Claim Missing Document
Check
Articles

Found 3 Documents
Search

Analisa Model Clustering Untuk Pemetaan Kualitas Lulusan Mahasiswa Berdasarkan Dataset Tracer Study Yusda, Riki Andri; Risnawati, Risnawati; Santoso, Santoso; Siregar, Putri Zakiyah Maharani; Nurani, Widiya Putri
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp18-23

Abstract

Graduate data from the tracer study process is critical in assessing the quality of a university's graduates. From this data, universities can see an objective picture to measure and evaluate the curriculum, materials, and the achievement of learning competencies so far whether they are following what is expected by graduate users. This will provide input to university management in making strategies and policies to improve quality. However, the problem is that the amount of data available so far has not been maximized properly to assist management in making decisions. Data on graduates and users of existing graduates are only processed into semester and annual reports and there is no in-depth analysis. So management does not get information that helps improve graduates' quality in the future. Optimization of clustering methods using the elbow method with a comparison of other distance formulas such as Euclidean Distance, Mahalanobis Distance, and Manhattan City Distance to improve the performance of mapping results. The DBI result obtained is 1.89 for the number of 6 clusters.
The Customer Relationship Management Concept Increases Customer Commitment Nurani, Widiya Putri; Manurung, Nuriadi; Dewi, Muthia
ITEJ (Information Technology Engineering Journals) Vol 10 No 2 (2025): December (In Progress)
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.276

Abstract

The advancement of information technology has encouraged business actors, including retail enterprises such as Toko Jaya Fashion, to adopt digital strategies in order to maintain and enhance customer commitment. Toko Jaya Fashion still operates using a manual sales system, resulting in low efficiency in customer data management and a noticeable decline in sales, particularly at the end of 2024. This study employs a qualitative research method by observing a single case in detail. This approach allows the researcher to gain a comprehensive understanding of the issues studied. This study aims to design and implement a web-based Customer Relationship Management (CRM) system as a solution to address these issues. The system is developed using the PHP programming language and MySQL database, and is equipped with features such as member cards, cashback programs, monthly sales reports, and online customer service. Based on the implementation results, the system significantly improves service quality, broadens marketing reach, and assists in managing customer data in a structured manner. It provides easier access to product information, offers special promotions for loyal customers, and facilitates customer feedback through WhatsApp integration. Moreover, the adoption of this CRM website has expanded product sales to customers outside the Meranti area, enabling Toko Jaya Fashion to reach more customers and increase overall satisfaction, thereby strengthening customer commitment.
Analisa Model Clustering Untuk Pemetaan Kualitas Lulusan Mahasiswa Berdasarkan Dataset Tracer Study Yusda, Riki Andri; Risnawati, Risnawati; Santoso, Santoso; Siregar, Putri Zakiyah Maharani; Nurani, Widiya Putri
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp18-23

Abstract

Graduate data from the tracer study process is critical in assessing the quality of a university's graduates. From this data, universities can see an objective picture to measure and evaluate the curriculum, materials, and the achievement of learning competencies so far whether they are following what is expected by graduate users. This will provide input to university management in making strategies and policies to improve quality. However, the problem is that the amount of data available so far has not been maximized properly to assist management in making decisions. Data on graduates and users of existing graduates are only processed into semester and annual reports and there is no in-depth analysis. So management does not get information that helps improve graduates' quality in the future. Optimization of clustering methods using the elbow method with a comparison of other distance formulas such as Euclidean Distance, Mahalanobis Distance, and Manhattan City Distance to improve the performance of mapping results. The DBI result obtained is 1.89 for the number of 6 clusters.