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All Journal Journal of Information Systems and Informatics Ed-Humanistics : Jurnal Ilmu Pendidikan IJORER : International Journal of Recent Educational Research Jurnal Abdimas Kartika Wijayakusuma Abimanyu: Journal of Community Engagement Berkala Ilmiah Pendidikan Journal of Informatics and Computer Science (JINACS) Data Sciences Indonesia (DSI) Journal of Artificial Intelligence and Digital Business Journal Research of Social Science, Economics, and Management Indonesian Research Journal on Education Scientica: Jurnal Ilmiah Sains dan Teknologi Neraca: Jurnal Ekonomi, Manajemen dan Akuntansi Jurnal Ilmu Ekonomi, Pendidikan dan Teknik (IDENTIK) Media Konstruksi : Jurnal Ilmiah Teknik Sipil Journal of Emerging Information Systems and Business Intelligence (JEISBI) Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi MURAKOM
I Kadek Dwi Nuryana, I Kadek Dwi
Universitas Negeri Surabaya
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Most Desired Product Classification Model For Sales of Women's Sandals Using the Naive Bayes Method (Case Study: UMKM Ann-d'Mello Sandals Krian Sidoarjo) Tifanny Maulida Innayah; I Kadek Dwi Nuryana
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.v5i3.62426

Abstract

A Demand Forecasting Model For Women's Sandals in the MSME Supply Chain Using the Linear Regression Algorithm: A Case Study of Ann-D'Mello Sandals Muchtarotun Novia Ustadha; I Kadek Dwi Nuryana
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.v5i3.62427

Abstract

Ann-D'Mello Sandals faces challenges in production management due to the lack of systematic production planning and reliance on intuition for demand forecasting. This approach results in inaccurate production quantities and potential losses. This research applies the linear regression method to analyze historical demand data for women's sandals and predict future demand. This method allows for the identification of patterns in historical data, aiding MSME like Ann-D'Mello Sandals in optimizing production based on the relationship between variables such as fashion trends, popularity, seasonality, and other economic factors. The aim of this study is to apply a linear regression algorithm to predict future demand for women's sandals and evaluate the accuracy of these predictions. The results indicate that applying the linear regression algorithm to forecast demand over the next 48 weeks shows an upward trend, with predictions reaching over 4,000 pairs by week 248. This demonstrates a promising market potential for women's sandals and can help MSME in planning more effective production and marketing strategies to meet the increasing demand. The evaluation of the linear regression model shows good performance with an Average MAPE value of 2.79 on the training set and 4.65 on the testing set, using a 10-fold Time Series Cross-Validation (TMCV) scenario. The low MAPE values indicate that the model can predict demand with high accuracy. Overall, this linear regression model has proven effective in forecasting demand for women's sandals, providing valuable guidance for MSME to optimize their production and marketing strategies.
Analisis Faktor yang Mempengaruhi Intensi Penggunaan Berkelanjutan terhadap E-Learning UNESA Rohmanialuhri Rengganis; I Kadek Dwi Nuryana
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.v5i3.62435

Abstract

E-learning adalah strategi pembelajaran yang memanfaatkan inovasi dalam data dan komunikasi untuk mengakses dan memfasilitasi pembelajaran. Universitas Negeri Surabaya (UNESA) memperkenalkan e-learning yang dapat diakses melalui Sinau Digital UNESA, namun implementasinya belum optimal. Penelitian ini bertujuan untuk memperjelas faktor-faktor apa saja yang mempengaruhi pengguna dalam terus menggunakan e-learning UNESA.Penelitian ini menggunakan kombinasi penggabungan metode Unified Theory of Acceptance and Use Technology3 (UTAUT3) dengan Expectation Confirmation Model (ECM). Penelitian ini menggunakan data dari 185 responden mahasiswa teknik UNESA yang merupakan pengguna e-learning UNESA. Data tersebut diolah dengan menggunakan metode SEM-PLS dan software SmartPLS 4. Hasil penelitian ini adalah faktor-faktor yang secara signifikan dan menyeluruh mempengaruhi keberlanjutan pemanfaatan e-learning UNESA adalah performance expectancy, facilitating conditions, effort expectancy, personal innovativeness dan habit. Sementara itu, hubungan antara faktor-faktor yang tidak signifikan terhadap intensi penggunaan berkelanjutan e-learning UNESA adalah satisfaction, hedonic motivation, dan social influence.
Analysis of User Satisfaction MELISA using End User Computing Satisfaction (EUCS) and Importance Performance Analysis (IPA) Methods: Analisis Kepuasan Pengguna MELISA menggunakan Metode End User Computing Satisfaction (EUCS) dan Importance Performance Analysis (IPA) Puspita Westi Erlitiya Ningrum; I Kadek Dwi Nuryana
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.v5i3.63646

Abstract

The Ministry of Education and Culture made an innovation by launching the Merdeka Belajar Kampus Merdeka or MBKM program to help students preparing the transformation. To succeed the program, UNESA built a digital service called UNESA MBKM Information System or "MELISA". MELISA has been used since 2022 and only conducted an evaluation in 2023 after which there were improvements by adding several features and changing some of its appearance. In this study, researchers measured the level of user satisfaction of MELISA using the End User Computing Satisfaction (EUCS) and Importance Performance Analysis (IPA) methods. The purpose of this study is to determine the level of user satisfaction of MELISA and to determine the aspects that need to be improved and maintained by MELISA. Data collection was carried out by distributing questionnaires to UNESA students class of 2021. The number of samples used in this study were 153 respondents. The results of this study indicate that the level of user satisfaction based on the gap value obtained negative results on all indicators. Based on the results of the suitability level analysis, the result is 80.0% which includes <100%. Based on these two results, it indicates that MELISA's performance is still unable to meet the expectations of its users or still does not satisfy its users. In addition, based on the interpretation of the IPA diagram, indicators that are included in quadrant I, which means that they really need priority to make improvements, including user friendly (E1), transparency (C4), and suitability (F2).
ANALISIS TINGKAT KEPUASAN DAN PENERIMAAN MAHASISWA TERHADAP SIDIA DENGAN MENGGUNAKAN METODE EUCS DAN TAM Lailatul Mukharromatus Sa'diyah; I Kadek Dwi Nuryana
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.v5i3.63736

Abstract

In the current era of globalization, technological developments in the world of education have created various new features that can help in the teaching and learning process. One implementation is E-learning, which enables the online learning process. Surabaya State University (UNESA) implemented E-Learning specifically for students in 2015 to facilitate teaching and learning activities to be more flexible because the material in UNESA E-Learning can be accessed anytime and anywhere, is easy to understand, saves energy, costs and time. Since 2023, the UNESA Single Sign On (SSO UNESA) Dashboard has changed its appearance and tools. One of the SSO facilities that has undergone changes is UNESA E-learning. Therefore, this research aims to conduct a comprehensive analysis of the level of student acceptance and satisfaction with the use of SIDIA. This analysis will be carried out using the End User Computing Satisfaction (EUCS) and Technology Acceptance Model (TAM) methods. The data collection process was carried out by distributing questionnaires to 100 respondents. Based on the results of the analysis carried out using the EUCS method, the results obtained were that all hypotheses were accepted, namely Content had an effect on user satisfaction, Accuracy had an effect on user satisfication, Timeliness had an effect on user satisfication, Format had an effect on user satisfication, and Ease of Use had an effect on user satisfication . This shows that users are satisfied with SIDIA. Meanwhile, for the TAM method, the results also showed that all hypotheses were accepted, namely Perceived Ease of Use (PEOU) had an effect on Acceptance of IT, and Perceived Ease of Use (PEOU) had an effect on Acceptance of IT. This shows that the user accepts the use of the SIDIA system. Keywords: E-Learning, SIDIA, Satisfaction, Acceptance, Users, EUCS (End user Computing Satisfaction), TAM (Technology Acceptance Model).
ANALISIS KEPUASAN PENGGUNA TERHADAP E-LEARNING UNIVERSITAS NEGERI SURABAYA: ANALYSIS OF USER SATISFACTION WITH E-LEARNING AT UNIVERSITAS NEGERI SURABAYA Jasica Ardana Herviyandasari; I Kadek Dwi Nuryana
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.v5i3.64045

Abstract

Pembelajaran daring atau online telah menjadi bagian integral dari pendidikan di Indonesia, termasuk pendidikan tinggi, terutama di masa pandemi COVID-19. Salah satu metode pembelajaran daring yang banyak digunakan adalah E-Learning. Universitas Negeri Surabaya (Unesa) telah mengimplementasikan E-Learning untuk memfasilitasi proses belajar mengajar jarak jauh. Saat ini, mahasiswa dapat mengakses pendidikan e-learning melalui SIDIA(Sinau Digital UNESA). Kepuasan Penggunaan Sistem E-Learning UNESA diukur dengan menggunakan model End User Computing Satisfaction (EUCS) yang mencakup lima dimensi yaitu akurasi, konten, format, kemudahan penggunaan, dan ketepatan waktu. Pengumpulan data dilakukan dengan menyebarkan kuesioner kepada Mahasiswa Sistem Informasi, angkatan 2022 yang mengikuti mata kuliah Literasi Digital yang berjumlah 150 mahasiswa. Teknik analisa yang digunakan adalah analisis deskriptif. Pada penelitian ini dilakukan 3 uji instrumen yaitu Uji Valilditas, Uji Reabilitas, dan Convergen Validity. Hasil penelitian menunjukkan bahwa secara keseluruhan, mahasiswa merasa puas dengan sistem yang digunakan. Nilai yang memiliki interval tertinggi ada pada indikator Timeliness T1(Kecepatan) yaitu 4,08. Sedangkan yang terendah ada pada indikator Content C2 (Manfaat) yaitu 3,90. Mengindikasikan perlunya peningkatan dalam kualitas dan relevansi konten yang disajikan. Meskipun demikian, beberapa area seperti peningkatan interaktivitas konten dan keandalan server masih memerlukan perhatian lebih untuk memastikan pengalaman pengguna yang lebih optimal di masa yang akan datang. Penelitian ini memberikan wawasan yang berharga bagi pengembangan lebih lanjut dari sistem ELearning di Unesa dan institusi pendidikan lainnya.
Analisis Sentimen Masyarakat terhadap Kebijakan Iuran Tabungan Perumahan Rakyat (Tapera) pada Platform X Menggunakan Algoritma Naïve Bayes Classifier dan Support Vector Machine Anis Maulidatur Rizqiyah; I Kadek Dwi Nuryana
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.v5i3.64074

Abstract

Pemerintah Indonesia menetapkan perubahan terhadap PP Nomor 25 Tahun 2020 tentang Penyelenggaraan Tabungan Perumahan Rakyat (Tapera) melalui PP Nomor 21 Tahun 2024. Dalam perubahan tersebut gaji pekerja Indonesia akan dipotong 3% untuk Tapera. Hal tersebut menimbulkan perdebatan dikalangan masyarakat, terutama pengguna platform X. Pada platform tersebut, masyarakat berbagi opini dan pandangan mereka terhadap kebijakan Tapera. Penelitian ini bertujuan untuk mengklasifikasikan tweet terkait kebijakan Tabungan Perumahan Rakyat (Tapera) menggunakan algoritma Naïve Bayes dan Support Vector Machine (SVM), sehingga didapatkan informasi mengenai sentimen masyarakat terhadap kebijakan tersebut. Data sejumlah 1280 tweet didapatkan dari hasil crawling web X. Data tersebut diproses menggunakan library sklearn dan diberikan label menggunakan InSet Lexicon. Data juga diproses menggunakan SMOTE. Klasifikasi dilakukan dengan membagi data ke dalam rasio 80:20, 70:30 dan 60:40. Hasil klasifikasi menggunakan algoritma Naïve Bayes dan SVM kemudian dievaluasi menggunakan confusion matrix dan k-fold cross validation. Dari hasil klasifikasi didapatkan bahwa sentimen masyarakat cenderung kearah negatif terhadap kebijakan Tapera. Didapatkan juga bahwa algoritma SVM memiliki akurasi yang lebih baik dibandingkan dengan algoritma Naïve Bayes. Sebelum SMOTE, SVM memiliki akurasi 84% pada rasio 80:20 dengan kernel linear dan C=2, sedangkan Naïve Bayes memiliki akurasi 81% pada rasio 80:20 dengan model Complement dan alpha 0.01. Setelah SMOTE, SVM memiliki akurasi 93% pada rasio 80:20 dengan kernel rbf dan C=3, sedangkan Naïve Bayes memiliki akurasi 89% pada rasio 60:40 dengan model Complement dan alpha 0.1.
Business Process Reengineering of The New Installation Process at PDAM Tirta Agung to Improve The Company's Business Performance Galang Maftuh Nur Alian; I Kadek Dwi Nuryana
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 3 (2025): Vol. 06 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i3.64497

Abstract

In increasingly complex business developments, companies are required to optimize business processes to be more effective and efficient. In addition, customer complaints are important feedback for companies to carry out evaluations to maintain their reputation in the eyes of customers. This study takes a case study on PDAM Tirta Agung, which provides clean water services in Babat District. Referring to interviews and observations, it was found that the legacy system used in the new installation business process has been running for more than four years and is considered inefficient, and time-consuming. Complaints from customers regarding the length of the installation process show that there is a need for repairs. Therefore, the Business Process Reengineering (BPR) method is proposed as a solution to improve service quality. BPR aims to implement radical changes to business processes so that companies can improve speed, accuracy, and cost efficiency, in accordance with the theory put forward by Hammer & Champy.
Design and Development of Raw Material Inventory System for “Es Barbar” SME Using the Material Requirement Planning Method Mohammad Dandi Arsydi; I Kadek Dwi Nuryana
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 3 (2025): Vol. 06 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i3.65777

Abstract

The difficulty in managing raw material inventory has become a major challenge for the UMKM Es Barbar, leading to imbalances such as shortages or excess materials, which hinder operational smoothness. This study aims to design and develop a web-based information system using the Material Requirement Planning (MRP) method to improve raw material management efficiency. With the System Development Life Cycle (SDLC) approach using the waterfall model, the system was designed through stages of communication, planning, modeling, construction, and implementation. The results show that the application of the MRP method successfully reduced stock shortages by 95% and excess stock by 85%, as well as improved the accuracy of raw material planning based on the Master Production Schedule (MPS) and Bill of Materials (BOM). This system facilitates precise raw material requirement planning, supports decision-making, and reduces waste, there by having a positive impact on the operational efficiency of UMKM Es Barbar.
Prediction of Goods Damage in Land Transportation Services (Trucking) Using Naïve Bayes Moh. Fatihul Farras Dzulfaqqor; I Kadek Dwi Nuryana
Journal of Emerging Information Systems and Business Intelligence (JEISBI) Vol. 6 No. 3 (2025): Vol. 06 Issue 03
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v6i3.66306

Abstract

Land transportation plays a crucial role in supporting economic dynamics, yet cargo damage remains a significant challenge that affects the supply chain, efficiency, customer satisfaction, and financial stability. This research aims to analyze the factors influencing cargo damage and predict its likelihood using the Naïve Bayes classification algorithm. A case study was conducted at PT. Tuntas Smart Solusi, a logistics company in Gresik, Indonesia. The Knowledge Discovery in Databases (KDD) framework was employed to process historical shipping data from 2021 to 2023, incorporating variables such as cargo type, shipping route, weather conditions, and load capacity. The results indicate that adverse weather conditions, excessive load weight, and rough routes significantly contribute to cargo damage rates. The Naïve Bayes classifier demonstrated high predictive accuracy, validated using k-fold cross-validation, proving its effectiveness in logistics risk assessment. The findings offer strategic recommendations for logistics companies to minimize damage risks, including optimized packaging strategies, route selection improvements, and predictive monitoring systems. By integrating machine learning-based predictive analytics, logistics firms can enhance operational efficiency, reduce financial losses, and improve overall service quality.
Co-Authors 'Ulhaq, Arafat A'izzatul Khiyana Achmad Asrori Ahmad Shihabudin Aininnisa, Firda Aisyiah, Jamilatul Akhmad Hilmy Zakaria Alifia Octaviany Bashir Amara Indah Putri Ananda Rizky Abidin Anandito Wisnu Widya Pratama Andini Pramesti Andrik Santoso, Muhammad Anggung Mestuti Kaprawiran, Immas Anis Maulidatur Rizqiyah ANITA ANDRIANI, ANITA Ardhini Aarih Utami Ardiansyah, Fernando Aries Dwi Indriyanti Aries Dwi Indriyanti, Aries Dwi Arif Hidayatullah, Arif Ariga Bahrodin Asriana Kibtiyah Augusta Jannatul Firdaus, Reza Aulia Mufidatur Rosida Aulina Naharul Kristanti Avikatria Cahyaningrum Aziz Bagas Setya Wicaksono Bagus Laksono Yudo Atmojo Bagus Bashir, Alifia Octaviany Billah, Hilmi Almuhtade Bonda Sisephaputra Burhan Hidayatulloh Cendra Devayana Putra Daniswara, Anak Agung Aryasatya Darren Waluya Ardianto Devanda Yudha Bharagus Devi Riskhi Kurniawati Egar Caesario Firmansyah Evita Widiyati Faizatul Mukaromah Fauzan Ali Ghofur Ferdani, Happy Septian Finna Nur Nandia Firmanda Himawan, Ahmad Fitrah Amaliah Gagah Ibnu Mutho’illah Galang Maftuh Nur Alian Gerin Azharani Ghea Sekar Palupi Ghea Sekar Palupi Hadi Sucipto, Hadi Hadi, Febria Erliana Hamdani, Hilman Hanif, Zidny Hasan, Jamal Hilal Hindi Saputra Husnul Mubaroq I Gede Adi Duta Saputra P. I Gusti Lanang Putra Eka Prismana, I Gusti Lanang Putra Eka Iftitaahul Mufarrihah Imam Muslih Intan Novita Sari Noer Qholby Maulidiyah Intan Rahma Diana Putri Irsyad Adi Rochman Ivander brian ramadhan Jasica Ardana Herviyandasari Jatminto, Joko Khiena Salsabiila Susanty Khoirotun Nisa Kurrotul Uyun Lailatul Mukharromatus Sa'diyah Laily Masruroh Lintang Iqhtiar Dwi Mawarni Lizza Nur Fadhila Madani, Heru Galang Ardi Reda Maharani, Herlina Syafhita Mahrus Ali Mairatul Lailia Margaretha Ekaristi Yobella Maulana Auliyaurroshidin Mochammad Ilham Study Wartana Ilham Moerdyanto, Octarian Prasetya Moh. Fatihul Farras Dzulfaqqor Mohammad Aris Saputra Mohammad Dandi Arsydi Mohammad Ulil Kirom Monica Cinthya Muchammad Sultan Triabidin Muchtarotun Novia Ustadha Muhammad Aswiandi Muhammad Hafizh Ferdiansyah Muhammad Naufal Ammar Rizqi Muhammad Naufal Baharudin Muizadin, Irwan Mujianto, Ahmad Heru Mukhtarul Fata An Nadwi Nadya Kumalasari Niasmara, Jeptika Herni Nugroho, Meriana Wahyu Nurul - Istiqomah Oki Kurniasari, Serly Oktaviana Tri Wulanndari Pramudita, Genta Prismala, Darisva Puspita Westi Erlitiya Ningrum Rafif Rafeda Ramma Ramadhan, Gemilang Idam Rizky Pratama Syahrul Ramadhan Robbiatul Adawiyah Rohmanialuhri Rengganis Rosida, Aulia Mufidatur Santoso, M Haries Eko Sari, Devit Etika Seriusman Waruwu Shuffy, Muhandis Suhartanto, Martin Suhendi, Laizim Tifanny Maulida Innayah Titin Sundari Totok Yulianto Ulumudin, Febri Nur Utomo, Ilham Wahyu Vania Nadhiya Tsary Wicaksono, Satria Adi Yulius Candra Akmala Yuninda Intan Zahra, Salsabila Nur Zahra