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All Journal YUDISIA : Jurnal Pemikiran Hukum dan Hukum Islam SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi Jurnal An-Nur Seminar Nasional Teknologi Informasi Komunikasi dan Industri Jurnal Sistem Informasi dan Informatika (SIMIKA) Journal of Informatics, Electrical and Electronics Engineering INOVTEK Polbeng - Seri Informatika
Arif Marsal
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Religion Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences Other

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Pengukuran Retensi Pelanggan Insyira Oleh-Oleh Berdasarkan Analisis Sentimen Pengguna Instagram Fiki; Inggih Permana; Febi Nur Salisah; Eki Saputra; Arif Marsal
Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v4i4.2473

Abstract

Instagram as a social media platform has opened new opportunities for businesses to market their products creatively and efficiently. Through interactive features such as the comments section, users can express their opinions about the products or services offered. These comments contain sentiments that can be analyzed to understand customer perceptions. This study aims to measure customer retention using sentiment analysis of Instagram user comments. The comment data was collected using web scraping techniques from the Instagram page, followed by labeling using a lexicon-based approach and sentiment classification into positive, negative, and neutral categories through sentiment analysis. This analysis is linked to the concept of customer retention, which is an important strategy for maintaining long-term relationships with consumers. Furthermore, the results of customer retention analysis in this study show that positive sentiment has a retention rate of 53.4% (303 out of 567 comments), neutral sentiment 6.9% (45 out of 650 comments), and negative sentiment 15.1% (22 out of 146 comments). Overall, 370 out of 1,363 comments, or 27.1%, were categorized as contributing to retention. In terms of the proportion of sentiment contributing to total retention, positive comments dominate with 81.9% (303 out of 370). These findings suggest that although neutral comments are the most frequent, positive sentiment contributes the most to customer retention. This indicates that positive sentiment is a strong predictor of customer loyalty, highlighting the importance for companies to foster positive experiences through quality products, reliable services, and active engagement on social media. Insyira is capable of maintaining customer retention, especially from those who express positive sentiment, which reflects satisfaction with its products, services, and interactions on social media
Pengukuran Akuisisi Pelanggan Insyira Oleh-Oleh Berdasarkan Analisis Sentimen Pengguna Instagram Wira Mulia, M. Roid; Inggih Permana; Febi Nur Salisah; Eki Saputra; Arif Marsal
Journal of Informatics, Electrical and Electronics Engineering Vol. 4 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jieee.v4i4.2472

Abstract

Social media, especially Instagram, has transformed how businesses interact with customers and market products. However, there remains a literature gap regarding customer acquisition measurement through sentiment analysis of Instagram comments. This research aims to measure customer acquisition at Insyira Oleh-Oleh Pekanbaru by analyzing 1,363 comments from May 2024 to May 2025 using Python-based Natural Language Processing (NLP). The results show neutral sentiment dominates (47.7%) with the highest acquisition rate (50.9%) - meaning every 2 neutral comments yield 1 acquisition - compared to positive (37.7%) and negative comments (41.8%). The Chi-square test confirms the significant relationship between sentiment and acquisition (?²=21.78; p<0.0001), while (OR=0.58; CI[0.46,0.73]) indicates positive comments have 42% lower acquisition probability than neutral ones, forming triangular consistency that eliminates doubts. Negative sentiment also yields higher acquisition than positive sentiment, challenging the assumption that positive comments are most effective for acquisition. This reveals neutral comments containing product inquiries have greater acquisition potential. The study provides new insights for digital marketing strategy, emphasizing the importance of quick responses to neutral comments to enhance new customer conversion.
User Experience Evaluation of e-Puskesmas in Payakumbuh City using the User Experience Questionnaire Method Furqan Anwari; Eki Saputra; Arif Marsal; Mona Fronita; Muhammad Jazman; Syafril Siregar
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/z7dkt524

Abstract

Puskesmas in Indonesia are responsible for providing primary health services to the local community. The Community Health Centers (Puskesmas) in Indonesia utilise e-Puskesmas, a web-based system that enables electronic data management and patient services. The newest version, e-Puskesmas Next Generation (NG), was made to allow online interactions, but it has had some technical problems, including duplicate medical data and wrong medication dosages because it doesn't have an allergy detection feature. The UEQ method will be used to rate the user experience of e-Puskesmas. The UEQ measures six factors: attractiveness, efficiency, perspicuity, dependability, stimulation, and novelty. Twenty-one people participated in the evaluation, and the results show that all variables were close to neutral. This means that using the system doesn't make people very happy or sad, but instead stays at an average level. This study confirms that, although e-Puskesmas has the potential to be an effective tool, there is still significant room for improvement, especially in terms of feature customisation and user interface. The "poor" score in the benchmark evaluation indicates that significant improvements in the system's design and functionality are necessary to enhance user satisfaction and healthcare service efficiency. It is hoped that these findings can encourage further development that addresses the existing shortcomings and effectively improves the management of health services at the community health centre
OPTIMALISASI STRATEGI PROMOSI BERDASARKAN WAKTU DAN JENIS PRODUK MENGGUNAKAN ALGORITMA FP-GROWTH Arifah Fadhila Andaranti; M. Afdal; Inggih Permana; Muhammad Jazman; Arif Marsal
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 2 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v8i2.4016

Abstract

Aba Mart is a convenience store that provides a wide range of daily necessities. One of the challenges faced by Aba Mart is the uncertainty in determining the optimal timing for product promotions. To address this issue, this study utilizes sales transaction data obtained from the store’s Point of Sale (POS) system, totaling 12,887 transactions recorded from March to August 2024. The dataset includes attributes such as date and product name, which were processed through attribute selection, categorization into 33 product types, conversion of dates to days, and transformation into boolean format for analysis. The study applies the Association Rule Mining (ARM) technique using the Frequent Pattern Growth (FP-Growth) algorithm to identify the relationship between the time of purchase and the types of products bought. The results demonstrate that the FP-Growth algorithm successfully identified patterns of association. By testing with minimum support values of 2%, 3%, and 4%, and a minimum confidence of 10%, the analysis produced 15 association rules in March, 11 in April, 14 in May, 13 in June, 11 in July, and 13 in August 2024. These rules have been used as a foundation for formulating more effective and targeted promotional strategies for Aba Mart.
Co-Authors Anisah Fitri Arifah Fadhila Andaranti Bambang Tetuko Eki Saputra Fauzan Luthfi Yaumul Adha Febi Nur Salisah Fiki Fitri Hidayati Furqan Anwari Idria Maita Inggih Permana M. Afdal Megawati Megawati Mona Fronita Muhammad Jazman Muhammad Luthfi Hamzah nanda kusuma Rice Novita Suci Ayu Mawarni Sutoyo Sutoyo Syafril Siregar Wira Mulia, M. Roid Zarnelly Zarnelly