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All Journal Jurnal Abdi: Media Pengabdian Kepada Masyarakat Abimanyu: Journal of Community Engagement Journal of Informatics and Computer Science (JINACS) ABDIMASY: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Jurnal Ilmu Ekonomi, Pendidikan dan Teknik (IDENTIK) Journal of Emerging Information Systems and Business Intelligence (JEISBI)
Aries Dwi Indriyanti
Universitas Negeri Surabaya
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Sentiment Analysis of Public Figures on X Using Naïve Bayes and SVM Muhammad Hashfiudin Tridharma Putra; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 2 (2026): Vol. 07 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i2.72943

Abstract

The rapid growth of social media has created an open public space where users freely express opinions toward public figures, generating positive, negative, and neutral sentiments. Platform X [Formerly Twitter] is one of the most widely used media for public discourse in Indonesia. This study analyzes public sentiment toward the Regent of Sidoarjo for the 2021–2024 period, Ahmad Muhdlor Ali, using sentiment classification techniques. The research applies two machine learning algorithms, namely the Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM), to identify and compare their performance in sentiment analysis. Data were collected through web scraping using relevant keywords and processed in Google Colab. A quantitative research approach was employed using the SEMMA framework, which consists of Sample, Explore, Modify, Model, and Assess stages. The process included data cleaning, text preprocessing, sentiment labeling, and classification using both algorithms. Model performance was evaluated using accuracy, precision, and recall metrics. The results show that both NBC and SVM perform well in classifying public sentiment, achieving high accuracy levels. However, differences in performance were observed between the two methods, indicating that algorithm selection influences classification outcomes. This study contributes to the evaluation of public perception toward government officials and provides a reference for the development of sentiment analysis systems based on social media data.
Enhancing Business Continuity Through Proactive Information System Risk Management in the Financial Services Sector M. Desfreezal Zurarah Bartien; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 1 (2026): Vol. 07 Issue 01
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i1.73009

Abstract

PT XYZ, a company operating in the financial services sector, heavily relies on its colection information system to maintain smooth business operations. In line with the company's strategic plan to conduct a vendor migration for this system, a comprehensive risk analysis becomes crucial to ensure data security, regulatory compliance, and business continuity. This study aims to analyze the risks within PT XYZ's colection information system using a combined approach of the Operationally Critical Threat, Asset, and Vulnerability Evaluation (OCTAVE) and Failure Mode & Effect Analysis (FMEA) methods. The OCTAVE method was systematically applied to identify relevant critical assets, threats, and vulnerabilities. Subsequently, the FMEA method was implemented to quantitatively evaluate the identified risk scenarios to determine their priority levels. The study successfully identified a range of fundamental critical assets across data, system, and brainware categories, and formulated numerous associated risk scenarios. Through the FMEA assessment, these scenarios were classified by their priority level, with a portion identified as high-risk requiring immediate attention. For these high-priority risks, this research recommends actionable mitigation strategies based on controls from the ISO 27001:2022 standard. This study produces a measurable risk profile that serves as a strategic foundation for PT XYZ to effectively manage information security.
Sales Performance Classification of Promotional Products Using Data Mining Rafli Satria Iswandaru; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 2 (2026): Vol. 07 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i2.75897

Abstract

The objective of this research is to establish a classification model to determine high sales performance promotional products using past sales records. The issue at stake is that it is very hard for business actors to forecast the appearance of high sales promotional products, taking into account different factors, such as product type, price per unit, quantity requested, and sales period. This study, based on a quantitative and experiential manner, makes use of the C4. 5 decision tree algorithms on real transaction data of HERA Promotion during 2024. The data falls into one of two types: "best-selling" and "not-selling" products. The proposed classification model achieved good generalization performance with the test accuracy of 99.48% and 5-fold cross-validation accuracy of 96.77%. Price Unit, Product Name, and Month were the most essential features in classifying products, showing that economic value and seasonal demand are major factors determining whether a product is sold. But when applied to the external data for the first few months of 2025, accuracy fell to 78%, which is a way for them to show that shifts in consumer behavior can drive changes in performance. From a theoretical point of view, this study fills the gap by incorporating the time effects as a dynamic variable into product classification models, which haven't been mentioned much in previous research. For practice, the results also encourage incorporating data-driven classification models within decision support systems to help with stock planning and promotional strategies. More work is warranted to use ensembling techniques and real-time data streams on the generalization ability and adaptability of the models.
Developing Order and Queue Web Systems Using User Centered Design in Diskominfo Mojokerto Ichwan Wahyu Utama; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 1 (2026): Vol. 07 Issue 01
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i1.76064

Abstract

The management of application development services at the Department of Communication and Informatics (Diskominfo) of Mojokerto Regency is still conducted manually, resulting in queue uncertainty and service delays. This study aims to design and implement an online order and queue management website application using the User-Centered Design (UCD) method. This method involves users at every stage of development, including planning, design, implementation, and evaluation. The application was developed using React JS (front-end), Express JS (back-end), and MySQL (database). Evaluation was conducted through usability testing involving 21 respondents from Regional Government Organizations (OPD) of Mojokerto Regency. The results show an average System Usability Scale (SUS) score of 79.41, exceeding the minimum standard score of 68. This indicates that the application is easy to use, efficient, and aligned with user needs.
User-Centered Design Evaluation of ShopeeFood Driver User Interface and Experience Azhari Yudistya Nurrahman; Aries Dwi Indriyanti
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 7 No. 2 (2026): Vol. 07 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v7i2.76127

Abstract

The ShopeeFood Driver application serves as a critical tool for delivery partners in managing orders and navigation. However, initial observations and user interviews conducted in Surabaya identified several usability issues, including the absence of demand visualization (heatmaps), lack of destination-based order filtering, and the inability for drivers to rate customers. This study aims to evaluate and redesign the UI/UX of the ShopeeFood Driver application using the User-Centered Design (UCD) method to enhance operational efficiency and user satisfaction. The research followed the four stages of the UCD process: understanding the context of use, specifying user requirements, producing design solutions, and evaluating against requirements. Data were collected from 30 active delivery partners in Surabaya through observations, semi-structured interviews, and System Usability Scale (SUS) questionnaires. The redesign introduced three key features: an order-demand heatmap, a destination-based (one-way) order filter, and a customer rating system. Post-redesign evaluation demonstrated significant improvements in usability. Effectiveness increased from 82.8% to 100%, while efficiency improved as the average task completion time decreased from 34.7 seconds to 21.7 seconds. Additionally, the average SUS score increased from 66.75 (Marginal/OK) to 87.25 (Acceptable/Excellent). These results indicate that the application of the UCD method successfully addressed operational challenges at the field level and substantially improved the usability of the ShopeeFood Driver application, resulting in a more intuitive and efficient user experience for delivery partners.
Inovasi Smart Green House dalam Mendukung Green Economy dan Produktivitas Pembibitan di Kelompok Tani “Hortikultura Makmur Bersama” Rejosari Tulungagung Aries Dwi Indriyanti; Ahmad Ajib Ridlwan; Yunus; Catur Surya Saputra; Aji Catur Prayogo; Rizdana Galih Pambudi
Jurnal ABDI: Media Pengabdian Kepada Masyarakat Vol. 11 No. 2 (2026): JURNAL ABDI : Media Pengabdian Kepada masyarakat
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/abdi.v11i2.45716

Abstract

The Farmers Group "Horticulture Makmur Bersama" in Rejosari Village, Gondang District, Tulungagung Regency, is one of the leading actors in the horticultural agricultural sector that provides superior vegetable and fruit seeds. The problems faced by the Farmer Group "Makmur Bersama Horticulture" are difficulties in controlling pests and diseases, maintaining the growing environment, and limited resources. Based on the problems faced, the service team provides solutions to solve these problems with the Smart Green House innovation. The differentiator in this innovation is an irrigation device with a movable concept. The method used in this service activity consists of problem identification, needs analysis, design/development, manufacturing and testing, training, implementation, monitoring and evaluation. The results of this service showed that the production of plant seeds increased by an average of 36%. The use of Smart Green House can control pests more effectively and reduce the excessive use of pesticides. This bright greenhouse has temperature, air humidity, soil moisture, and light sensors integrated with IoT. Based on this service activity, the importance of technology integration in a sustainable agricultural sector in supporting the green economy can be concluded. Smart Green House can contribute to food security and empower farmers to manage their agriculture modernly.
Implementasi Sistem Informasi Perpustakaan pada Sekolah Indonesia Davao Filipina Menggunakan CMS SLiMS Bonda Sisephaputra; I Kadek Dwi Nuryana; Aries Dwi Indriyanti; Ghea Sekar Palupi
Abimanyu : Jornal of Community Engagement Vol 6 No 2 (2025): August 2025
Publisher : Universitas Negeri Surabaya

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Abstract

This community service aims to develop a Library Information System at Indonesian School of Davao, Philippines, to improve the efficiency of library management and the accessibility of learning resources for students and teachers. The system was built using the Content Management System (CMS) SLiMS, an open-source platform designed for managing library operations digitally, including inventory recording, book lending, and returns. In implementing this Community Service Program (PKM), the methods used to address the problems at Indonesian School of Davao (SID) were the Diffusion of Science and Technology (Ipteks) and Training. This activity also involved continuous evaluation to ensure the success of the program. The results showed increased efficiency in library management, easier access to information, and improved skills of library staff in using CMS SLiMS. In conclusion, the application of information technology through CMS SLiMS in the library of Indonesian School of Davao has contributed positively to enhancing the teaching and learning process.
Analisis Kepuasan Pengguna Website Baznas Kota Surabaya Menggunakan Metode Webqual 4.0 dan Importance Performance Analysis (IPA) Fattah Bima Maulana; Aries Dwi Indriyanti
Journal of Informatics and Computer Science (JINACS) Vol. 7 No. 03 (2026)
Publisher : Universitas Negeri Surabaya

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Abstract

Abstrak—Website BAZNAS Kota Surabaya berperan sebagai sarana penyedia informasi, transparansi, dan layanan zakat digital bagi masyarakat. Namun demikian, efektivitas website tersebut dalam memenuhi kepuasan pengguna perlu dievaluasi secara sistematis. Penelitian ini bertujuan untuk menganalisis tingkat kepuasan pengguna website BAZNAS Kota Surabaya berdasarkan dimensi usability, information quality, dan service interaction quality menggunakan metode WebQual 4.0, serta menentukan prioritas perbaikan layanan melalui pendekatan Importance Performance Analysis (IPA). Penelitian ini menggunakan pendekatan kuantitatif deskriptif dengan subjek penelitian sebanyak 30 responden yang terdiri atas muzakki dan mustahik. Pengumpulan data dilakukan melalui kuesioner skala Likert lima tingkat, wawancara, dan studi pustaka. Instrumen penelitian dinyatakan reliabel dengan nilai Cronbach’s Alpha sebesar 0,822 dan terdiri atas 20 butir pernyataan yang valid. Teknik analisis data meliputi uji asumsi klasik, analisis regresi linier berganda, uji t, uji F, analisis kesenjangan (gap), dan IPA. Hasil penelitian menunjukkan bahwa secara parsial hanya variabel usability yang berpengaruh signifikan terhadap kepuasan pengguna dengan nilai signifikansi sebesar 0,021, sedangkan information quality dan service interaction quality tidak berpengaruh signifikan. Secara simultan, ketiga variabel tersebut berpengaruh signifikan terhadap kepuasan pengguna. Analisis gap menunjukkan adanya kesenjangan negatif terbesar pada dimensi usability. Selanjutnya, hasil IPA menempatkan atribut navigasi, tampilan antarmuka, dan fitur umpan balik sebagai prioritas utama perbaikan. Dengan demikian, peningkatan kualitas website perlu difokuskan pada aspek kemudahan penggunaan dan interaksi layanan untuk meningkatkan kepuasan pengguna.   Kata Kunci— kepuasan pengguna, WebQual 4.0, Importance Performance Analysis, BAZNAS Kota Surabaya.
Studi Komparasi Arsitektur GoogLeNet dan CNN untuk Klasifikasi Gambar Penyakit Daun Mangga M. Alfan Tsalits; Aries Dwi Indriyanti
Journal of Informatics and Computer Science (JINACS) Article In Press
Publisher : Universitas Negeri Surabaya

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Abstract

Abstrak— Penyakit daun mangga secara signifikan mempengaruhi produktivitas pertanian, sehingga diperlukan sistem identifikasi otomatis dan efisien. Penelitian ini bertujuan untuk melakukan studi komparasi antara arsitektur Convolutional Neural Network (CNN) konvensional dengan arsitektur GoogLeNet dalam mengklasifikasikan delapan kategori kondisi daun mangga. Metodologi penelitian ini menggabungkan pendekatan SEMMA (Sample, Explore, Modify, Model, Assess) untuk tahapan pengembangan model, serta metode RAD (Rapid Application Development) untuk tahapan implementasi sistem dashboard berbasis website. Hasil eksperimen menunjukkan bahwa GoogLeNet mengungguli CNN konvensional, mencapai akurasi validasi yang lebih tinggi sebesar 90,68% dan loss validasi yang lebih rendah sebesar 0,2580, dibandingkan dengan akurasi CNN sebesar 89,55% dan loss 0,3309. Selain aspek akurasi, GoogLeNet jauh lebih efisien secara komputasi karena hanya menggunakan 2,87 juta parameter sementara CNN konvensional memerluka hingga 25,8 juta parameter. Melalui implementasi sistem yang telah dibangun, model terbaik mampu menyajikan hasil diagnosis penyakit dan nilai confidence score secara real-time. Kata Kunci— Penyakit Daun Mangga, Deep Learning, Convolutional Neural Network, GoogLeNet, Klasifikasi Citra.
Peningkatan Literasi Etika Artificial Intelligence (AI) bagi Guru SMP Negeri 18 Gresik Rahadian Bisma; Ghea Sekar Palupi; Anggraeni Widya Purwita; Aries Dwi Indriyanti
Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Vol 05 No 02: Oktober 2026 (in progress)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.adipati.2026.v5i2.8642

Abstract

Kegiatan Pengabdian kepada Masyarakat (PkM) bertema “Penggunaan Artificial Intelligence (AI) secara Beretika untuk Pembelajaran” telah dilaksanakan oleh tim dosen Program Studi Sistem Informasi Universitas Negeri Surabaya (UNESA) di SMP Negeri 18 Gresik dengan tujuan meningkatkan literasi digital dan kapasitas guru dalam memanfaatkan teknologi AI secara bijak, kreatif, dan bertanggung jawab. Workshop interaktif selama tiga jam ini mengenalkan berbagai aplikasi AI seperti ChatGPT, Canva AI, Quillionz, dan DALL·E yang dapat digunakan untuk pembuatan soal, desain media pembelajaran, serta asesmen otomatis. Selain aspek teknis, pelatihan menekankan pentingnya etika AI dengan mengacu pada prinsip UNESCO (2021) dan OECD (2023), meliputi tanggung jawab, privasi data, keadilan, transparansi, dan akuntabilitas. Guru dilatih memahami AI Ethics Literacy melalui studi kasus bias algoritmik, penerapan human-in-the-loop, dan integritas akademik. Kegiatan berbasis collaborative workshop ini menghasilkan rancangan RPP sederhana yang mengintegrasikan etika digital, serta meningkatkan kesadaran peran guru sebagai agen pembentuk kepekaan digital siswa. Program ini mencerminkan komitmen UNESA dalam memperkuat literasi AI dan mendorong transformasi digital pendidikan melalui riset dan pengabdian yang berfokus pada etika dan tata kelola teknologi pembelajaran
Co-Authors Ahmad Ajib Ridlwan Aji Catur Prayogo Anggraeni Widya Purwita Arisni Kholifatu A.S Azhari Yudistya Nurrahman Bonda Sisephaputra Catur Surya Saputra Chusnul Nuur Fadillah Davin Putra Febriansyah Desando Anugrah Ramadhan Fadhilah Shabuhalaika Aliyya Farah Nabilah Ardana Fattah Bima Maulana Ghea Sekar Palupi Hafidz Aqilla Herlambang Haris Supratno I Kadek Dwi Nuryana, I Kadek Dwi Ichwan Wahyu Utama Khoirul Anas Khonsa Aziza Almash M. Alfan Tsalits M. Desfreezal Zurarah Bartien Mochammad Chafithul Ngulum Muhammad Hashfiudin Tridharma Putra Nadia Nur Thahirrah Rafli Satria Iswandaru Rahadian Bisma Raharjo, Resdianto Permata Rizdana Galih Pambudi Yemi Fitriana Yonathan Setiagita Yunus