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All Journal TRIMAS: Jurnal Inovasi dan Pengabdian Kepada Masyarakat Journal of Software Engineering and Information System (SEIS) Jurnal Informatika Ekonomi Bisnis
Mulyadi, Iriene Putri
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Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Social Sciences

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Journal : Journal of Software Engineering and Information System (SEIS)

 1 
EKSPLORASI SENTIMEN PENGGUNA X TERHADAP ISU KESEHATAN MENTAL BERBASIS MACHINE LEARNING Rifaldi, Dianda; Famuji, Tri Stiyo; Fanani, Galih Pramuja Inngam; Ramadhan, Fauzan Purma; Mulyadi, Iriene Putri; Saputra, Vanji
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 2 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i2.9594

Abstract

Mental health has become an increasingly relevant topic in the digital era, particularly on social media platforms such as X, which serve as public spaces for expressing opinions and sharing personal experiences. This study aims to analyze public sentiment toward mental health topics on Twitter using the Multinomial Naive Bayes algorithm. Data were collected from tweets containing mental health-related keywords and processed through text cleaning and feature extraction using the TF-IDF method. The classification results showed that the model achieved an accuracy of 71%, with stronger performance in identifying negative sentiment compared to positive sentiment. A WordCloud visualization also revealed the frequent appearance of terms such as “mental,” “health,” “self,” and “disorder,” reflecting the main focus of online discussions. These findings indicate that machine learning-based sentiment analysis is effective in capturing public perceptions of mental health issues on social media. This research is expected to contribute to the development of digital communication strategies and real-time monitoring of psychosocial issues in online spaces.
IMPLEMENTASI K-MEANS MENGUKUR KEPUASAN SISWA TERHADAP PELAYANAN PADA SMKS PELITA RAYA JAMBI Saputra, Vanji; Rifaldi, Dianda; Ramadhan, Fauzan Purnama; Mulyadi, Iriene Putri
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 6 No. 1 (2026)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v6i1.9636

Abstract

Education plays a strategic role in improving the quality of human resources; therefore, the quality of educational services must be continuously evaluated. Student satisfaction is an important indicator in assessing school service quality, as students actas the primary customers of educational services. SMK Swasta Terpadu Pelita Raya Jambi needs to measure student satisfaction to enhance service quality and institutional competitiveness.This study applies a data mining approach using the K-Means Clustering algorithm to analyze student satisfaction with school services. Data were collected through questionnaires distributed to 319 students using a Likert scale. The measurement of student satisfaction was based on five service quality dimensions: tangibles,reliability, responsiveness, assurance, and empathy. The research stages included data collection, data cleaning, data transformation, and data processing using both manual calculations and SPSS software.The results indicate that student satisfaction data were grouped into three clusters. The first cluster consisted of 183 students who were satisfied with school services, the second cluster included 30 students who were moderately satisfied, and the third cluster comprised 106 students who were dissatisfied. The clustering results obtained using SPSS showed a similar pattern, although slight differences in cluster membership occurred due to random centroid initialization.In conclusion, the K-Means algorithm effectively clusters student satisfaction levelsand provides valuable insights for school management. The clustering results can serve as a basis for evaluating and improving service quality to enhance student satisfaction at SMK Swasta Terpadu Pelita Raya Jambi
PENERAPAN E-COMMERCE DENGAN METODE CRM BERBASIS WEBSITE PADA TOKO BATAVIA COLLECTION Mulyadi, Iriene Putri; Yaasin, Muhammad; Rahman, Fadil Aulia; Rifaldi, Dianda; Ramadhan, Fauzan Purma; Saputra, Vanji
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 6 No. 1 (2026)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v6i1.9736

Abstract

Website-based e-commerce is a crucial strategy for increasing transaction efficiency and fostering stronger relationships with customers, especially in the fashion sector. Among the fashion brands, Batavia Collection uses digital systems with Customer Relationship Management (CRM) integration to make it easier for customers to access product information, conduct online transactions, and communicate wirelessly with customers. The waterfall method is used to build the system, covering the phases of requirement analysis, system design, implementation, and pengujian. CRM integration is useful for managing customer data, supporting sales activities, and expanding personal services. According to the study's findings, operational efficiency has increased, customer satisfaction, and the potential for more extensive market expansion. This system also aids in more systematic promotion and pelaporan processes. The implementation of CRM-based e-commerce can increase Batavia Collection's sales and service quality.
Co-Authors Dianda Rifaldi Fanani, Galih Pramuja Inngam Indrayani Irwandi Rizki Putra Niswah , Muhlisahtun Rahman, Fadil Aulia Ramadhan, Fauzan purma Ramadhan, Fauzan Purnama Saputra, Vanji Tri Stiyo Famuji Yaasin, Muhammad Yulandari, Mesy