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Fitriani Muttakin
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Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering

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Analisis Kepuasan Pengguna Aplikasi DANA Menggunakan Metode TAM dan EUCS Fitratul Aini; Fitriani Muttakin; Tengku Khairil Ahsyar; Eki Saputra
Jurnal Sistem Cerdas Vol. 6 No. 1 (2023)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v6i1.288

Abstract

The DANA application is a payment system service that can be used via a smartphone, which can be in the form of fund transfers, electronic wallets, electronic money and other supporting services. User satisfaction with the application is very important, because it can be used as an assessment material for improving the service quality of the application. By combining two methods, namely the Technology Acceptance Model (TAM) which contains the variables Perceived Usefulness, Perceived Ease of Use and Attitude Toward Using and End User Computing Satisfaction (EUCS) which contains the variables Content, Accuracy, Format, Ease of Use and Timeliness to measure application user satisfaction DANA is the aim of this research. The technique that will be used to collect data is by distributing questionnaires to DANA application users. Through lameshow calculations, there were 100 respondents in this study. Based on the results of the analysis carried out, there are 6 hypotheses that are accepted, namely Perceived Usefulness, Content, Accuracy, Format, Ease of Use and Attitude Toward Using and 2 hypotheses are rejected, namely Perceived Ease of Use and Timeliness. The results obtained through SEM analysis are classified as good with an R-Square correlation value of 75.2% for user satisfaction variables.
Sistem Pengendalian Persediaan Stok Obat dengan Menggunakan Metode Analisis Always Better Control dan Metode Economic Order Quantity Pada Apotek Shofika Adilya; Fitriani Muttakin; Angraini
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1866

Abstract

XYZ Pharmacy is a pharmacy that specializes in the sale of prescription medications and exclusively accepts prescriptions from licensed physicians. Problems that arise include determining which drugs should be prioritized to reduce production costs which result in unstable drug stock supplies, and frequent excesses and shortages of drug stock due to delays in drug orders from suppliers. Therefore, it is necessary to apply a technique that makes it easier to control drug stock at XYZ Pharmacy, which aims to make it easier for XYZ Pharmacy to determine which drugs should be prioritized and manage drug stock control in the pharmacy. To overcome these problems effectively. ABC analysis of drugs in group A shows that there are 7 types of drugs which contribute 35.00% of total drug use, and generate total income of 67%. In group B there are 6 types of drugs which represent 30.00% of total drug use and generate total income of 23%. Finally, group C consists of 7 types of drugs which cover 35.00% of total drug use, and generate total revenue of 11%. Using the EOQ method, analysis was carried out on 7 types of drugs in group A, obtaining various optimal order quantities EOQ. The highest EOQ was 90.64 or 90 items for OB2 drugs, while the lowest EOQ was 43.29 or 43 items for OB19. Each type of drug has a range of 1-4 Safety Stock, and the Reorder Point for each type of drug varies in terms of the number of units needed.
Customer Segmentation Using the RFMD Model and Fuzzy C-Means Algorithm Muhammad Hafis Zikri; Siti Monalisa; Fitriani Muttakin
Jurnal Sistem Cerdas Vol. 7 No. 3 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i3.481

Abstract

Many businesses face challenges in optimizing customer data processing, which often limits the ability to understand customer behavior and improve marketing strategies. This research addresses these challenges by applying the RFMD (Recency, Frequency, Monetary, Diversity) model combined with the Fuzzy C-Means (FCM) clustering algorithm to segment customers based on transaction data. The results identified five distinct customer segments based on Customer portfolio Analysis (CPA), which were validated using the Davies-Bouldin Index (DBI), with each segment showing diverse levels of engagement and behavioral patterns. The results show that the best clusters of Superstar and Golden customers are clusters 4 and 2, while Typical and Occasional customers are clusters 1 and 3. The lowest cluster of Everyday customers is found in cluster 5. The findings provide applicable insights to improve customer retention and optimize data-driven marketing strategies.
Customer Segmentation Analysis Through RFM-D Model and K-Means Algorithm Refri Martiansah; Siti Monalisa; Fitriani Muttakin; Mona Fronita
Jurnal Sistem Cerdas Vol. 8 No. 1 (2025)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v8i1.504

Abstract

This research analyzes customer segmentation through the RFM-D (Recency, Frequency, Monetary, and Diversity) model and the K-Means algorithm. The data comes from sales transactions at Café Z from January 2023 to February 2024, with 10,212 entries. The applied methodology includes several stages: data pre-processing, cleaning, transformation, normalization, and clustering. Clustering validation was carried out using the Davies-Bouldin Index (DBI) to ensure the quality of the clusters formed. The analysis results identified three customer clusters based on purchasing behavior, indicating that the K-Means algorithm effectively groups customers. These findings provide insight for companies to design marketing strategies that are more focused and appropriate to the characteristics of each customer segment. Companies can improve operational efficiency, increase customer satisfaction, and maximize profitability by utilizing this segmentation. This research contributes to optimizing resource allocation and personalizing marketing approaches, ultimately strengthening customer relationships.
Sistem Pakar Diagnosa Gizi Buruk Pada Balita Menggunakan Metode Forward Chaining M Zaky Ramadhan Z; Fitriani Muttakin; Zarnelly; Inggih Permana
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 5 (2024): April 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i5.1776

Abstract

During a child's growth and development, inadequate nutrition can impede both physical and intellectual development. Although many people perceive these issues as commonplace, neglecting them can lead to severe consequences. To address the challenge of a limited number of nutritionists and a growing number of patients, this final project introduces an expert system designed to identify malnutrition in toddlers. The expert system conducts a diagnosis of malnutrition based on observed symptoms and offers recommendations for addressing the issues associated with malnutrition in toddlers. This expert system aims to empower parents to independently identify their children's malnutrition types, potentially alleviating the shortage of nutritionists in the healthcare system. The expert in this study is a nutritionist working at Puskesmas Berkilau Pangkalan Kerinci 2. If the knowledge base and production rules, which consist of comprehensive and accurate information, are in place, they can be applied to develop an inference engine. In this phase, the application guides users in inputting facts (characteristics), enabling the generation of conclusions related to toddler nutrition levels. The knowledge stored in the knowledge base and production rules serves as the foundation for the inference engine
Co-Authors Angraini Eki Saputra Fitratul Aini Inggih Permana M Zaky Ramadhan Z Mona Fronita Muhammad Hafis Zikri Refri Martiansah Shofika Adilya Siti Monalisa Tengku Khairil Ahsyar Zarnelly