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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Perspektif : Jurnal Ekonomi dan Manajemen Universitas Bina Sarana Informatika Jurnal Teknik Komputer AMIK BSI Jurnal Pilar Nusa Mandiri Faktor Exacta JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Riset Informatika Jurnal SITECH : Sistem Informasi dan Teknologi Jusikom: Jurnal Sistem Informasi Ilmu Komputer INTI Nusa Mandiri JURSIMA (Jurnal Sistem Informasi dan Manajemen) TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Applied Data Sciences Jurnal AbdiMas Nusa Mandiri RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Jurnal Responsif : Riset Sains dan Informatika Mediastima JURSIMA Journal Medical Informatics Technology Journal Information & Computer (JICOM) Jurnal Sistem Informasi dan Manajemen
Sulistyowati, Daning Nur
Universitas Nusa Mandiri
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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SISTEM INFORMASI REKAPITULASI DATA OPERASIONAL BERBASIS WEBSITE PADA PT WAHANA ERA SEJAHTERA Heni Listianingrum; Valiza Niswa Audina; Sarah Aprilia; Daning Nur Sulistyowati
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8111

Abstract

In recent years, advances in information technology (IT) have contributed significantly to improving business processes and operational efficiency. However, the adoption and utilization of IT remain suboptimal in some organizations, including PT Wahana Era Sejahtera. The company's operational data management is still carried out conventionally through external reports in the form of PDF and Microsoft Excel files, which causes the risk of duplication, data loss, and difficulties in the information retrieval process. In addition, this condition hinders the monitoring of the company's performance and increases the risk of errors in checking employee data and work tools. This research focuses on the development of a web-based operational data management system for PT Wahana Era Sejahtera to improve the efficiency of recording, storing, retrieving, and monitoring operational data. The system was developed using the Prototype model within the Software Development Life Cycle (SDLC) framework. Evaluation through User Acceptance Testing (UAT) resulted in a score of 82.32%, indicating a high level of user acceptance. The findings demonstrate that the proposed system can support operational activities by reducing the risk of data duplication and data loss, facilitate information management and retrieval, and support the process of monitoring company performance and decision-making more quickly, precisely, and accurately.  
CLASSIFICATION OF STUDENT SATISFACTION WITH ONLINE LECTURE Nanang Ruhyana; Tati Mardiana; Fachri Amsury; Daning Nur Sulistyowati
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1171.987 KB) | DOI: 10.34288/jri.v4i1.144

Abstract

Abstra Covid-19 has had a significant impact on people's lives, resulting in the paralysis of almost the entire economy and education, especially in the education sector, resulting in many students being unable to carry out teaching and learning activities at schools or universities. Based on this, the Ministry of Education and Culture has issued an appeal to stop face-to-face teaching and learning activities at schools and universities and replace them with distance or online learning. Resulting in teaching and learning activities to be less than optimal for students or students, there is dissatisfaction with the distance or online learning system, the purpose of this study is to measure the level of student satisfaction with online lectures by applying data mining techniques, classifying the level of online learning satisfaction using an online learning approach. k-NN algorithm and Decision Tree with 100 questionnaire data that has been collected from active students who carry out online lectures with an accuracy rate of 96.00% from the k-NN algorithm and a satisfied precision value of 95.51%, a satisfied recall value of 98.84% on a precision value the dissatisfied class is 90.91%, the recall value of the dissatisfied class is 71.43%. While the accuracy results using the Decision Tree algorithm approach is lower with an accuracy of 95.00%. based on research results that the level of student satisfaction with distance learning or online is quite high.
ANALISIS MULTI-MODEL KOMPARATIF UNTUK DETEKSI DINI KANKER PAYUDARA MENGGUNAKAN EVALUASI ROC-AUC DAN MCC Daning Nur Sulistyowati; Sri Hadianti; Ridan Nurfalah
INTI Nusa Mandiri Vol. 21 No. 1 (2026): INTI Periode Agustus 2026
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v21i1.8278

Abstract

Breast cancer is one of the leading causes of death in women and relies heavily on early detection to improve the chances of recovery. The main challenges in machine learning-based early detection systems are class imbalance and the limitations of evaluation metrics that often rely solely on accuracy or ROC–AUC. In this context, the Matthews Correlation Coefficient (MCC) offers a more comprehensive assessment because it considers all elements of the confusion matrix. This study analyzes and compares the performance of four classification algorithms: Naive Bayes, Decision Tree, Random Forest, and SVM on the Breast Cancer Wisconsin (Diagnostic) dataset. The dataset was first divided using a stratified train–test split of 80:20 to maintain class proportions. Feature normalization was performed only on the training data to avoid data leakage, then applied to the test data using the same parameters. Furthermore, 5-fold cross-validation was performed on the training data for model evaluation and selection. The results show that SVM provides the best performance with an accuracy of 98.25%, a precision of 1.00, an F1-score of 0.9762, an AUC of 0.9971, and an MCC of 0.9630. Naive Bayes and Random Forest also show excellent performance with AUC values ​​above 0.99 and an MCC of 0.9253, while Decision Tree has a lower performance. Confusion matrix and ROC curve analysis confirm the superiority of SVM in minimizing classification errors. These findings emphasize the importance of a multi-model approach and the use of MCC as a more representative evaluation metric in breast cancer early detection systems.
Co-Authors Aditya, Mulyadi Ahmad Setiadi Angelia, Helen Ani Oktarini Sari Aziz, Faruq Dwi Arum Ningtyas Dwi Arum Ningtyas Dwiza Riana Eni Heni Hermaliani Fachri Amsury Fahrul Rozi Frieyadie Gata, Windu Haider Haider Heni Listianingrum Hery, Moch Ida Zuniarti, Ida Imam Budiawan Irwansyah Saputra Ismail Hasan Jansen Pratama Setiawan Lumbantobing Jilan Jamilah Kadafi, Abdul Rahman Laureta, Wika Widya Mahendra Gilang Ramadhynara Maruloh Maruloh Mayangky, Nissa Almira Mohammad Badrul Muhamad Angga Maulana Muhammad Salbiyath Munawaroh, Fiqrotul Nanang Ruhyana Nanang Ruhyana Nita Merlina, Nita Norma Yunita Nurajijah Nurajijah Nurman Machmud Prasetio, Arfhan Reza Ema Furi Ridan Nurfalah Rifky Permana Ris yanto Risca Lusiana Pratiwi Risma Purnama Sari Sandra, Gardika Santoso Setiawan Saputra, Surya Fajar Sarah Aprilia Septian Septian Septian, Septian Siti Fauziah Siti Fauziah Siti Fauziah Sri Hadianti Sri Hadianti Tammayyusdin, Aulia Salma Tati Mardiana Taufik Asra Tika Adilah M Valiza Niswa Audina Yunita, Norma