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All Journal JIEET (Journal of Information Engineering and Educational Technology) Indonesian Journal of Engineering and Technology (INAJET) Journal of Vocational and Technical Education (JVTE) ICONESTH Journal of Emerging Information Systems and Business Intelligence (JEISBI) Journal of Education Technology and Information System
Ardhini Warih Utami
Universitas Negeri Surabaya
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Neuroscience Nursing Public Health Social Sciences Other

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Rancang Bangun Sistem Informasi Prediksi Masa Tunggu Pekerjaan Alumni Dengan Pendekatan Algoritma Naïve Bayes Lucky Andrean; Ardhini Warih Utami
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 2 (2024): Vol. 05 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i2.60520

Abstract

Efisiensi dan efektivitas sistem pendidikan sangatlah penting untuk kemajuan suatu negara. Evaluasi terhadap kurikulum dan kemampuan menghasilkan lulusan yang siap bersaing di pasar kerja menjadi krusial. Salah satu aspek evaluasi yang signifikan adalah pelacakan data alumni. Data dari pelacakan alumni juga merupakan parameter penting yang digunakan dalam konteks proses akreditasi lembaga pendidikan. Salah satu data pelacakan alumni yang digunakan dalam akreditasi lembaga adalah masa tunggu alumni dalam mencari pekerjaan. Oleh karena itu, tujuan dari penelitian ini adalah untuk merancang bangun sistem informasi berbasis website yang mengimplementasikan metode naïve bayes dan laplace correction untuk memprediksi lama masa tunggu alumni dalam memperoleh pekerjaan pertama. Penelitian ini menggunakan metode pengembangan Rapid Application Development (RAD) yang memiliki beberapa tahapan pengembangan yaitu tahap requirements planning, user design, construction, dan cutover. Pada tahap cutover, dilakukan pengujian terhadap website yang telah dibangun menggunakan metode pengujian Blackbox untuk memastikan fungsionalitas dari sistem. Hasil dari penelitian ini menunjukkan hasil perhitungan sistem memiliki kesamaan dengan hasil perhitungan manual, hal tersebut menunjukan bahwa aplikasi ini dapat dikembangkan dengan menggunakan metode Rapid Application Development (RAD). Hasil perhitungan prediksi menunjukkan bahwa metode naïve bayes dan laplace correction dapat diterapkan untuk memperkirakan waktu tunggu alumni dalam memperoleh pekerjaan pertama. Penerapan laplace correction juga terbukti efektif dalam mengatasi masalah probabilitas akhir yang bernilai 0.
Rancang Bangun Sistem Informasi Pengelolaan dan Pemeliharaan Aset Berbasis Website Pada PT. XYZ Hawa Nur Rahma; Ardhini Warih Utami
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 2 (2024): Vol. 05 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i2.60625

Abstract

Aset adalah benda yang bernilai penting dalam sebuah perusahaan. Aset menjadi kekayaan perusahaan yang harus dikelola dengan baik dan terstruktur agar aset yang dimiliki tetap terjaga nilainya dalam rentan waktu yang lama. Beberapa perusahaan memiliki jumlah aset yang sangat besar, salah satunya yaitu PT. XYZ. Pengelolaan aset pada PT. XYZ masih dilakukan secara manual, sehingga proses pengelolaan menjadi tidak efektif dan efisien. Oleh karena itu dibutuhkan sistem informasi manajemen aset sebagai penyedia informasi manajerial dalam mendukung operasional manajemen aset dan pengambilan keputusan dalam melakukan fungsi perencanaan serta pengendalian. Permasalahan yang sedang dihadapi oleh PT.XYZ menjadi tujuan utama penelitian ini untuk merancang dan membangun sistem informasi pengelolaan dan pemeliharaan aset berbasis website sebagai solusi atas permasalahan PT. XYZ dalam mengelola aset mereka. Metode pengembangan yang digunakan yaitu RAD (Rapid Application Development). Metode RAD terdiri dari Requirement Planning, User Design, Construction, dan Cutover. Pengujian sistem menggunakan Metode Black Box Testing untuk memastikan bahwa fungsionalitas sistem informasi yang dibangun telah berjalan sesuai dengan fungsinya. Hasil penelitian membuktikan bahwa sistem ini mampu membantu PT. XYZ dalam mengelola aset mereka agar aset tersebut dapat terdokumentasi dengan baik secara terkomputerisasi.
Decision Support System for Selecting Cryptocurrency Exchange Platforms Using the Multi Attribute Utility Theory (MAUT) Method Based on a Website: Sistem Pendukung Keputusan Pemilihan Platform Cryptocurrency Exchange Menggunakan Metode Multi Attribute Utility Theory (MAUT) Berbasis Website R. Gading Utama Arsendy Putra; Ardhini Warih Utami
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 2 (2024): Vol. 05 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i2.60691

Abstract

In the rapidly evolving digital era, the financial industry has undergone significant changes with the emergence of cryptocurrency in Industry 4.0. In Indonesia, the number of cryptocurrency holders has increased rapidly, leading to the proliferation of many cryptocurrency exchange platforms to meet the needs of individual traders, financial institutions, investors, and novice users who lack foundational knowledge about blockchain technology or market dynamics. This complexity in choosing the right platform necessitates an effective decision support system. Previous research has proposed decision-making methods such as the Preference Selection Index (PSI) and the Analytical Hierarchy Process (AHP). To enhance the accuracy of platform selection, this study employs the Multi-Attribute Utility Theory (MAUT) and Forward Chaining methods. MAUT enables the assessment of pre-determined criteria and weights, while Forward Chaining simplifies the decision-making process by providing recommendations based on user preferences. By utilizing MAUT and Forward Chaining, this system assists users in understanding the essential aspects of selecting a platform and provides recommendations that align with their preferences and needs. The criteria for this decision-making process are based on a pre-survey conducted within the SGB x Crypto cryptocurrency community, and the MAUT weights and preferences were determined through interviews with cryptocurrency experts. Based on the results of questionnaires and interviews, five main criteria were selected: security with a weight of 0.35 (K1), feature completeness with a weight of 0.2 (K2), customer service quality with a weight of 0.1 (K3), regulation with a weight of 0.2 (K4), and the number and variety of coin assets with a weight of 0.15 (K5). The five evaluated cryptocurrency exchange platforms are Tokocrypto (A1), Pintu (A2), Indodax (A3), Binance (A4), and Bybit (A5). This study results in the implementation of a web-based decision support system for selecting cryptocurrency exchange platforms using MAUT and Forward Chaining. This system helps novice users understand the crucial aspects of choosing a platform and provides recommendations for cryptocurrency exchange platforms that suit their preferences.
Development of a Blast System and Chatbot for Information Dissemination in the IPI Community (Ibu Pembelajar Indonesia) Using the WhatsApp-Web.js Library: Pengembangan Sistem Blast dan Chatbot untuk Penyebaran Informasi di Komunitas IPI (Ibu Pembelajar Indonesia) dengan Menggunakan Library WhatsApp-Web.js Alwan Jauza Rosyad; Ardhini Warih Utami
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 3 (2024): Vol. 05 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i3.61228

Abstract

The research focuses on the development of a blast system and chatbot for disseminating information within the IPI (Ibu Pembelajar Indonesia) Community using the Whatsapp-web.js library. The main objective of this research is to address the limitation of the maximum number of members in a WhatsApp group, which is only 1,024 members, and to disseminate information in a community that has more than 4,000 members. The Rapid Application Development (RAD) method is used in the development of this system, which includes the stages of requirement planning, design, rapid construction, and cutover. The results of the study indicate that the blast system enables admins to disseminate information en masse to all members without having to select numbers one by one, while the chatbot provides automatic interaction and real-time responses to community members. The developed system has proven to be effective in disseminating information quickly and accurately, reducing manual workload, and minimizing the potential for communication errors. Moreover, the implemented chatbot technology has successfully enhanced member engagement and satisfaction through more dynamic interactions and content personalization based on usage data analysis. Nonetheless, this research suggests the development of additional features, enhancement of data security, and training and socialization to ensure optimal system utilization. Further research is needed to evaluate the long-term impact of using this system and to test its scalability in other communities or organizations with complex communication needs.
Analisa dan Permodelan Proses Bisnis pada CV Tekad Jaya Mandiri menggunakan Metode Business Prosess Modelling Notation (BPMN) ari maulana; ardhini warih utami
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 3 (2024): Vol. 05 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i3.62687

Abstract

CV Tekad Jaya Mandiri merupakan percetakan yang punya focus di percetakan metal dan non-metal. Dalam menjalankan proses bisnisnya CV Tekad Jaya Mandiri punya masalah dalam efisiensi pada beberapa proses bisnis yang ada. Jika pada proses bisnis tidak segera diperbaiki maka akan memberi efek buruk karena berkurangnya efisiensi dan menimbulkan dampak buruk untuk Perusahaan. Model proses bisnis dibutuhkan untuk mempermudah dalam memahami proses bisnis yang sedang berjalan saat ini. Pemodelan proses bisnis menggunakan Business Process Model And Notation (BPMN). Dari hasil temuan permasalahan proses bisnis yang terjadi di CV Tekad Jaya Mandiri akan di teliti dan akan diberikan usulan perbaikan yang diharapkan menjadi bahan pertimbang untuk CV Tekad Jaya Mandiri dalam melakukan perbaikan pada proses bisnisnya agar meningkatkan efisiensi dan efektifitas pada CV Tekad Jaya Mandiri.
Rancang Bangun Sistem Informasi Geografis Untuk Optimasi Rute Terpendek Distribusi Produk Dengan Algoritma A-Star (Studi Kasus UD Ali Berkah) Febri Tri Prasetyo; Ardhini Warih Utami
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 5 No. 3 (2024): Vol. 05 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i3.62919

Abstract

Sistem Informasi Geografis (SIG) adalah teknologi komputer yang mengelola dan menyimpan data geografis, dengan kemajuan dalam beberapa dekade terakhir berdampak signifikan pada berbagai bidang, termasuk usaha dagang. SIG dapat menentukan rute terpendek untuk distribusi produk, meningkatkan efisiensi operasional. Algoritma A-Star, yang menggunakan pendekatan heuristic, efektif menemukan jalur terpendek, mengurangi waktu pencarian dan biaya transportasi. Penelitian ini merancang dan membangun SIG untuk optimasi rute terpendek distribusi produk menggunakan algoritma A-Star, dengan studi kasus pada UD Ali Berkah, usaha grosir bahan pangan. Tantangan yang dihadapi UD Ali Berkah meliputi efisiensi pengiriman produk, pemantauan stok, dan pemilihan rute optimal. Pengembangan sistem menggunakan metode Rapid Application Development (RAD), yang terdiri dari tahap Requirement Planning, User Design, Construction, dan Cutover. Pengumpulan data melalui observasi, studi literatur, dan wawancara. Pengujian sistem dilakukan dengan metode White Box dan Black Box Testing. Hasil penelitian menunjukkan bahwa sistem yang dikembangkan mampu mengoptimalkan rute distribusi produk secara efektif dari segi jarak dan waktu tempuh dibandingkan metode manual yang sebelumnya digunakan. Algoritma A-Star terbukti meningkatkan efisiensi distribusi produk UD Ali Berkah, sehingga sistem ini dapat menjadi solusi efektif dalam optimasi operasional usaha dagang.
Decision Support System For Determining The Best Employees To Get Incentives Using The Web-Based Multi Factor Evaluation Process (MFEP) Method Dimas Prananda; Ardhini Warih Utami
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 2 (2025): Vol. 06 Issue 02
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i2.69087

Abstract

One way for companies to enhance employee performance and motivation is by discovering the most effective methods of providing incentives. However, due to the multitude of factors that must be considered, this process is often complex. Therefore, the objective of this research is to create and develop a web-based Decision Support System that employs the Multi-Factor Evaluation Process (MFEP) method to assist in determining the employees who are most deserving of compensation. This research leverages the Rapid Application Development (RAD) methodology, which encompasses several phases: requirements planning, user design, construction, and cutover. During the construction phase, the system was tested using the Blackbox method to ensure that all functions operated correctly without examining the program code. The research findings indicate that the decision support system can recommend the employees who are most eligible for compensation in accordance with company standards. The MFEP method implemented in this system yields unbiased evaluation results by considering various assessment factors. The rapid system development (RAD) method facilitated a swift and structured development process. The results of the Blackbox testing demonstrate that the system operates effectively in line with the established requirements. With this system, it is anticipated that the process of identifying top-performing employees will become more efficient, objective, and transparent. Additionally, this system can enhance employee motivation to achieve the highest levels of performance.
Web-Based Stock Forecasting Application Using Single Exponential Smoothing Method (Case Study: CV. Anugerah Ajitama) Muchammad Ichwan Firdaus; Ardhini Warih Utami
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.v7i2.81896

Abstract

CV. Anugerah Ajitama, a building material distribution company, faces inventory management challenges due to stock determination that is still conducted manually based on subjective estimation. This condition has led to recurring overstock and stockout issues, resulting in increased storage costs, product damage risks, and lost sales opportunities. This study aims to design and develop a web-based inventory forecasting system utilizing the Single Exponential Smoothing (SES) method, as well as to evaluate the forecasting accuracy and system functionality. System development employs the Rapid Application Development (RAD) method, encompassing the stages of requirement planning, user design, construction, and cutover. The research data consists of historical sales data of three main products water tanks, turbine ventilators, and metal roof tiles from the January 2023 to December 2025 period. The forecasting process involves testing alpha values from 0.1 to 0.9 through a trial and error approach, with the best alpha selected based on the smallest Mean Squared Error (MSE), while Mean Absolute Deviation (MAD) serves as supplementary information. The results show that the optimal alpha values are 0.1 for water tanks (MSE: 13.70, MAD: 2.60), 0.2 for turbine ventilators (MSE: 5.12, MAD: 2.02), and 0.3 for metal roof tiles (MSE: 4932.58, MAD: 53.60). The system was successfully implemented as a web-based application built with Laravel and React, featuring product data management, stock realization, sales data management, automated forecasting, report generation, notifications, and role-based access control. Furthermore, functional testing using Black Box Testing across three user roles (Super Admin, Business Owner, and Admin Staff) with a total of 133 test scenarios was successfully executed with a 100% pass rate. Based on these findings, this application can effectively serve as a decision support tool for inventory planning at CV. Anugerah Ajitama.
Design of an Android Application for Leaf Disease Detection in Plants Muhammad Nizam Setiawan; Ardhini Warih Utami; Fauzan Nusyura
Journal of Education Technology and Information System Vol. 2 No. 01 (2026): Journal of Education Technology and Information System (JETIS)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jetis.v2i01.42208

Abstract

Agriculture plays a strategic role in Indonesia's economy, with approximately 29,342,202 individual agricultural enterprises recorded in 2023, according to Statistics Indonesia (BPS). Golokan Village, located in Sidayu District, Gresik Regency, is one of the agrarian areas where 23.22% of the population works as farmers, and it has a total agricultural land area of 385 hectares. However, between 2019 and 2023, there was a significant decline in the production of three main commodities: corn decreased from 302.5tons to 275.6tons, tomatoes from 810tons to 585 tons, and cassava from 1,000tons to 832tons. One of the contributing factors is the difficulty in early detection of plant diseases. To address this challenge, this study designed and developed an Android application called AgroAI utilizing deep learning technology, specifically a Convolutional Neural Network (CNN) model based on the MobileNet architecture optimized with TensorFlow Lite for mobile devices. The development was carried out using the Scrum methodology in two sprints. The first sprint included needs analysis, dataset collection, interface design, and model training. The second sprint implemented the core features such as leaf disease detection via camera or gallery, classification results with recommended solutions, analysis history management, educational articles, and user authentication via Firebase. Black box testing confirmed that all features functioned as intended, while model validation achieved an accuracy of 94.74%. This application is expected to enhance farmers' efficiency in crop management and support the sustainability of both local and national agricultural sectors.
Co-Authors Alwan Jauza Rosyad Anjar Septya Ningrum Ari Kurniawan ari maulana Choirotus Sa’adah Diah Widyaningsih Dimas Prananda Fauzan Nusyura Febri Tri Prasetyo Ghea Sekar Palupi Hawa Nur Rahma Khoirun Arining Azizah Lucky Andrean Moh Zulfikar Rofi Yansyah Muchammad Ichwan Firdaus Muhammad Nizam Setiawan Muhammad Rifqi Ardani Muhammad Zildan Faisal R. Gading Utama Arsendy Putra Yeni Anistyasari Zidan Nurdin Robbi