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Teknik Informatika Universitas Muhammadiyah Pontianak
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Rancang Bangun Sistem Informasi Pada Kantor Desa Sebagai Media Pengajuan Surat Dengan Metode Waterfall Dunga Triandri; Istikoma; Sucipto
Jurnal Komputer, Informasi dan Teknologi Vol. 5 No. 1 (2025): Juni
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v5i1.2375

Abstract

The Tumuk Manggis Village Government, Sambas District, Sambas Regency still provides manual letter processing services, which require people to come directly to the Village office. This is considered inefficient because the process takes a long time, coupled with the lack of human resources and mastery of technology by Village employees. In addition, on average, employees at the village office are rarely there and also operational hours are not opened according to the adjusted time. To overcome this problem, a website-based information system is needed that can facilitate online letter submission. This study aims to design and build a letter submission information system using the waterfall method, which includes the stages of needs analysis, design, implementation, testing, and maintenance. The waterfall method was chosen because the process is structured and carried out in stages so that it is easy to develop the system according to what the user wants. Testing was carried out using black box testing to ensure that the system being built is seen and confirmed. The results of the UAT test obtained with an average value of 90.2% which is included in the Strongly Agree category. The results of this study are a website-based system that is expected to be able to accelerate and streamline the letter submission process, so that services become more structured and effective for the people of Tumuk Manggis Village
Penerapan Data Mining untuk Klasifikasi Tingkat Kepuasan Pelanggan Café Menggunakan Metode Decision Tree C4.5 Atta Tha Ariq; Sucipto Sucipto; Rachmat Wahid Saleh Insani
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 15, No 1 (2026): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v15i1.9653

Abstract

Kepuasan pelanggan adalah faktor utama dalam meningkatkan reputasi bisnis, loyalitas pelanggan, dan efisiensi operasional. Penelitian ini bertujuan mengembangkan sistem yang memberikan informasi akurat tentang tingkat kepuasan dan ketidakpuasan pelanggan di sebuah café. Harapannya, temuan dari penelitian ini dapat memberikan dampak baik kepada café guna untuk meningkatkan kualitas pelayanan dengan mengetahui apa saja indikatot-indikator yang mempengaruhi tingkat kepuasan pelanggan café. Metode yang digunakan adalah Decision Tree C4.5, yang membangun pohon keputusan untuk klasifikasi. Proses meliputi penanganan missing value, pengecekan duplicate data, label encoding, penanganan data imbalance dengan SMOTE, pemodelan Decision Tree C4.5, pengecekan akurasi, dan visualisasi aturan keputusan. Evaluasi model dilakukan menggunakan metrik confusion matrix. Hasil evaluasi menunjukkan bahwa model klasifikasi memiliki performa sangat baik, dengan accuracy 98% pada data latih dan 93% pada data uji. Nilai recall, precision, dan F1-score masing-masing adalah 94%, 97%, dan 95%.
Comparison of Naive Bayes and KNN Algorithms for Heart Attack Disease Classification Syahril Arsad; Sucipto; Barry Caesar Octariadi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2218

Abstract

This Heart attack is one of the leading causes of death worldwide and requires early diagnosis to reduce fatal risks. This study aims to compare the performance of the Naive Bayes and K-Nearest Neighbors (KNN) algorithms in classifying heart attack disease. The dataset used consists of medical records containing clinical parameters such as age, blood pressure, cholesterol level, and heart rate. The research methodology includes data preprocessing, splitting the dataset into training and testing sets, and evaluating performance using accuracy, precision, recall, and F1-score metrics. The results show that Naive Bayes demonstrates advantages in computational speed and performs well on smaller datasets, achieving an accuracy of 85%. In contrast, KNN provides better performance on larger datasets, reaching an accuracy of 90%, particularly when the optimal K value is applied. These findings indicate that algorithm selection for heart attack classification depends on dataset characteristics and specific implementation needs. This study is expected to contribute to the development of artificial intelligence–based clinical decision support systems for early heart attack diagnosis and improved healthcare outcomes.
Implementation of a Web-Based Decision Support System for New Employee Recruitment Using the VIKOR Method Arochman; Sucipto; Asrul Abdullah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2298

Abstract

An effective and objective employee selection process is essential to obtain high-quality human resources. This study aims to develop a web-based decision support system to assist in the recruitment of new employees using the VIKOR method. The VIKOR method is chosen because it can rank alternatives based on their closeness to the ideal solution while considering compromise among criteria. The criteria used in the system include education, work experience, skills, interview results, and work personality. This research adopts the waterfall approach for system development and implements PHP programming language with a MySQL database. The testing results indicate that the system is capable of providing accurate and consistent rankings of job candidates, as well as facilitating the HR team in conducting evaluations more efficiently.
Network Device Performance Monitoring Using the Simple Network Management Protocol (SNMP) Method Aldi Mulia Rismanto; Asrul Abdullah; Sucipto
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2346

Abstract

Network problems frequently occur at Politeknik Negeri Pontianak due to the increasing number and scale of network devices. These issues require continuous monitoring to ensure service availability across all network devices. To address this problem, the author conducted network monitoring using the SNMP (Simple Network Management Protocol) method and network performance measurement using the Wireshark application. SNMP is a standard protocol used to monitor and manage network devices such as routers, switches, servers, and other networking equipment. The research stages began with data collection, followed by monitoring and performance testing of the network. After testing the network in the Informatics Engineering Building, both satisfactory and unsatisfactory results were obtained. The results of SNMP measurements on MRTG showed the lowest throughput values on the second day of testing, with 485.6 kbps for daily traffic, 236.8 kbps for weekly traffic, 232 kbps for monthly traffic, and 121.6 kbps for yearly traffic. Meanwhile, the Quality of Service measurement produced the lowest throughput value of 0.225 kbps, packet loss of 0.354%, delay of 3.331 ms, and jitter of 8.763 ms.
Co-Authors Aldi Mulia Rismanto Arfiyan, Fandika Roinaldi Arochman Asrul Abdullah Atta Tha Ariq Barry Caesar Octariadi Barry Ceasar Octariadi Dedy Susanto Dunga Triandri Fadillah Bergas Fenni Supriadi Istikoma M. Khairul Anwari Muhammad Hendri Rachmat Wahid Saleh Insani Rachmat Wahid Saleh Insani Syahril Arsad Ya' Ilham Eka Saputra Yulrio Brianorman