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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Teknologi Informatika dan Komputer Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Jurnal Pelita Pengabdian Journal Innovation in Information and Computer Technology
Candra Naya
Universitas Pelita Bangsa
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Penentuan Kepuasan Pelanggan Terhadap Pelayanan Kantor Pelayanan Pajak Menggunakan C4.5 dan PSO Ikhsan Romli; Fairuz Kharida; Chandra Naya
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (703.527 KB) | DOI: 10.29207/resti.v4i2.1718

Abstract

Tax Service Office is a work unit of the Directorate General of Taxation that carries out services in the field of taxation to the public, both registered and unregistered taxpayers, within the working area of the Directorate General of Taxes. The number of Primary Tax Service Offices in Indonesia, one of which is the Primary Tax Service Office in Bekasi, has various ways to increase the satisfaction of taxpayers for the services provided. This study aims to determine the accuracy of taxpayers' satisfaction using data mining techniques using the Decision Tree C4.5 Algorithm with Particle Swarm Optimization (PSO) feature selection, validation uses cross validation techniques while accuracy is measured by the confussion matrix, which is to determine the level of service satisfaction conducted by distributing questionnaires to taxpayers in the Primary Tax Service Office in Bekasi as many as 500 questionnaires. The results show the accuracy value of Taxpayers' service satisfaction at the Pratama Tax Service Office using the Decision Tree C4.5 Algorithm with a feature selection of Particle Swarm Optimization (PSO) of 98,85%, Precission of 98,85% and Recall of 100%.
Implementasi Aplikasi Kasir Pada Warung Chicken Geprek Sahabat Berbasis Desktop Menggunakan Vb.Net Candra Naya; Bayu Nugroho; Elkin Rilvani
Jurnal SIGMA Vol 13 No 2 (2022): Juni 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Abstract Warung Chicken Geprek Sahabat is one of the businesses engaged in the sale of ready-to-eat chicken geprek, in the process of selling the system it is still done manually and the reports generated are only stored in the form of documents as archives, resulting in loss of documents and accumulation of papers resulting in excessive use of paper. Therefore, to make it easier for the friend's chicken geprek stall, the researcher made data processing and transaction reports, the researcher took advantage of the use of technology, one of which was computer technology by making a cashier application for the friend's chicken geprek stall. The purpose of this cashier application design is to assist the stall's activities in processing data such as food and beverage data, user data, sales transaction data, as well as daily and monthly transaction reports. The process of designing this cashier application uses Microsoft Visual Basic as the programming language used, as well as application development using the waterfall method. The result of this research is a desktop-based friend's chicken geprek cashier application program with vb.net which can make it easier for administrators and employees to process chicken geprek friends data. Keywords: Program, Cashier Application, Microsoft Visual Basic, Sales
Penerapan Data Mining Untuk Prediksi Kelulusan Siswa Menggunakan Algoritma Naïve Bayes Pada SMK Garuda Endah Yaodah Kodratillah; Daririn Daririn; Candra Naya
Jurnal SIGMA Vol 12 No 4 (2021): Desember 2021
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Student graduation is a series of process stages that must be assessed by each student, including having to complete a predetermined number of lessons, and must meet the terms and conditions set by the school, because graduation is a reference so that they can continue their education to a higher level. and work in the business world and the industrial world. Therefore, this study will utilize data about student graduation by processing it using Data Mining to obtain information in the form of predictions of student graduation. The algorithm that will be used is the Naive Bayes algorithm. The attributes used in predicting student graduation are Practice Score, US (School Examination) and Student Behavior. Data Mining testing using the Naive Bayes algorithm produces an accuracy of 76.25%, precision 93.33%, recall 78.87% and an AUC value of 0.751. It can be concluded that the Naive Bayes algorithm has very good accuracy in this study. Keywords: Data mining, Classification, C4.5 Algoritma, Naive Bayes
Analisis Quality Of Service Management Bandwidth Pada Jaringan Internet Menggunakan Peer Connection Queue (Studi Kasus : Rumah Makan Ikan Ayam) Candra Naya; Lathifah Zahroh
Jurnal SIGMA Vol 12 No 4 (2021): Desember 2021
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The The research objective was to analyze and implement network hotspots and bandwidth management at the Restaurant Ikan Ayam, so that the Restaurant can provide microtic-based hotspot facilities, evenly distribute bandwidth on hotspot networks to each customer and limit bandwidth usage according to the time stated on the voucher package. The research methods included the analysis method, namely by conducting a survey of the system that is running and the study of literature, the design method of network topology by selecting network devices to be used and configuration on each network device used, testing new networks, and maintenance activities (bandwidth traffic monitoring). The results of the research obtained are the implementation of the design of network hotspot topology and bandwidth management using RouterOS Microtics optimize the performance of hotspot networks and maximize bandwidth on hotspot networks. The conclusion of this study is that by using RouterOS Microtics on hotspot networks, internet cafes can limit the bandwidth usage of customers based on the voucher package that has been made and there is no attraction in attracting bandwidth between customers due to equal bandwidth distribution. Keywords: Hotspot, Bandwidth Management, RouterOS Microtics
Perancangan Aplikasi Pembelajaran Ekspesi Matematika Dengan Metode Stack Menggunakan Delphi 2010 Candra Naya
Jurnal SIGMA Vol 12 No 1 (2021): Maret 2021
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

Long mathematical expressions may make it difficult to divert them. In the data structure, the stages of completion of a mathematical expression can be represented in the form of a stack and a binary tree. In this case the author will use the stack work to complete a mathematical expression and use Embarcadero Delphi 2010 as the programming language. In real life, humans are more familiar with mathematical expressions of infix notation than other notations. Unlike the process inside the computer, in completing the calculation does not use the form of infix notation, but using prefix and postfix notation. In prefix and postfix notation there will be no brackets and the hierarchy on the operator is invalid, so the reading time is faster. The world of education requires a learning tool that can simplify the learning process, one of which is the application of teaching tools. Design of Learning Mathematical Ekpresi Application With Stack Method is designed to facilitate the learning and management and calculation of mathematical expressions. By using the stack work system, this application converts the mathematical expressions commonly used by human infix notation into the mathematical expressions commonly used by computers ie prefix and postfix notation and evaluate the results. This unlimited application only executes operands with a single character operand, but is also capable of executing operands with characters longer than one character. Model of software design approach used is waterfall model. Design and implementation for Application Design Learning Mathematical Expression is focused on one module that is the conversion process and calculation of mathematical expression. At the end of the thesis, evaluated the process and product of software development. Keywords : Mathematical Expression, Stack Method, Infix, Prefix, Postfix
Analisis Sentimen Terhadap Operator Seluler Telkomsel Menggunakan Algoritma Naïve Bayes Candra Naya
Jurnal SIGMA Vol 11 No 2 (2020): Juni 2020
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The use of social media in the era of globalization is very necessary for all people including Telkomsel cellular operators, Telkomsel uses Twitter as a promotional media. However, the use of Twitter as a medium for promotion of Telkomsel received various compliments of input and criticism and in this case the authors conducted research to analyze Telkomsel user sentiment. And in this study the authors used the Naïve Bayes algorithm to classify sentiments and look for preference values. From the results of tests conducted using cross validation techniques and accuracy measurements using confusion matrix with 10 times the best accuracy testing obtained was 85.33 % and the positive response obtained from the calculation of preference value was 37.03 %. It can be concluded that the Naïve Bayes algorithm can be used to classify quite well and be able to measure user responses. Keywords : Twitter, Sentiment Analysis, Naïve Bayes Classifier, Cross Validation, Preference Value
Analisa Kepuasan Pelanggan Menggunakan Algoritma C4.5 Pada PT. Cahaya Indotama Engineering Candra Naya; Arif Siswandi
Jurnal SIGMA Vol 13 No 4 (2022): Desember 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v13i4.2237

Abstract

Dalam penelitian ini kepuasan pelanggan menjadi salah satu penilaian terhadap produk dan jasa untuk memenuhi kebutuhan pelanggan. Salah satu hal yang penting dalam pengelolaan pelanggan adalah bagaimana suatu perusahaan dapat mempertahankan pelanggan yang dimilikinya. Kepuasan pelanggan merupakan perasaan senang atau kecewa seorang yang merupakan hasil dari analisa kepuasan pelanggan melalui kuesioner para pelanggan. Maka, metode klasifikasi mampu menemukan model yang mampu memprediksi dan menentukan kelas dari kepuasan pelanggan dengan data training yang telah diperoleh, Algoritma C4.5 adalah algoritma klasifikasi data dengan teknik pohon keputusan yang terkenal dan disukai karena memiliki kelebihan-kelebihan. Kelebihan ini misalnya dapat mengolah data numeric dan diskret, dapat menangani nilai atribut yang hilang, yang menghasilkan aturan-aturan mudah diinterpretasikan dan tercepat diantara algoritma yang lainnya untuk memprediksi kepuasan pelanggan dengan hasil penelitian menggunakan metode C4.5 termasuk algoritma yang akurat untuk memprediksi karena hasil akurasi menggunakan RapidMiner menyatakan tingkat accuracy, precision, dan recal C4.5 memiliki tingkat accuracy 86,11%, precision 89,02% dan recall 92,40%. Kata kunci : Data mining, Algoritma C4.5, Klasifikasi, Kepuasan pelanggan
Implementasi Data Mining Untuk Pengelompokan Pengangguran Terbuka di Indonesia Dengan Metode Clustering Candra Naya; Arif Siswandi
Jurnal SIGMA Vol 14 No 2 (2023): Juni 2023
Publisher : Teknik Informatika, Universitas Pelita Bangsa

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Abstract

The number of unemployed as of August 2021 was 9.1 million people from all types of educational circles in Indonesia, so the percentage of unemployed in Indonesia is quite large and is a factor that can be underlined. The unemployment rate will increase every year if there are no significant efforts to reduce the percentage of unemployed in Indonesia. Therefore, there is a need for government realization in providing jobs in accordance with the groupings in the territory of Indonesia in order to know the level of unemployment clusters of the Indonesian population. The implementation of data mining using the clustering method in this study aims to determine groups of the unemployed based on the level of unemployment in the territory of Indonesia. The clustering method using the k-means algorithm can group Indonesia into three clusters, namely cluster 1 is a group of regions with a low unemployment rate which includes 3 regions, cluster 2 is a group of regions with a moderate unemployment rate which includes 10 regions, and cluster 3 is a group regions with high unemployment rates covering 21 regions. The results of the analysis obtained the percentage of each cluster, namely cluster 1 has 9% of the area, cluster 2 has 29% of the area, and cluster 3 has 62% of the area. These results are expected to provide information to the community and local government, especially in areas with high unemployment rates, to be able to carry out ideas to reduce the percentage rate of unemployment in Indonesia. Keywords: Data mining, Clustering, K-means Algorithm
Membuat Sistem Informasi Bursa Kerja Khusus (BKK) di SMK Al-Amin Cibarusah Berbasis Website Ermanto Ermanto; Arif Susilo; Candra Naya; Elkin Rilvani; Edi Tri Wibowo
VIDHEAS: Jurnal Nasional Abdimas Multidisiplin Vol. 1 No. 1 (2023): Juni 2023
Publisher : VINICHO MEDIA PUBLISINDO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61946/vidheas.v1i1.6

Abstract

Bursa Kerja Khusus (BKK) SMK Al-Amin bekerja dalam melayani informasi terkait dunia industri untuk para siswa dan alumninya. Selama ini BKK SMK Al-Amin tidak menggunakan sistem terpadu sebagai alat bantu dalam penyampaian informasi terkait lowongan pekerjaan. BKK SMK Al-Amin masih mengandalkan sistem manual berupa selembaran poster yang ditempel di mading sekolah. BKK SMK Al-Amin sudah berusaha menggunakan teknologi pesan singkat melalui handphone akan tetapi pendataan nomor handphone alumni masih sulit dilakukan. Maka dari itu tujuan pengabdian ini adalah untuk mengembangkan sistem bursa kerja khusus berbasis web agar dapat membantu kinerja BKK SMK Al-Amin dalam melakukan fungsi pelayan terkait dunia kerja kepada para siswa dan alumni. Selain itu sistem ini juga dapat mengintegrasikan antara siswa, pihak BKK, dan Perusahaan.
Implementation of Decision Tree C4.5 and Naïve Bayes for Data Mining-Based Chronic Kidney Disease Prediction Amali Amali; Candra Naya
Journal Innovation in Information and Computer Technology Vol. 2 No. 3 (2025): (September) Journal Innovation in Information and Computer Technology (JICTECH)
Publisher : PT. Altaf Publishing Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70895/jictech.v2i3.126

Abstract

Chronic Kidney Disease (CKD) is a serious health problem with increasing prevalence worldwide. Early detection is important to prevent severe kidney failure and reduce healthcare costs. This study aims to implement and compare the performance of Decision Tree C4.5 and Naïve Bayes algorithms for CKD prediction using a dataset from the UCI Machine Learning Repository containing 400 patient records and 24 clinical attributes. Data preprocessing included handling missing values, transforming categorical data into numerical form, and selecting relevant attributes. Model evaluation was conducted using 10-Fold Cross Validation with performance indicators including accuracy, precision, recall, and Area Under Curve (AUC). The results show that Decision Tree C4.5 achieved 93.00% accuracy, 84.27% precision, 100% recall, and 0.944 AUC. Meanwhile, Naïve Bayes obtained slightly better performance with 93.50% accuracy, 85.23% precision, 100% recall, and 0.948 AUC. The findings indicate that both algorithms are effective for CKD classification, although Naïve Bayes demonstrated better predictive performance, while Decision Tree C4.5 provided more interpretable classification rules. This research contributes to the development of intelligent decision support systems for early CKD diagnosis.
Co-Authors Afif Firmansyah Amali Amali Annisa Maulana Majid Arif Siswandi Arif Susilo Bayu Nugroho Daririn Daririn Desvi Ramadhani Syafitri Edi Tri Wibowo Eko Budiarto Elkin Rilvani Endah Yaodah Kodratillah Ermanto Ermanto Fairuz Kharida Gatot Tri Pranoto Ikhsan Romli Irfan Afriantoro Lathifah Zahroh Nawangsih, Ismasari Pupung Purnamasari Suryadi Unggul Prima Dhani