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All Journal Dinamik Pixel : Jurnal Ilmiah Komputer Grafis Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika BERNAS: Jurnal Pengabdian Kepada Masyarakat Abdi Kami : Jurnal Pengabdian Kepada Masyarakat Infotek : Jurnal Informatika dan Teknologi Madaniya Media Aplikom Jurnal Bingkai Ekonomi (JBE) Brilliance: Research of Artificial Intelligence Jurnal Informasi Sains dan Teknologi (ISAINTEK) Jurnal Rekam Medis dan Manajemen Informasi Kesehatan Jurnal Cakrawala Informasi (JCI) Jurnal HUMMANSI (Humaniora, Manajemen, Akuntansi) Digital Transformation Technology (Digitech) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Jurnal Pengabdian Teknik dan Ilmu Komputer (PETIK) Jurnal Pengabdian Kepada Masyarakat Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Community: Jurnal Pengabdian Pada Masyarakat SmartComp Jurnal Pengabdian Masyarakat (Jupemas) Jurnal Pengabdian Masyarakat Science Technology and Management Journal (STMJ) Scientific Journal of Informatics Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi ABDI KAMI: Jurnal Pengabdian Kepada Masyarakat Global Science: Journal of Information Technology and Computer Science
Siska Narulita
Universitas Nasional Karangturi Semarang
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Journal : Science Technology and Management Journal (STMJ)

 1 
INTEGRASI MODEL AIDA PADA VIRTUAL CARD: PENGEMBANGAN SISTEM INFORMASI PEMASARAN DIGITAL PADA BATIK WARNA ALAM SIPUTRI Andreas Tigor Oktaga; Siska Narulita; Prihati
Science Technology and Management Journal Vol. 5 No. 1 (2025): Januari 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Nasional Karangturi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53416/stmj.v5i1.330

Abstract

Penelitian ini bertujuan untuk mempertajam sistem informasi pemasaran digital dengan merancang dan mengimplementasikan virtual card yang menerapkan model AIDA. Metode penelitian menggunakan pendekatan waterfall yang diuji dengan Blackbox Testing dan System Usability Scale (SUS) terhadap pelanggan dan calon pelanggan Batik Warna Alam siPutri. Bahasa pemrograman yang digunakan adalah HTML, CSS, dan Javascript, yang mengasilkan virtual card dengan nilai usability yang tinggi. Skor acceptability ranges berada pada zona Acceptable, dengan skala grade A, dan adjective rating termasuk dalam kategori best imaginable. Hasil penelitian ini memberikan wawasan terdapatnya kombinasi yang erat pada penerapan model AIDA dalam implemetasi sistem dan teknologi informasi untuk menunjang strategi pemasaran online dan memberikan dampak yang signifikan.
Analysis of Fashion Business Customer Segmentation Based on Age Using the X-Means Algorithm Approach Sudradjat Budi Darminto, Gafgarion; Siska Narulita
Science Technology and Management Journal Vol. 6 No. 1 (2026): Januari 2026
Publisher : Fakultas Sains dan Teknologi, Universitas Nasional Karangturi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53416/stmj.v6i1.489

Abstract

The rapid development of the fashion industry in Indonesia requires business practitioners to understand customer behavior more deeply and efficiently in order to formulate targeted marketing strategies. One approach that can be used to identify customer behavior patterns is customer segmentation. This study aims to perform customer segmentation in the fashion business based on age using the X-Means algorithm. The data used were obtained from a sales transaction dataset consisting of customer, order, product, and sales information. The variables analyzed include customer age and total expenditure. To evaluate the performance of the method, the X-Means algorithm was compared with K-Means and K-Medoids. Algorithm performance was measured using the Davies–Bouldin Index (DBI). The experimental results show that X-Means produced the best performance with the lowest DBI value of 0.404 at k = 5 clusters, indicating a more representative grouping of differences in purchasing behavior based on age. The segmentation results can be utilized by fashion business practitioners to design more appropriate promotional strategies and product recommendations tailored to the characteristics of each age group. Furthermore, this study recommends the use of the Deep Embedded Clustering (DEC) approach in future research when large-scale datasets (more than 1,000 customer records) are available, as deep learning-based methods are more capable of capturing non-linear patterns and improving cluster representation quality.
ANALISIS FORECASTING EKSPOR BATIK INDONESIA DENGAN ALGORITMA X-MEANS Gracia Stefani Suharyadi; Siska Narulita
Science Technology and Management Journal Vol. 6 No. 1 (2026): Januari 2026
Publisher : Fakultas Sains dan Teknologi, Universitas Nasional Karangturi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53416/stmj.v6i1.490

Abstract

Batik is one of Indonesia's cultural heritages that has high economic value because it is a leading export product. In recent years, the value of batik exports has varied considerably each year. This study was conducted to analyze Indonesian batik export data using the X-Means algorithm as a development of previous studies that used forecasting methods. The difference in this study lies in the approach used. While forecasting emphasizes future predictions, the X-Means algorithm is used to see the clustering patterns of existing data. The data used comes from the 2010-2021 batik export dataset obtained from Kaggle and the Indonesian Batik and Handicraft Center. Data processing was carried out using the RapidMiner application with several cluster tests to determine the best results. The results showed that the test with 3 clusters produced a Davies Bouldin Index (DBI) value of 0.029. A low DBI value indicates that the clustering results are very good and there is a clear distance between clusters. From these results, the countries with the highest batik export values were the United States, Germany, and Japan, while the countries with the lowest exports included Slovenia and Portugal. These results prove that the X-Means algorithm can be used to analyze Indonesian batik export patterns effectively.
Co-Authors Aditya Eka Widyantoro Aditya, Galuh Agus Wantoro Ahmad Jurnaidi Wahidin Ahmad Nugroho Aji Priyambodo Amaliyah, Shofwatun Andreas Heri Kurniawan Andreas Tigor Oktaga, Andreas Aries Alfian Prasetyo Aries Alfian Prasetyo, Aries Alfian Aulia Noveesa Allanda Bambang Widjanarko Susilo Bayu Praharsena Calisto, Calvin Deny Prasetyo Dhieo Kurniawan Diah Ayu Fatmasari Dimas Adi Wicaksono Dody Indra Sumantiawan Dyah Ardyani Rizqi Azizah Adha Evan Setiawan Wicaksono Faqih Ahyar Prayoga Gafgarion Sudrajat Budi Darminto Galuh Aditya Gati Gati Ghani Ayang Arjuna Giyantolin Gracia Stefani Suharyadi Heru Yulianto Hikmal Adi Wibowo Ika Susanti Indradno, Jasman Jasman Indradno Jawade Hafidz Arsyad Kholilurrahman, Muhammad Kristiawan Nurdianto Kurniawan, Dhieo Laurentius Kenneth V Luther Aldo Christian M. Zakki Abdillah Marsiska Ariesta Putri Martinus Apun Heses Martinus Apun Heses Mayadilanuari, Aerrosa Murenda Michael Fernando Putra S Milka Putri Novianingrum Mudjiyono Munadi Munadi Nanik Qosidah Novianingrum, Milka Putri Nugroho, Ahmad Oei Joviano Matthew Wijaya Petra Valentino Praharsena, Bayu Prihati Prihati . Prihati Prihati Prihati Prihati Priyo Nugroho Adi Priyo Nugroho Adi Priyo Wibowo Rengga Pratama Putra Retno Ginanjar Reynard Adelard Richo Muthicahya Safari, Teti Sekarlangit Sekarlangit Sekarlangit Sekarlangit, Sekarlangit Silvia Nurvita, Silvia Sri Danar Dono Sudradjat Budi Darminto, Gafgarion Suhaji Suhaji Suharmanto, Abraham Yano Sumantiawan, Dody Indra Suprapedi Suprapedi Suprapedi Suprapedi Suyahman Suyahman Teguh Khristianto Very Dwi Setiawan Vic Jeremy Prajogo Widiastuti, Rosalina Yani