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Journal : SAINTEK

Penerapan Data Mining Untuk Klasifikasi Kepuasan Pelanggan Transportasi Online (Ojek Online) Menggunakan Algoritma C.4.5 Suherman Suherman; Donny Maulana; Vivi Mustikaningtyas
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/SAINTEK0101.165175

Abstract

Human activities to meet their daily needs and needs, both at work, or just for a walk. So, this needs to be supported by adequate transportation. With the development of technology today there are applications that introduce motorcycle taxi booking services using technology and use service standards. In Indonesia there are many motorbikes, which also function as general vehicles, namely transporting people / goods. Currently there are many online transportation service providers (online motorcycle taxi) known as Go-Jek, Grab, and Uber. Customer satisfaction input attributes in this study include price, facilities, service and loyalty. Data mining is a series of processes to explore added value in the form of information that has not been known manually from a database. In this study it is expected to help the online transportation services in increasing customer satisfaction. Based on the results of the classification using C4.5 algorithm shows that the accuracy reached 75.33%, which shows that the C4.5 algorithm is suitable for measuring the level of satisfaction of online transportation. Keywords: Satisfaction of online transportation, Data Mining, Algoritma C.4.5
Sistem Monitoring Suhu Dan Kelembapan Udara Berbasis Internet Of Things Pada Ruang Kerja Proses Injection Molding Donny Maulana; Ikhsanudin ikhsanudin
Prosiding Sains dan Teknologi Vol. 1 No. 1 (2022): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 1 - Juli 2022
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of technology is currently growing very rapidly and can be felt in the industrial world and in society, one of which is the application of the Internet of Things (IoT) in the work environment. The work environment is all things or elements that can affect directly or indirectly the organization or company that will have a good or bad impact on employee performance and job satisfaction. The purpose of this research on temperature and humidity monitoring systems is to monitor the stability of temperature and humidity in the injection molding process workspace, where room temperature is related to the engine cooling temperature and affects the results of production. This temperature and humidity monitoring system is designed using the NodeMCU ESP8266 module and the DHT11 sensor using the Arduino IDE program C language and the Thingspeak web server. In this research, the methodology used is the prototype methodology. The prototype model is a technique to collect certain information about the user's information needs quickly. As a result, manual thermometers can be replaced with Internet of Things-based temperature sensors. The temperature and humidity monitoring system can be applied in the injection molding process workspace so that it can speed up the response by the facility in the event of an abnormality in room temperature. Keywords: Internet of Things, Thingspeak, NodeMCU ESP8266, DHT11 Sensor
Komparasi Algoritma Support Vector Machine (Svm) Dan Logistic Regression Menggunakan Metode Smote Untuk Klasifikasi Penyakit Diabetes Melitus Donny Maulana; Linda Wahyu Setyoningsih
Prosiding Sains dan Teknologi Vol. 3 No. 1 (2024): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 3 - Januari 2024
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

Diabetes Mellitus is a metabolic disease characterized by increased blood sugar levels due to impaired insulin production, insulin action or both. Utilization of data mining is used in the health sector and also in the technology industry. Processing data so that it can be used as a source of fresh knowledge and information is one of the many advantages of data mining. In this study, two algorithms are used, namely Support Vector Machine and Logistic Regression. Both of these algorithms use the SMOTE (Synthetic Minority Over-sampling Technique) method to overcome data imbalances. Based on tests carried out using the Confusion Matrix, the results of measuring the performance values of Accuracy, Precision, Recall and f1-score using the Support Vector Machine (SVM) algorithm and Logistic Regression using the SMOTE method, it can be concluded that the best algorithm in the classification of diabetes mellitus is the Support Vector Machine (SVM) algorithm with an Accuracy value of 0.81, Precision of 0.80, Recall of 0.82 and f1-score of 0.81.
Sistem Informasi Pengajuan Cuti Karyawan Pada Pt.Tass Engginering Berbasis Website Donny Maulana; Emilda Yulian Sari
Prosiding Sains dan Teknologi Vol. 4 No. 1 (2025): Seminar Nasional Sains dan Teknologi (SAINTEK) ke 4 - Februari 2025
Publisher : DPPM Universitas Pelita Bangsa

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Abstract

The rapid development of information technology encourages companies to implement web-based information systems to improve the effectiveness and efficiency of data management. PT Tass Engineering still manages employee leave requests manually using paper forms and simple office applications, which often leads to recording errors, delays in approval processes, and potential data loss. This study aims to design and develop a web-based Employee Leave Management Information System that facilitates the submission, approval, and management of leave data in an integrated manner. The research method uses structured interviews to identify system requirements, while the system development applies the Waterfall model, consisting of requirement analysis, system design, implementation, testing, and maintenance stages. The system is modeled using Unified Modeling Language (UML) and implemented using PHP as the programming language and MySQL as the database, running on a XAMPP environment. System testing is conducted using the Black Box Testing method to ensure that each function operates according to the specified requirements. The results indicate that key features, including login authentication, leave submission, employee data management, approval processes, and report generation, function properly and meet user needs. The developed system improves administrative efficiency, minimizes human error, and ensures centralized and secure data storage within the database.