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Journal : International Journal Engineering and Applied Technology (IJEAT)

COMPARISON C4.5 AND NAÏVE BAYES METHODS BASED ON PARTICLE SWARM OPTIMIZATION IN LEVELS OF DROP OUT STUDENTS dudih gustian; Faridatun Ni’mah; Agus Darmawan
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 2 No. 2 (2019): International Journal of Engineering and Applied Technology (IJEAT)
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/ijeat.v2i2.19

Abstract

The high percentage of drop-out students causes a campus management problem, this is because the percentage of students graduating on time is one of the elements of accreditation assessment set by the national accreditation board of higher education. One reason why the drop out rate is still high is because the Management System has not run well, such as lecturer professionalism, campus facilities, academics and administration, student affairs, outside influence and student personality. This study aims to analyze several indicators that can cause student drop outs by comparing the C4.5 method based on particle swarm optimization and Naïve Bayes based on PSO. This study contributes to campus management in anticipating the occurrence of drop outs through indicators that occur and can predict student drop out rates through the classification process. The highest level of accuracy produced from C4.5 + PSO is around 99.32% with AUC from Naïve Bayes is 0.974 categorized as excellent classification.
Decision Support System For New Employee Recruitment In PT. Prosweal Indomax Using The Simple Additive Weighting Anti Aprianti; Yayatillah Rubiati; Muhamad Renaldi Aripin; Cecep Warman; Dudih Gustian
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 3 No. 1 (2020): International Journal of Engineering and Applied Technology (IJEAT)
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (865.115 KB) | DOI: 10.52005/ijeat.v3i1.39

Abstract

The eligibility for hiring new employees based on certain criteria that the company expects is something that is very rarely obtained. The acceptance process may result in inaccurate and productive decisions due to inefficient admission processes. There are several criteria in making decisions about the recruitment of new employees at PT. Prosweal Indomax, which is based on latest education, expertise, age and work experience. Purpose made This system is able to help make decisions to determine the optimal recruitment process using the method Simple Additive Weighting (SAW). This method was chosen because this method determines the weight value for each attribute, then is followed by a ranking process that will select the best alternative. The research was conducted by finding the weighted value for each criterion, and then creating a ranking process that would determine which alternative was the best applicant.
PRIORITY PROGRAM SELECTION OF VILLAGE FUND USING THE K-MEANS METHOD Ati Sulastri; Siti Khalifah; Dhea Lestari; Dudih Gustian; Muhamad Muslih; Kirishchieva Irina Rafaelevna
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 3 No. 2 (2020): International Journal of Engineering and Applied Technology (IJEAT)
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1118.891 KB) | DOI: 10.52005/ijeat.v3i2.61

Abstract

The allocation of funds is certainly a big village also demands a big responsibility for the village government. In managing public funds, a public sector organization is required to be able to provide accountable financial reports. To achieve the effectiveness of village financial management, a decision support system is needed to assist village officials in determining which village programs will be prioritized. This research focuses on village programs that use village fund allocations. The purpose of this study is to create a decision support system todetermine priority village fund programs using a web-based kmeans clustering algorithm. The k-means clustering algorithm can perform the modeling process without supervision (unsupervised) and is one of the methods that performs data grouping using the partition system. This is in accordance with the desired end result in the form of grouping the village work program into 3 priority levels, where the village road repair program is included in the high-level priority program in cluster 1, the BUMDES program is included in the medium level priority in cluster 2 and the program for the construction of a reservoir for incoming rainwater. in low priority cluster 3. This research was conducted by considering the aspects of urgency and usefulness developed using the programming language PHP version 5 and MySQL database version 3.2.1.
Broken Road Detection Methods Comparison: A Literature Survey Indra Yustiana; Somantri; Dudih Gustian; Anggy Pradifta Junfithrana; Satish Kumar Damodar
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 5 No. 2 (2022): November 2022
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/ijeat.v5i2.75

Abstract

Roads are infrastructure built to facilitate regional development. Good road conditions will certainly provide a sense of comfort for every vehicle that will pass through it. For that, care and attention to road conditions needs to be done. The occurrence of damage to the road will hinder the development process. Currently, detection of damaged roads is still done manually using human resource. It makes the detection process take quite a lot of time to determine how bad the damage is. So there needs a way to help improve time efficiency and accuracy in detecting damaged roads. One of them is by utilizing machine learning technology. In this paper, we will discuss what methodology can be use and their comparisons to be able to use appropriate and effective methodologies to detect cases of damaged roads
MACRO VBA-BASED MAIL SERVICE ADMINISTRATION INFORMATION SYSTEM IN VILLAGES AND SATISFACTION ANALYSIS USING NAÏVE BAYES CLASIFICATION Dudih Gustian; A. Oktian Permana; Sihabudin; Lucas Crammer
INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT) Vol. 6 No. 1 (2023): May 2023
Publisher : Nusa Putra University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52005/ijeat.v6i1.81

Abstract

Based on the Law of the Republic of Indonesia Number 25 of 2009 concerning Services, public services must achieve good and clean governance, have less time discipline and tend to slow down the process, as well as a lack of professionalism from employees who are not responsible for their work. In addition to providing benefits and information to the village government, administrative services for research letters also affect quality and performance. The stages that will be carried out in this study include observation, interviews, and literature study from previous research. The Naïve Bayes classification method is used in this study, where the basic calculation is based on the probability of each attribute. If an attribute with a certain class has a value of zero, then the probability of that class will also be zero, and this will affect the final result of the Naïve Bayes calculation. Questionnaire result data is divided into 60% training data, 40% testing data, and 10% validation data. The evaluation results show an accuracy rate of 98.6% for training data, 100% for testing data, and 97.2% for validation data. The comparison shows that there is only a change of 2% after using the mail service administration information system
Co-Authors A. Oktian Permana Aan Setiawan Aan Setiawati Aang Hasanudin Acep Saepulrohman Ade Bahrum Adhitia Erfina Aditya Nurfitri Agum Taufikurrahman Alia Ahadi Argasah Alun Sujada Ammar Ammar Anang Suryana Anggy Pradiftha Junfithrana Anita Rahayu Annisa Desi Pratiwi Anti Aprianti Arti Hariyanti Ati Sulastri Azkia Aura Shanda Cecep Warman Debby Rahmawati Debby Rahmawaty Dede Irwan Dede Wahidin Dewa Saepurrahman Dewi Destinasari Dharma Saputra Dhea Lestari Dicki Nugraha Edwinanto Ekky Noor Mahmudi Elsa Ramadanti Eneng Mia Rizkianti Enti Sulastri falentino sembiring Faridatun Ni’mah Fatwa Adib Soetedjo Fauziah Nur Octafiani Fuji Apriani Harry Atmami Heri Firmansyah Imam Faisal Arridzwani Indra Supriadi Indra Yustiana Jelita Asian Jihad Hari Jordan Chan William Kirishchieva Irina Rafaelevna Kudin Rustaman Lucas Crammer M Dezan Sya’ban S M. Syukron Nawawi M. Yosef Ismatulloh Marina Artiyasa Maryam Nurhasanah Mega Lumbia Sinaga Megasari Putri Meisa Sindriama Rinelda Mia Kurniasari Mochamad Khilmi Mohamad Najib Muahamad Taufik Muhamad Amar Muhamad Renaldi Aripin Muhamad Salman Al-Farits Muhamad Zaenal Abidin Muhamd Ammar Muhammad Ammar Muhammad Arip Muhammad Arsyad Muhammad Iqbal Ahmadi Muhammad Wildan Goni Muslih, Muhamad Neng Resti Noviansyah Nunik Destria Arianti Nur Apriyanti Nur Apriyanti Nur Fauza Muhidin Nuraeni Pahmi, Samsul Paikun Rahayu Awaliyah Rian Nugraha Rico Sihotang Rifaldi Zulkarnaen Rimalya Widian Rinrin Rinrin Rintho Rante_Rerung RR. Ella Evrita Hestiandari Rudi Heryanto Saepudin, Sudin Salsa Lisna Audina Sarah Sifa Antadipura Sastradipraja, C K Satish Kumar Damodar Selsa Khairunisa Fadiya haya Sihabudin Sihabudin Sihabudin Siti Handayani Siti Hasna Fadhilah Siti Khalifah Siti Olis Somantri Somantri Taufik Bahrul Alam Wildan Riswandi Wulan Alinda Wahyumi Yayatillah Rubiati Yoga Vikriansyah Yudi Nata Yunita Gusti Nurani Yusuf Iskandar Zaid Sulaiman