Article Per Year (5 Year)
p-Index From 2021 - 2026
2.715
P-Index
This Author published in this journals
All Journal ELS Journal on Interdisciplinary Studies in Humanities Pendas : Jurnah Ilmiah Pendidikan Dasar Journal of System and Computer Engineering Journal Peqguruang: Conference Series Global Abdimas: Jurnal Pengabdian Masyarakat Journal of Artificial Intelligence and Digital Business Journal Pharmacy and Application of Computer Sciences DIDAKTIS: Jurnal Pendidikan Bahasa dan Sastra Indonesia Jurnal Ilmu Pertanian dan Perkebunan Advances in Computer System Innovation Journal (ACSI Journal)
Mardewi, Mardewi
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Transportation Other

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : Journal of System and Computer Engineering

 1 
Klasifikasi Liver Cirrhosis Menggunakan Teknik Ensemble: Studi Perbandingan Model Boosted Tree, Bagged Tree, dan Rusboosted Tree Mardewi, Mardewi; Wungo, Supriyadi La
Journal of System and Computer Engineering Vol 5 No 2 (2024): JSCE: Juli 2024
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v5i2.1302

Abstract

Liver cirrhosis, as a significant chronic liver disease, exhibits a rising global prevalence, demanding more effective preventive approaches. In an effort to enhance early detection and patient management, this research proposes the development of a liver cirrhosis risk prediction model using machine learning technology, specifically comparing the performance of three ensemble tree models: Ensemble Boosted Tree, Ensemble Bagged Tree, and Ensemble RUSBoosted Tree. Utilizing clinical and laboratory data from adults with a history or risk of cirrhosis, the study reveals that Ensemble Bagged Tree achieved the highest accuracy at 71%, followed by Ensemble Boosted Tree (67.2%) and Ensemble RUSBoosted Tree (66%). Analysis of clinical and laboratory variables provides further insights into the most significant contributors to risk prediction. The findings lay the groundwork for the advancement of a more sophisticated liver cirrhosis risk prediction tool, supporting a vision of more personalized and effective preventive strategies in liver disease management.
ARIMA Method Implementation for Electricity Demand Forecasting with MAPE Evaluation Wungo, Supriyadi La; Aziz, Firman; Jeffry, Jeffry; Mardewi, Mardewi; Syam, Rahmat Fuady; Nasruddin, Nasruddin
Journal of System and Computer Engineering Vol 6 No 1 (2025): JSCE: January 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i1.1666

Abstract

Electricity demand forecasting is critical for efficient energy management and planning. This study focuses on the development and implementation of the Autoregressive Integrated Moving Average (ARIMA) method for forecasting electricity demand in South Sulawesi's power system. The evaluation of forecasting accuracy was conducted using the Mean Absolute Percentage Error (MAPE), which measures the percentage error between predicted and actual values. Two experiments were conducted with different ARIMA models: ARIMA(5,1,0) and ARIMA(2,0,1). Results showed that the ARIMA(5,1,0) model achieved a MAPE of 2.15%, while the ARIMA(2,0,1) model performed slightly better with a MAPE of 1.91%, indicating highly accurate predictions. The findings highlight the effectiveness of the ARIMA method in forecasting electricity demand, providing a reliable tool for energy providers to optimize resource allocation and enhance operational efficiency. Future research may explore integrating ARIMA with other advanced methods to further improve forecasting performance.
Decision Support System for Selecting Used Cars Using the Analytical Hierarchy Process (AHP) Method Based on a Website at CV Auto Mobil Manokwari Marhaba, Melvi; Mardewi, Mardewi; Sangka, Yuliana; Hasbi, Hasbi; Wungo, Supriyadi La
Journal of System and Computer Engineering Vol 6 No 3 (2025): JSCE: July 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i3.2106

Abstract

Buying a used car is often considered by the public as an alternative because it is more affordable than a new one. However, the process of choosing a used car is not easy because there are various factors that must be considered, such as engine condition, completeness of documents, physical condition, price, engine capacity, and year of manufacture. At CV Auto Mobil Manokwari, prospective buyers often have difficulty determining the choice of a used car that best suits their needs and budget. This research aims to design a website-based decision support system using the Analytical Hierarchy Process (AHP) method to assist buyers in choosing used cars objectively and systematically. The AHP method is used to compare each criterion in pairs and determine the priority weight of each criterion. The system was developed using the PHP programming language and MySQL database with a waterfall approach. With this system, the process of selecting used cars becomes more directed, accurate, and efficient, as well as helping users make decisions practically and quickly, and objectively.
Sistem Monitoring Status Meja Pada Restoran Berbasis Internet of Things (IOT) Mardewi, Mardewi; Iskandar, Imran; Sofyan, Sofyan; La Wungo, Supriyadi; Aziz, Firman
Journal of System and Computer Engineering Vol 4 No 2 (2023): JSCE: Juli 2023
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v4i2.816

Abstract

The condition of a busy restaurant sometimes makes it difficult for waiters to monitor and provide satisfactory service to customers. Customers must wave when they want to call waiters but feel ignored or not seen and will feel uncomfortable with the atmosphere and calm in the dining room. An Internet of Things (IOT) based desk status monitoring system is a concept that has the ability to transfer data over a network without the need for human-to-human interaction. This study proposes a table status monitoring system in IOT-based restaurants. This tool is made so that it can be applied to large rooms and crowded visitors. A device equipped with wireless communication to send data to the server, so that it can be monitored in real time. If the button on the tool is pressed, the system will send a signal to the relay to give a call sign warning to restaurant staff/waitresses. The results of this study indicate that status information from tables requesting service from waiters will respond to these service requests and help optimize service at restaurants so that they can satisfy their customers.
Co-Authors Adi Nugroho, Dwi Adrian Adrian Almince, Delsi Arifin, Sofyan Asdar Asdar Ayuningtyas, Nirmala Basri Basri Batkunde, James Christy, Sebianus Rainer N Dowansiba, Novelina Firdaus, Jey Firman Aziz Hasbi Indrayani, Lilis Indrayanti, Lilis Irmawati Leppang Isdaryanti, Isdaryanti Iskandar, Imran Ismail Ismail Ismail JA, Puspita Hadriani Jeffry Jeffry Kaco, Suardi Khaerunnisa Khaerunnisa, Khaerunnisa La Wungo, Supriyadi Makalmai, Beci J. Marhaba, Melvi Muhammad Sarjan Musrifah Tahar Nasruddin Nasruddin Puspa, Rati Qamal Qamal Saifuddin Saifuddin Sangka, Yuliana Sofyan Sofyan Syam, Rahmat Fuady Tonapa, Jennis W, Setyo Hendra Aldi Wiyarzah, Ice Wungo, Supriyadi La Yarkuran, Nuru Zulkarnain Zulkarnain