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All Journal Jurnal Ilmiah Multidisiplin Ilmu Jurnal Riset Sistem Informasi
Zainur Rahman
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Computer Science & IT Education Other

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SISTEM INFORMASI PEMBUATAN SURAT KETERANGAN TIDAK MAMPU BERBASIS WEBSITE Ahmad Su’aydi; Zainur Rahman; Firman Santoso
Jurnal Riset Sistem Informasi Vol. 2 No. 1 (2025): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/jpkajh56

Abstract

Jeru Curah Village Office is a government organization located in Jeru Curah Village, Panji Subdistrict, Situbondo District. Making a certificate is one of the services offered by the Jeru Curah Village Government to its citizens. Previously, certificates were made manually, which required residents to come to the Village Office to fill in the required documents and be verified by the manager. However, this process often experienced problems, such as residents' ignorance of the letter-making process, the need to visit the Village Office frequently due to limited working hours and not meeting certain requirements, thus reducing the effectiveness and efficiency of this service. A web-based certificate service information system should be created to overcome these problems. This research includes interviews, literature observation, and observation as data collection methods. The Waterfall method which has five stages of communication, planning, modeling, building, and implementing is used to design this system. The system was built using PHP programming language and MySQL database.Testing with Google Chrome shows that this approach provides reliable results. A web-based service information system that can facilitate the creation of certificate letters by village office officers, save work time, and facilitate the lives of citizens as a consequence of this research. easily simply input the required information, and is available online through the website.
KLASIFIKASI SPESIES BUNGA IRIS MENGGUNAKAN ALGORITMA KLASIFIKASI KNN DI RAPIDMINER Zainur Rahman; Zaehol Fatah; Jarot Dwi Prasetyo
Jurnal Ilmiah Multidisiplin Ilmu Vol. 1 No. 6 (2024): Desember : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/0syd5n74

Abstract

The classification of Iris flower species based on morphological features is a crucial challenge in biological research and data science. This study aims to address this issue using the K-Nearest Neighbor (KNN) algorithm, implemented via RapidMiner, to automate and enhance the accuracy of the classification process. Fisher's Iris Dataset, consisting of 150 samples across three species (Iris setosa, Iris versicolor, and Iris virginica), was utilized. The research followed the Knowledge Discovery in Database (KDD) methodology, involving data preprocessing, model training, and evaluation. The results showed that the KNN algorithm achieved 100% accuracy in classifying the dataset, validating the effectiveness of both the algorithm and the RapidMiner platform for data mining. These findings underline the potential of KNN as a reliable tool for similar classification tasks.
Co-Authors Ahmad Su’aydi Firman Santoso Jarot Dwi Prasetyo Zaehol Fatah