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All Journal Sistemasi: Jurnal Sistem Informasi J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS)
Susetyo, Yeremia Alfa
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy

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Perancangan UI/UX Design Aplikasi Pemesanan Sayur Berbasis Mobile Menggunakan Design Thinking Cantika, Berliana Nala; Susetyo, Yeremia Alfa
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 2 (2023): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i2.671

Abstract

One of the most common problems is how to save time without going to the market. In addition, it is difficult to search for vegetables by type, quality, price and other factors. Therefore, this application is designed to provide solutions that bring convenience and meet the needs of users. The purpose of this study is to apply the design thinking method in making UI/UX design for mobile-based vegetable ordering applications. Design Thinking is a method that focuses on innovation and consumers, in addition to paying attention to user needs and combining them with appropriate technological features so that they become good products due to their feasibility. Empathize, define, ideate, prototype, and testing are the 5 stages of the design thinking method. Next, use the System Usability Scale as a testing stage. Based on the test results on the aspect of satisfaction obtained a score of 91 with the assessment of adjective ratings is “Excellent“, while the grade scale gives the results of”A".
Predict Airline Customer Satisfaction using a Machine Learning Model Suwito, Yoel Dinata; Susetyo, Yeremia Alfa
SISTEMASI Vol 15, No 1 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i1.5868

Abstract

Customer satisfaction is a strategic factor for the sustainability of airline businesses amid increasingly intense competition in the aviation industry. This study aims to predict airline customer satisfaction using an Artificial Neural Network (ANN) approach by leveraging a publicly available Kaggle dataset containing 22 airline service features. Two ANN architectures were developed, differing primarily in the number of hidden layers, the number of neurons, and the application of Batch Normalization and LeakyReLU in the second model. The experimental results show that the first ANN model achieves an accuracy of 92.31%, while the second model attains significantly higher performance, with an accuracy of 95.75% on the test dataset. The second model also demonstrates a strong balance between precision and recall (0.94–0.97), with an average F1-score of 0.95–0.96 and a minimal number of misclassifications. These results confirm that employing a more complex ANN architecture can deliver highly accurate predictions of customer satisfaction. The implementation of ANN-based predictive models not only enhances passenger experience quality but also strengthens customer loyalty and helps airlines maintain long-term competitiveness.
ETL Pipeline with DTO Normalization for IPOS Data Integration in Spring Boot Nugroho, Adhi Septian; Susetyo, Yeremia Alfa
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6850

Abstract

IPOS point-of-sale software, widely used by Indonesian small and medium retail enterprises (UMKM), exports transaction data as Excel files with no enforced schema—producing format-variable, multi-row receipt blocks with heterogeneous date representations, locale-dependent numeric formats, and embedded unit strings that resist conventional relational import. Transforming these unstructured exports into a relational database requires a structured architectural approach capable of handling format variability, type inconsistency, and record duplication. This study designs and implements a Spring Boot-based ETL (Extract, Transform, Load) service that applies the Data Transfer Object (DTO) pattern through ten purpose-specific DTO classes covering each pipeline phase, structured within a four-layer Model-View-Controller (MVC) architecture (Controller-Service-Repository-Entity). The Extractor employs a streaming Excel reader with dynamic column-layout detection based on header keywords, producing raw String-typed ExtractedReceipt and ExtractedItem DTOs. The Transformer applies six normalization steps via four utility classes—StringNormalizer, DateParser (seven date-format patterns), NumberParser (Indonesian and Western currency formats), and a HashSet-based duplicate detector—converting raw strings into typed ValidatedReceipt and ValidatedItem DTOs with explicit error logging. The Loader performs batch inserts per 1,000 records using pre-loaded duplicate sets for O(1) lookup. The pipeline operates asynchronously, returning a jobId immediately while processing continues on a background thread. Functional evaluation across ten scenarios yielded a 100% pass rate, covering valid files, invalid file types, date-format heterogeneity, embedded-unit quantity strings, Indonesian numeric formats, cross-file and intra-file duplicate detection, grand-total reconciliation tolerance, and product-variation tracking. Performance observation shows that files of 200–500 receipts complete within 5–15 seconds. These results indicate that a DTO-centric, explicitly mapped ETL pipeline over Spring Boot MVC provides a maintainable, auditable, and production-ready solution for UMKM retail data integration.
Co-Authors Cantika, Berliana Nala Kejora, Cahyo Bintang Nugroho, Adhi Septian Santoso, Wahyu Aji Suwito, Yoel Dinata