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IC Tech: Majalah Ilmiah
Published by Institut Widya Pratama
ISSN : 19077912     EISSN : 26228092     DOI : https://doi.org/10.47775/ictech.v20i2
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Other
IC Tech: Majalah Ilmiah merupakan publikasi ilmiah yang berfokus pada bidang ilmu komputer dan teknologi terkaitnya yang diterbitkan oleh Pusat Penelitian dan Pengabdian kepada Masyarakat Institut Widya Pratama. Jurnal ini berfungsi sebagai platform bagi para peneliti, akademisi, dan profesional untuk berbagi temuan, inovasi, dan kemajuan mereka di berbagai bidang seperti Kecerdasan Buatan (Artificial Intelligence, AI), Algoritma dan Pemrograman, Jaringan Komputer dan Keamanan Siber, Rekayasa Perangkat Lunak, Big Data dan Data Mining, Manajemen Sistem Informasi, Analisis dan Desain Sistem. IC Tech: Majalah Ilmiah menerbitkan artikel penelitian asli, makalah tinjauan, dan laporan teknis, yang memberikan wawasan tentang aspek teoritis dan praktis ilmu komputer.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 182 Documents
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ANALISIS KEPUTUSAN MAHASISWA DALAM MEMILIH INSTITUT WIDYA PRATAMA DAN IMPLIKASINYA TERHADAP STRATEGI PEMASARAN VICTORIANUS ARIES SISWANTO; Tri Pudji Wahjuningsih; Nur Ika Royanti
IC Tech: Majalah Ilmiah Vol 21 No 1 (2026): IC Tech: Majalah Ilmiah Volume XXI No. 1 April 2026
Publisher : P3M Institut Widya Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47775/ictech.v21i1.399

Abstract

This study aims to examine the factors influencing students’ decision-making in choosing Institut Widya Pratama (IWIMA) Pekalongan and their implications for the institution’s marketing strategy formulation. The research is motivated by the declining trend in new student admissions in recent years, highlighting the need to analyze student behavior as consumers of higher education services. This study employs a descriptive approach using a mixed-method design (qualitative and quantitative). Data were collected through a Google Form questionnaire distributed to 102 active students in semesters 3, 5, and 7 from the Informatics Engineering and Information Systems study programs. The data analysis technique used descriptive percentage analysis to identify the dominant factors influencing campus selection decisions. The results indicate that the primary source of information about IWIMA is recommendations from friends and family (62.6%), followed by social media (33.3%) and brochures (20.2%). The dominant factors in choosing a study program are students’ personal interest (54.9%), the desire to deepen knowledge in computer science (45.1%), and consideration of job opportunities after graduation (37.3%). The decision to enroll at IWIMA is mainly influenced by proximity to parents (38.2%), followed by interest in the study program (30.4%), career opportunities (29.4%), and the strategic location of the campus (27.5%). The level of student satisfaction with IWIMA tends to be neutral (44.1%), while 32.4% of students are satisfied and 13.7% are very satisfied, with the remainder expressing dissatisfaction. These findings suggest that IWIMA’s marketing strategy should focus on strengthening word-of-mouth promotion, optimizing social media utilization, improving the quality of academic services and campus facilities, and enhancing collaboration with stakeholders to increase student satisfaction, institutional image, and competitiveness in attracting prospective students.
ANALISIS KLASTERISASI DATA TRANSAKSI PENYEWAAN PAKAIAN MENGGUNAKAN ALGORITMA K-MEANS UNTUK IDENTIFIKASI KARAKTERISTIK PELANGGAN SEBAGAI DASAR STRATEGI INOVASI DAN STOK Much Rifqi Maulana; Arochman; Chrinstian Yulianto Rusli
IC Tech: Majalah Ilmiah Vol 21 No 1 (2026): IC Tech: Majalah Ilmiah Volume XXI No. 1 April 2026
Publisher : P3M Institut Widya Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47775/ictech.v21i1.402

Abstract

This study aims to analyze clothing rental patterns and identify customer segmentation of Nani Collaction Clothing Rental, as an effort to support strategic decision-making in the rental business. The method used is the K-Means algorithm with the determination of the optimal number of clusters using the Elbow Method. The data analyzed include clothing categories, costs, rental time, clothing types (men/women), and sizes (children/adults). The results show that the data can be grouped into four main clusters, namely the profession-based children's segment, the culture-based children's segment, the adult segment with high transaction value, and the niche youth segment. The children's segment has the largest transaction volume and is therefore the main market, while the adult segment contributes more to revenue. Meanwhile, the youth segment has specific and seasonal demand characteristics. The analysis results show that the clustering approach is effective in identifying customer patterns and can be used as a basis for developing business strategies, particularly in stock management, service innovation, and market segmentation. This study also recommends the implementation of segmentation-based strategies, the utilization of reservation technology, and the development of further research by adding more diverse variables and clustering methods.

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