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Evaluasi Usability Aplikasi Mobile Banking Menggunakan Metode Retrospective Think Aloud dan Post-Study System Usability Questionnaire Naufal, Muhammad; Ahsyar, Tengku Khairil; Jazman, Muhammad; Permana, Inggih
The Indonesian Journal of Computer Science Vol. 13 No. 3 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i3.4039

Abstract

BRKS Mobile is a digital service provided by Bank Riau Kepri Syariah to facilitate its customers in conducting financial transactions via smartphones. Because this application is relatively new, there are problems when running the application. The results of user reviews on playstore comments and pre-surveys, the problem that often occurs is errors when making transactions. In this study, usability evaluation was carried out using the Retrospective Think Aloud (RTA) and Post-Study System Usability Quesionaire (PSSUQ) methods. The results of the usability measurement show that users experience little difficulty when running the transfer and purchase menus. This is reinforced by the results contained in the norms of the PSSUQ method where the results of the SyeUse variable value of 2.70 and InfoQual 2.95 are below the average which indicates that the usability of the system and the quality of information on BRKS Mobile are still lacking. For the InterQual value of 3.09, it is above average and overall the BRKS application is at 2.89 above average, which means that the application can be accepted by its users.
PENGEMBANG TOOLKIT SUPPLY CHAIN MANAGEMENT DENGAN PENDEKATAN HOUSE OF RISK (HOR) (CASE STUDY: SAINT CINNAMON PEKANBARU) Putra, Adhytia Pratama; Angraini, Angraini; Salisah, Febi Nur; Jazman, Muhammad
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7812

Abstract

Penelitian ini mengembangkan perangkat Supply Chain Manage-ment (SCM) dengan menggunakan pendekatan House of Risk (HOR), Excel dan Visual Basic for Applications (VBA) untuk mengatasi tan-tangan manajemen risiko di Saint Cinnamon Pekanbaru. Metode House of Risk (HOR) memakan waktu dan rentan terhadap kesala-han, sehingga membutuhkan waktu s. Perangkat lunak ini men-gotomatiskan analisis risiko, mendukung pengambilan keputusan yang lebih cepat dan akurat. Metodologi ini menggunakan model SCOR untuk mengidentifikasi risiko di seluruh rantai pasokan (Plan, Source, Make, Deliver, Return). Model House of Risk (HOR) kemudian diterapkan untuk memprioritaskan agen risiko berdasarkan Aggregate Risk Potential (ARP). Strategi mitigasi diformu-lasikan dan diurutkan berdasarkan rasio Efektivitas terhadap Tingkat Kesulitan.Perangkat ini mengotomatiskan analisis HOR, menghasilkan diagram Pareto dan matriks ETD. Toolkit berbasis Visual Basic for Applications (VBA) yang dikembangkan memung-kinkan manajemen risiko yang proaktif, mengurangi gangguan operasional, dan meningkatkan layanan pelanggan.
MSME Segmentation in Pekanbaru Based on Local E-Catalog Participation Using K-Means Aliya, Rahma; Permana, Inggih; Salisah, Febi Nur; Novita, Rice; Jazman, Muhammad
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.760

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the economy; however, their participation in digital government procurement platforms such as the Local E-Catalog in Pekanbaru City remains relatively low. The lack of comprehensive, data-driven mapping of MSME characteristics has resulted in less targeted development and assistance programs. This study aims to segment MSMEs based on revenue, number of employees, and participation status in the Local E-Catalog to generate business groups that can support more effective development strategies. A data mining approach using the K-Means clustering algorithm was applied and implemented through the Orange Data Mining application. The results indicate that a three-cluster configuration is the most optimal, achieving the highest Silhouette Score of 0.444. Cluster 1 represents micro-scale MSMEs with low business capacity and minimal participation in the Local E-Catalog, Cluster 2 consists of growing MSMEs with moderate business capacity, and Cluster 3 comprises established MSMEs with high business capacity and active participation in the Local E-Catalog. These findings provide empirical evidence to support local governments in formulating more targeted and data-driven policies for accelerating MSME digitalization.