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All Journal Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Jurnal Pengabdian Pada Masyarakat IPTEKS
Hazlita
Institut Teknologi Dan Kesehatan Ika Bina
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Social Sciences Transportation

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Backpropagation Neural Network Untuk Prediksi Kebutuhan Pemakaian Obat (Kasus Di RSUD dr. Adnaan WD) Hazlita, H; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Vol 9, No 1 (2024): Edisi Februari
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/jurasik.v9i1.736

Abstract

Artificial Intelligence which is developing increasingly rapidly makes it possible to make predictions. Predictions are made using one of the Artificial Intelligence systems, namely Artificial Neural Networks. Predicting the need for drug use is a problem currently being faced by RSUD dr. Adnaan WD Payakumbuh so that the service is not optimal. This research aims to design an Artificial Neural Network architecture and determine the resulting level of accuracy in predicting the need for drug use. The method used in this research is the Backpropagation method. The stages in the Backpropagation algorithm include the initial weight initialization process, activation stage, weight change and iteration stage. The data processed in this research is drug use data obtained from the Pharmacy Installation at dr. Adnaan WD Payakumbuh Hospital. The results of this research show that the best network architecture is 12-12-1 with a relatively small Mean Squared Error (MSE) value of 0.00685, a Mean Absolute Percentage Error (MAPE) value of 0.1696% and a high level of accuracy reaching 99 .83% for the prediction of Paracetamol 150 mg. The results of this research can help health service centers optimize their services
Pendampingan Pengajar Meningkatkan Pembelajaran Berbasis Teknologi Informasi di SDIT Alam Sahabat Al-Qur'an Aek Kanopan Chairul Huda; Riszki Fadillah; Hazlita; Intan Nur Fitriyani; Suerni
Jurnal Pengabdian Pada Masyarakat IPTEKS Vol. 3 No. 3 (2026): Jurnal Pengabdian Pada Masyarakat IPTEKS, Juni 2026
Publisher : CV. Global Cendekia Inti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71094/jppmi.v3i3.360

Abstract

This community service activity aimed to improve teachers' competence in developing technology-based learning materials through the use of Canva and Quizizz at SD IT Alam Sahabat Al-Qur'an Aek Kanopan. The activity employed the Participatory Action Research (PAR) approach involving 15 teachers. The implementation consisted of needs identification, program planning, material presentation, Canva and Quizizz training, hands-on practice with mentoring, and evaluation. During the activity, participants developed digital learning media using Canva and interactive learning assessments using Quizizz according to the subjects they taught. The evaluation was conducted through observation and a satisfaction questionnaire using a five-point Likert scale. The results showed that all 15 participants successfully produced learning media and digital quizzes ready for classroom implementation. The evaluation also indicated an average score of 4.81 (96.2%), categorized as Very Good, demonstrating that the mentoring program effectively enhanced teachers' digital competencies and increased their readiness to integrate technology into classroom learning. This activity is expected to encourage sustainable innovation in technology-based learning within the school environment
Customer Relationship Management Strategy for Enhancing Customer Loyalty at MM Beauty Clinic Using the K-Means Algorithm Hazlita Hazlita; Hafizhah Mardivta; Aysyah Rengganis
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 7, No 1 (2026): Inovasi Teknologi Informasi Berkelanjutan Mendukung Ekosistem Cerdas Berbasis Di
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v7i1.15780

Abstract

MM Beauty Clinic is one of the beauty service providers in North Sumatra Province that still carries out most of its service processes manually. This condition has the potential to reduce service quality and increase the risk of customers switching to other clinics. This study aims to design and implement a web-based Customer Relationship Management (CRM) system to strengthen customer loyalty. The system was developed using the PHP programming language and a MySQL database. The approach used is Recency, Frequency, and Monetary (RFM) analysis combined with the K-Means algorithm to segment customers based on their transaction patterns. The data used are patient transaction data for April 2026. The segmentation results are used as the basis for determining appropriate service strategies for each customer group. The implementation of this CRM system is expected to improve the effectiveness of customer relationship management, as well as facilitate transaction processing, consultation services, complaint submission, and access to service information more quickly, effectively, and efficiently.
Co-Authors Aysyah Rengganis Chairul Huda Gunadi Widi Nurcahyo Hafizhah Mardivta Intan Nur Fitriyani Riszki Fadillah Sarjon Defit Suerni