment in the future. Therefore, increasing service capacity through additional staff and optimizing the digital queuing system are strategic steps that should be implemented to handle the projected surge in applications. These measures are essential to ensure efficient service and the Immigration Office's preparedness for the ongoing rise in applications.
Hubungan Sistem Shift Perawat dan Kesalahan Medik di RSUD Rantauprapat Riyan Agus Faisal; Rani Darma Sakti Tanjung; Riszki Fadillah; Nabila Keysa Erianti
Journal of Innovative and Creativity Vol. 5 No. 2 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v5i2.2570

Abstract

Kesalahan medik merupakan salah satu indikator penting dalam menilai kualitas pelayanan rumah sakit, khususnya yang melibatkan tenaga keperawatan. Shift kerja perawat, terutama pada shift malam, sering dikaitkan dengan peningkatan risiko kesalahan medik akibat kelelahan, stres kerja, dan penurunan konsentrasi. Penelitian ini bertujuan untuk menganalisis hubungan antara sistem shift kerja perawat dengan kejadian kesalahan medik di RSUD Rantauprapat. Penelitian menggunakan desain analitik dengan pendekatan cross-sectional. Sampel penelitian berjumlah 100 perawat yang bekerja di instalasi rawat inap dan diambil menggunakan teknik total sampling. Data dikumpulkan melalui kuesioner dan dokumentasi kejadian kesalahan medik, kemudian dianalisis menggunakan uji Chi-Square.Hasil penelitian menunjukkan bahwa dari total 100 perawat, sebanyak 40% pernah melakukan kesalahan medik. Distribusi kesalahan paling banyak terjadi pada shift malam (66%), diikuti shift pagi (35%) dan shift sore (20%). Uji statistik menunjukkan adanya hubungan yang signifikan antara shift kerja dan kesalahan medik (p = 0,0004). Faktor-faktor penyebab kesalahan medik pada shift malam antara lain adalah kelelahan, tingginya beban kerja, dan kurangnya pengawasan. Hasil ini menunjukkan perlunya intervensi manajemen shift untuk menurunkan risiko kesalahan medik, seperti rotasi shift yang lebih seimbang, pelatihan manajemen kelelahan, serta peningkatan jumlah staf dan pengawasan pada shift malam.
Pendampingan Pemanfaatan Learning Management System Untuk Meningkatkan Kemandirian Belajar Mahasiswa Di Perguruan Tinggi Chairul Huda; Atika Sadariah Nasution; Intan Nur Fitriyani; Riszki Fadillah
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

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

Abstract

Transformasi digital dalam pendidikan tinggi mendorong perguruan tinggi untuk mengoptimalkan pemanfaatan teknologi pembelajaran guna meningkatkan kualitas proses belajar mahasiswa. Salah satu teknologi yang banyak digunakan adalah Learning Management System (LMS), yang berfungsi sebagai lingkungan belajar digital untuk mengelola materi, tugas, diskusi, dan evaluasi pembelajaran. Namun, pemanfaatan LMS yang belum optimal serta rendahnya kemandirian belajar mahasiswa masih menjadi tantangan dalam pelaksanaan pembelajaran digital. Oleh karena itu, kegiatan Pengabdian kepada Masyarakat ini bertujuan untuk meningkatkan kemandirian belajar mahasiswa Institut Teknologi dan Kesehatan Ika Bina melalui pendampingan pemanfaatan LMS secara terstruktur dan berkelanjutan. Metode pelaksanaan kegiatan dilakukan dengan pendekatan edukatif dan partisipatif yang melibatkan 100 mahasiswa sebagai peserta. Kegiatan meliputi tahap persiapan, sosialisasi pemanfaatan LMS, pendampingan teknis dan pedagogis, serta evaluasi dampak kegiatan. Pendampingan difokuskan pada optimalisasi penggunaan fitur LMS serta penguatan strategi belajar mandiri, seperti pengelolaan waktu, inisiatif belajar, dan tanggung jawab akademik. Hasil kegiatan menunjukkan bahwa pendampingan pemanfaatan LMS memberikan dampak positif terhadap kemandirian belajar mahasiswa. Mahasiswa menjadi lebih aktif dalam mengakses materi, mengelola tugas, dan berpartisipasi dalam diskusi daring. Selain itu, mahasiswa menunjukkan peningkatan dalam pengelolaan waktu belajar dan tanggung jawab terhadap proses pembelajaran. Kegiatan ini menegaskan bahwa pendampingan pemanfaatan LMS merupakan strategi yang efektif untuk mendukung pembelajaran digital dan pengembangan kemandirian belajar mahasiswa di perguruan tinggi.
Co-Authors Adawiyah, Quratih Al Ghazali, Baginda Restu Astia Weni Syaputri Asy’ari, Ilham Atika Sadariah Nasution Baginda Restu Al Ghazali Boby Supriyanto Chairul Huda D, Novica Jolyarni Desi Irfan Desi Irpan Dinda Salsabila Ritonga Fahruzi Sirait Hazlita Ilham Asy’ari Intan Nur Fitriyani Mardivta, Hafizhah Mesran, Mesran Muhammad Abyanda Tamaza Muhammad Amin Muhammad Amin Mustakim Mustakim Nabila Keysa Erianti Nur Indah Nasution Purwanto, Juni Putri Anglenia Putri Ramadani Rahadatul 'Aisy Riadi Ramadani, Ramadani Rani Darma Sakti Tanjung RINA ANGGRAINI Riswan Syahputra Damanik Riyan Agus Faisal Rizalina Rizalina Sarjon Defit Sentosa Pohan Sirait, Fahruzi Suerni Suerni, Suerni Sumijan Supriyanto, Boby Tamaza, Muhammad Abyanda Tanjung, Rani Darma Sakti Tusakdiyah Harahap, Halimah Tusakdiyah, Halimah Wahyu, Riski Ferita Yusril Iza Mahendra Hasibuan