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All Journal Jurnal Informatika Upgris JURNAL MEDIA INFORMATIKA BUDIDARMA ILKOM Jurnal Ilmiah Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar JSAI (Journal Scientific and Applied Informatics) JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Nasional Cosphi Nusantara of Engineering (NOE) Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK) Jurnal Rekayasa elektrika
Haditsah Annur
Universitas Ichsan Gorontalo
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Other

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PENERAPAN NETWORK MONITORING SYSTEM (NMS) SECARA VISUAL PADA INFRASTRUKTUR JARINGAN FISIK BERBASIS WEB Annur, Haditsah; Laari, Ramdan A
Nusantara of Engineering (NOE) Vol 5 No 2 (2022): Volume 5 No 2 Tahun 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/noe.v5i2.18682

Abstract

A Network Monitoring System (NMS) is a system that continuously monitors the network and provides immediate notification to network administrators in the event of problems or interruptions. This study aims to apply a Network Monitoring System for monitoring network devices in Universitas Ichsan Gorontalo. This application is visually web-based, so network administrators can easily find problems with network devices in this system. As a result of this study, the system can now find problematic network devices on existing network devices. It can show the results in a visual format. If the network device check fails, the system recognizes if there is a problem with the network device.
PENERAPAN ALGORITMA NAIVE BAYES BERBASIS FORWARD SELECTION UNTUK MEMPREDIKSI PENJUALAN MOBIL BEKAS haditsah annur; Moh.Efendi Lasulika
JURNAL ILMU KOMPUTER Vol 10 No 2 (2024): Edisi September
Publisher : LPPM Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jiik.v10i2.320

Abstract

Cars are one of the vehicles that are the daily needs of the people, not only the use of new cars is in demand, but now used cars are also in great demand because the quality of used cars is still good and the many types of used cars are sold in the market. The aim of the researchers is to increase public interest in switching to buying used cars. This study uses data mining methods, one of which is prediction using the Naive Bayes algorithm as an algorithm that uses probabilistic and statistical methods to predict the future, besides that the data is also processed using forward selection feature selection which aims to reduce the level of complexity of a classification algorithm while increasing accuracy. The research data used were 2318 records, in this study an experiment was carried out with the accuracy results obtained using split validation on the naive Bayes algorithm of 96.98% and then another experiment was carried out to obtain accurate results using split validation on the naive bayes algorithm based on forward selection of 97.82 %. Thus the naive Bayes algorithm based on forward selection is suitable for predicting, as well as being used for handling in the future that there are still many used cars that are of interest to the public..
Analisis Keranjang Belanja Pelanggan Coffe Shop Menggunakan Algoritma FP-GROWTH haditsah annur; Serwin Serwin; Intan Nur Anisa
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.8835

Abstract

One of the businesses that attracts economic development is a coffee shop. This business is very important and growing rapidly. Shopping cart analysis has the ability to provide information about which products are frequently purchased together. The use of shopping cart analysis is regulated in association rules which is a data processing process that provides records of purchase transactions that come out simultaneously at one time, the algorithm used to regulate these association rules is the FP-Growth algorithm. coffee shop customer shopping cart analysis uses the FP-Growth Algorithm. This research data was obtained from public data on the website https://www.kaggle.com/datasets/sryasuka/coffee-shop-dataset/data,, with a dataset of 1000 transactions, the data processing uses RapidMiner tools, after processing, 2 association rules were found using minimum support = 0.01 and minimum confidence = 0.7. It can be concluded that the results of the shopping cart analysis show that 1 item is most frequently purchased by customers, namely croissants and the purchase of 2 items, namely croissants and fries. So that the shopping basket analysis method with the FP-Growth algorithm can optimize item combination patterns and can improve sales strategies, thereby supporting coffee shop business decision making.
Co-Authors ABDUL_MUHRIZAL_ZULKIFLI_H_MARADA Andri Setiawan Apriyanto Alhamad Asmaul Husnah Nasrullah Balok, Admin Caldiyastovan Mohi Intan Nur Anisa Irma Surya Kumala Idris Laari, Ramdan A Moh.Efendi Lasulika Mohamad Efendi Lasulika Muammar Zainuddin Nur Insani Panna, sudirman S. Rachmawan Sidik Laminullah Rahma Rizal Roys Pakaya Rustam, Suhardi Serwin Sudirman Melangi Suhardi Rustam Warid Yunus Yusrianto Malago