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All Journal Jurnal Teknologi Dan Sistem Informasi Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) ABIDUMASY : Jurnal Pengabdian kepada Masyarakat Jurnal Abdimas Kartika Wijayakusuma Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Journal of Informatics and Computer Science (JINACS) TAKSONOMI Journal of Emerging Information Systems and Business Intelligence (JEISBI) Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi
Aries Dwi Indriyanti, Aries Dwi
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Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Rancang Bangun Aplikasi Penjualan Dan Pembelian Berbasis Website Untuk UMKM Studi Kasus PT EDII Putra Hadi, Affan Adyatma; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 1 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i1.58764

Abstract

Rancang Bangun Sistem Informasi Aplikasi Bank Sampah Menggunakan Framework Laravel Berbasis Website (Studi Kasus : Desa Mekarsari, Jimbaran) Akasa, Dinda Fatika; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 1 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i1.58765

Abstract

Mekar Sari Jimbaran Village Waste Bank is environmental organizations working in the health sector environment. This activity is carried out by representatives local environmental communities and customers. Garbage bank at Mekar Sari Village is registered in the savings book. Taking citizens' savings cannot be implemented directly, However, it is implemented once and can be withdrawn at any time if necessary. When processing waste bank data, archived documents are still messy, handwritten, and the text is not clear. This often results in errors and loss of data on citizens' savings cycles. This research discusses the development of bank website applications with waste using the Rapid Application Development Method (RAD) as well as deploy system level reception through Technology Acceptance Model (TAM). This website aims to simplify the process of waste management, driving community participation, and increasing transparency finance in the waste bank system. The RAD method is used to speed up the development process with an approach iterative and responsive to user feedback. Results development includes member registration features, transaction management, financial reporting, management systems rewards, and integration with social media.
Rancang Bangun Aplikasi Pemakaian Ruangan Perkuliahan Pada Fakultas Teknik di Universitas Negeri Surabaya Berbasis Website Menggunakan Metode Greedy Prakosa, Daniel Dhian; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 1 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i1.59016

Abstract

Dalam era perkembangan teknologi informasi yang pesat, berbagai aplikasi telah diciptakan untuk memenuhi kebutuhan manusia, memberikan kemudahan akses informasi global, dan mendukung dunia pendidikan. Fakultas Tenik pada Universitas Negeri Surabaya berupaya menerapkan digitalisasi dengan Sistem pemakaian ruangan perkuliahan. Penelitian ini mengembangkan aplikasi pemakaian ruangan perkuliahan yang memungkinkan Dosen dan Tata Usaha berpartisipasi dalam proses. Metode pengembangan Waterfall digunakan dalam penelitian ini, melalui tahap perencanaan, desain, pembuatan kode, pengujian, implementasi dan pemeliharaan. Aplikasi ini menggunakan Laravel dan memanfaatkan UML dalam perancangan. Terdapat fitur-fitur untuk mengelola data dosen, ruangan, kelas, program studi, mata kuliah, dan mengelola jadwal perkuliahan. Uji Blackbox Testing dilakukan oleh Tata Usaha untuk memvalidasi fungsionalitas aplikasi. Hasil penelitian menunjukkan bahwa aplikasi pemakaian ruangan perkuliaha dengan Metode Greedy dapat membantu dalam pengomptimalkan penggunakan ruangan perkuliahan dan meningkatkan efektivitas serta efisiensi ruangan perkuliahan. Dengan demikian, aplikasi ini berpotensi membawa manfaat bagi Fakultas Teknik dalam sistem pemakaian ruangan perkuliahan.
Forecasting Cookies Sales at the "Sweetnest" Business Using the Simple Moving Average Method: Peramalan Penjualan Cookies pada Usaha Cookies Sweetnest Menggunakan Metode Simple Moving Average WIDI, KINASIH; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 2 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i2.60220

Abstract

Perbandingan Algoritma Naive Bayes dan Support Vector Machine dalam Analisis Sentimen Aplikasi teman Bus: Perbandingan Algoritma Naive Bayes dan Support Vector Machine dalam Analisis Sentimen Aplikasi teman Bus Soraya, Fitri Aurellia; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 2 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i2.60358

Abstract

Penelitian ini mengevaluasi performa dua algoritma klasifikasi, yakni Naïve Bayes dan Support Vector Machine (SVM), dalam analisis sentimen ulasan pengguna terhadap aplikasi Teman Bus di Google Play store. Meskipun kedua algoritma ini telah digunakan pada analisis sentimen pada penelitian sebelumnya, belum ada studi yang secara langsung membandingkannya dalam konteks aplikasi Teman Bus. Analisis sentimen ini melibatkan pemrosesan teks dan klasifikasi sentimen untuk menilai respons pengguna terhadap layanan bus tersebut. Hasil perbandingan mengungkapkan perbedaan performa antara Naïve Bayes dan Support Vector Machine pada klasifikasi sentimen. SVM dengan kernel RBF menunjukkan akurasi sebesar 85%, lebih baik dalam menangani pola sentimen yang kompleks dan tidak linier dibandingkan dengan Naïve Bayes yang mencapai akurasi 82%, khususnya pada dataset dengan rasio pembagian data 30:70. Penelitian ini memiliki tujuan agar memberikan informasi yang lebih mendetail mengenai evaluasi pengguna terhadap layanan Teman Bus menggunakan ulasan yang ditemukan di Google Play store serta memberikan wawasan berguna untuk memilih algoritma yang tepat dalam tugas serupa di masa depan. SVM dengan kernel RBF cenderung menjadi pilihan yang lebih baik untuk analisis sentimen aplikasi Teman Bus, meskipun pemilihan algoritma terbaik tetap bergantung pada konteks dan karakteristik data yang ada.
ANALISIS PERBANDINGAN METODE NAÏVE BAYES DENGAN C45 UNTUK MENGUKUR TINGKAT KEPUASAN MAHASISWA Saputra, Kresna Yudha Bayu; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 3 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i3.63707

Abstract

Penelitian ini bertujuan untuk membandingkan klasifikasi Data di Kelompok Informatika Universitas Negeri Surabaya memakai dua teknik berbeda, yaitu Naïve Bayes dan C4.5, untuk mengukur tingkat kepuasan mahasiswa terhadap pembelajaran tatap muka. Kepuasan mahasiswa menjadi indikator penting dalam menilai mutu kesempatan belajar serta efektivitas strategi pengajaran. Data dari survei kepuasan mahasiswa dapat dianalisis lebih mendalam menggunakan algoritma C4.5 dan Naïve Bayes. Dalam desain penelitian ini, 150 mahasiswa akan memberikan jawaban mereka pada kuesioner yang mencakup berbagai aspek terkait pendidikan mereka, seperti kehadiran, partisipasi dalam diskusi, fasilitas, kualitas pembelajaran, dan layanan sistem informasi. Kedua metode tersebut digunakan untuk menganalisis data yang terkumpul guna menentukan nilai f1-score, akurasi, presisi, dan recall dari masing-masing metode tersebut. The research results show that the C4.5 algorithm has an accuracy rate of 97.33%, which is superior in handling student satisfaction data classification compared to Naïve Bayes which has an accuracy of 91.33%, especially on datasets with a data sharing ratio of 20:80. These findings provide valuable insights for educational institutions in choosing appropriate analytical methods for evaluating student satisfaction. Thus, the results of this research can be used as a basis for decision making in an effort to improve the quality of offline learning in the university environment.
PENERAPAN METODE K-NEAREST NEIGHBOR (K-NN) UNTUK PREDIKSI PENJUALAN PAKAIAN (STUDI KASUS: UMKM KRESNA) Rahmawati, Lutvia; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 3 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i3.64064

Abstract

Sentiment Analysis of 2024 Election Fraud Using SVM and Naïve Bayes Algorithms Hilmi, Faalih Hibban; Indriyanti, Aries dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 4 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i4.64703

Abstract

Elections are one of the main pillars of democracy, where the people's voice is the main determinant in government formation. Election fraud not only harms political competitors but also undermines public trust in democracy. The role of social media Twitter in widely disseminating information and disinformation adds to the challenge of maintaining election integrity. Sentiment analysis is the process of collecting and understanding individual opinions related to an event. Support Vector Machine (SVM) and Naïve Bayes algorithms are often used in this analysis due to their effectiveness and efficiency in text classification. This research aims to analyze public sentiment related to the 2024 presidential election fraud and compare the effectiveness of SVM and Naïve Bayes in sentiment classification. The study was conducted quantitatively, involving the stages of data collection, preprocessing, labeling, TF-IDF weighting, classification, and evaluation. The results of the sentiment analysis of public opinion on the 2024 presidential election fraud showed 42.5% negative sentiment, 38.6% neutral, and 18.9% positive. The dominance of negative sentiments reflects the public's concerns about election integrity. The high neutral sentiment indicates public doubt. To overcome this, transparency, strengthening supervisory institutions, electronic election technology, and strict law enforcement are needed. The SVM algorithm with RBF kernel produces 58% accuracy, better than Naïve Bayes with 51%.
Software Quality Evaluation Of MV5PAS Airport Authority Region III Using FURPS Model: Software Quality Evaluation Of MV5PAS Airport Authority Region III Using FURPS Model Suhartono, Darell Timotius; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 1 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i1.64722

Abstract

The widespread use of software to enhance organizational efficiency makes software development essential. The Airport Authority Region III Office uses MV5PAS software for operational activities, aiming to improve public services. Ensuring software quality is crucial for optimal performance, which this study evaluates using the FURPS model. This model assesses software based on five characteristics: functionality, usability, reliability, performance, and supportability.The study employs a mixed-method evaluation approach. Functionality and usability are assessed via a questionnaire with 25 respondents, while reliability is tested using WAPT V.10.1. Performance is measured with GTMetrix web analysis, and supportability is tested across different OS and browsers.Results indicate that MV5PAS meets the FURPS model standards in four categories. Functionality scores 0.983 (0 ≤ X ≤ 1), reliability achieves R = 0.982, usability scores 80.2, and supportability is confirmed through successful multi-device testing. However, performance requires improvement, receiving a “D” on the GTMetrix Grade. This highlights the need for quality enhancements to optimize the system’s overall efficiency.
Analysis of Factors Influencing Acceptance of the Online Population Administration Information System in Mojokerto Regency Using Technology Acceptance Model (TAM 3) AYER, FIDIANTI RAMADANI SUHADI; Indriyanti, Aries Dwi
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 4 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i4.65853

Abstract

This research investigates factors influencing the acceptance of the POSKeTanMu online population administration system in Mojokerto Regency using the Technology Acceptance Model (TAM 3). POSKeTanMu (Pelayanan Online Sistem Kependudukan Tanpa Ketemu) is a self-service online population administration system for residents of Mojokerto Regency. A quantitative approach with Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied, analyzing data from 159 respondents through questionnaires. Findings indicate that Behavioral Intention (BI) significantly influences user independence and responsibility. Key factors affecting technology acceptance include perceived usefulness, ease of use, social influence, and experience, while computer anxiety and system usability showed no significant impact. Additionally, the study explores the implementation of the Double Track program using a qualitative case study approach, guided by Thomas Lickona’s character-building theory. Data collection involved interviews, observations, and documentation, analyzed using Miles and Huberman’s framework. Results highlight ease of use, perceived benefits, and social perceptions as major drivers of technology adoption. Positive user experiences and social support play crucial roles in enhancing e-government adoption. This research contributes to the development of POSKeTanMu and provides strategic recommendations for the government to strengthen digital service implementation. Findings offer valuable insights for policy formulation to improve e-government services and promote broader technology adoption in society.
Co-Authors Abda Abda Akasa, Dinda Fatika Amalia Putri, Amalia ANITA ANDRIANI, ANITA Asfiah, Asfiah Aulia Rachman, Muhammad Wisnu Aditya Aulia Syalsabila Dian Yahya AYER, FIDIANTI RAMADANI SUHADI Cahyani, Rizka Dwi Eko Sediyono Ernawati, Sulistya Fadhilah, Putri Nur Hadi Sucipto, Hadi Hapsari, Nawang Ambika Hilmi, Faalih Hibban I Gusti Lanang Putra Eka Prismana, I Gusti Lanang Putra Eka I Kadek Dwi Nuryana, I Kadek Dwi Ibrahim, Moch. Araafi Syamsul Iftitaahul Mufarrihah Indriawan, Fani Kholifatu A.S, Arisni Kholifatu Amalia Shofiani, Arisni Kusuma, Ragil Candra Laili, Elisa Nurul Mahmudah, Alya Choirum Mahrus Ali Mashuri, Chamdan Mauludi, Kartika Mujianto, Ahmad Heru Mursyid, Rabhita Nada, Kirana Meliana Dwi Nur Cholis Majid PADWASIH, ELLEN MARIA Prakosa, Daniel Dhian Pratama, Wahyu Suprayogi Adhyaksa Pratiwi, Juwita Ajeng Pritasari, Octaverina Kecvara Puspaningrum, Hellen Fatima Putra Hadi, Affan Adyatma Raharjo, Resdianto Permata Rahmat Gernowo Rahmawati, Lutvia Reyhana Putri, Adelia Rizma Rizal, Muhammad Fatkhur Robbaniyah, Shibghotur Ayu Safa'ah, Siti Nurhalizatus Saputra, Kresna Yudha Bayu Shofi, Ravita Dinia Sholihah, Rohmatus Soraya, Fitri Aurellia Subandiyah, Heny Suhartono, Darell Timotius Supratno, Haris Supratno, Haris Supratno Tanhella Zein Vitadiar Tasmara, Hasbi Rivanda Thahirrah, Nadia Nur UBAIDILLAH, M FATIH FADLIL UMAR FAUZI Utama, Jihad Satrio Victoria, Margaretha Sarah WIDI, KINASIH Widoyoningrum, Sri Widyaretno, Nabilla Yanti, Risma Novi