cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Saluky
Contact Email
luke4line@yahoo.com
Phone
-
Journal Mail Official
jurnalsistemcerdas@gmail.com
Editorial Address
-
Location
Kota bekasi,
Jawa barat
INDONESIA
Jurnal Sistem Cerdas
Published by Asosiasi Prakarsa Indonesia Cerdas
ISSN : -     EISSN : 26228254     DOI : -
Core Subject : Science, Education, Engineering,
Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering
Jurnal Sistem Cerdas dengan eISSN : 2622-8254 adalah media publikasi hasil penelitian yang mendukung penelitian dan pengembangan kota, desa, sektor dan kesistemam lainnya. Jurnal ini diterbitkan oleh Asosiasi Prakarsa Indonesia Cerdas (APIC) dan terbit setiap empat bulan sekali.
Arjuna Subject : Umum - Umum
Articles 13 Documents
 1   2 
Search results for , issue "Vol. 7 No. 3 (2024)" : 13 Documents clear
Application of the DBSCAN Algorithm in MSME Clustering using the Silhouette Coefficient Method Abidin, Mochammad Syahrul; Kustiyahningsih, Yeni; Rahmanita, Eza; Satoto, Budi Dwi; Firmansyah, Muhammad Iqbal
Jurnal Sistem Cerdas Vol. 7 No. 3 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i3.472

Abstract

MSMEs participate in the very important contribution of developing Indonesia's economy, where this industry contributes to GDP and also to the absorption of labor. Most MSMEs in Sidoarjo Regency are still constrained by financial management and the utilization of technology. This research will apply the DBSCAN method to clustering MSMEs in Sidoarjo for the purpose of finding patterns in characteristics related to capital, turnover, and workforce. The analysis will involve 1,479 MSMEs, while the research methodology applies the CRISP-DM method to guide the process from business understanding up to the implementation phase. Normalization using Simple Feature Scaling was applied before clustering. The results of this analysis provide insight that the best possible combination of the parameters in DBSCAN is epsilon (ε) 0.10 and MinPts 16, which gives the optimal value of Silhouette Score as 0.4304. It creates seven clusters, in which the third has the highest Silhouette value of 0.9326, indicating that there are high similarities recorded within that cluster. These results provide essential lessons to develop more targeted policy strategies and interventions for MSMEs in Sidoarjo and explore the capabilities of DBSCAN as an effective analytical tool in determining the characteristics of businesses in the region.
User Experience Evaluation of M-Passpor Using User Experience Questionnaire Winanda, Salsa; Tengku Khairil Ahsyar; Angraini; Megawati
Jurnal Sistem Cerdas Vol. 7 No. 3 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i3.474

Abstract

This study evaluates UX of the M-Passpor application, an m-government application to facilitate the online passport administrative process and reduce queues at the immigration office. Although this application offers convenience in making passports, since its release M-Paspor has received many complaints from users regarding the services provided. A UX evaluation was conducted using the UEQ method, which measures six of these aspects aspects: Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, and Novelty. The outputs presented that Perspective and Attractiveness aspects had the highest scores, indicating that the app is quite easy to understand and visually appealing. However, the Novelty aspect had a low score, indicating a lack of innovation and new experiences for users. Based on these findings, the researcher recommends improving efficiency, simplifying processes, notifications and feature innovation to improve UX. The outcome of this study is expected to become the basis for improving the UX quality of the M-Passpor application so as to create better and satisfying services for users in the future
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.

Page 2 of 2 | Total Record : 13

 1   2 

Filter by Year

2024 2024


Reset
Filter By Issues
All Issue Vol. 8 No. 3 (2025) Vol. 8 No. 2 (2025) Vol. 8 No. 1 (2025) Vol. 7 No. 3 (2024) Vol. 7 No. 2 (2024) Vol. 7 No. 1 (2024) Vol. 6 No. 3 (2023) Vol. 6 No. 2 (2023) Vol. 6 No. 1 (2023) Vol. 5 No. 3 (2022) Vol. 5 No. 2 (2022) Vol. 5 No. 1 (2022) Vol. 4 No. 3 (2021) Vol. 4 No. 2 (2021) Vol. 4 No. 1 (2021) Vol. 3 No. 2 (2020): Riset dan Inovasi Sistem Cerdas pada Penanggulangan Wabah Covid-19 Vol. 3 No. 3 (2020): Kecerdasan Artifisial pada Rekayasa Biomedis Vol. 3 No. 1 (2020): Artificial Intelligence untuk Indonesia Vol. 2 No. 3 (2019): Transformasi dan Inovasi Kota Cerdas Vol. 2 No. 2 (2019): Smart Transportation Vol. 2 No. 1 (2019): Artificial Intelligence for Smart Society Vol. 1 No. 2 (2018): Internet of Things for Smart Society Vol. 1 No. 1 (2018): Smart System More Issue