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Contact Name
Asep Erlan Maulana
Contact Email
dosen02716@unpam.ac.id
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+6281299366151
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jiup@unpam.ac.id
Editorial Address
Ruang Gugus Mutu Fakultas Ilmu Komputer Universitas Pamulang - Kampus Viktor Lt. 3 Jalan Raya Puspitek No. 46 Buaran, Serpong, Tangerang Selatan, Banten, Indonesia
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Kota tangerang selatan,
Banten
INDONESIA
Jurnal Informatika Universitas Pamulang
Published by Universitas Pamulang
ISSN : 25411004     EISSN : 26224615     DOI : https://doi.org/10.32493
Core Subject : Science,
Jurnal Informatika Universitas Pamulang is a periodical scientific journal that contains research results in the field of computer science from all aspects of theory, practice and application. Papers can be in the form of technical papers or surveys of recent developments research (state-of-the-art). Topics cover the following areas (but are not limited to): Artificial Intelligence Big Data Business Intelligence Data mining Decision Support Systems Intelligent Systems Machine Learning Network and Computer Security Optimization Pattern Recognition Soft Computing Software Engineering
Articles 625 Documents
Sistem Pendukung Keputusan Penerimaan Pegawai PT. Andalusia Nur Ramadhan dengan Metode Simple Additive Weighting Bramantara Yudha
Jurnal Informatika Universitas Pamulang Vol 5, No 4 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i4.8177

Abstract

The purpose of the hiring decision support system is to assist and speed up the decision-making process. There are so many methods that companies can apply in determining employee acceptance to rank prospective employees according to the results of the assessment, examples of methods that can be used are the SAW method or Simple Additive Weighting using the Java Netbeans application and the MySQL database. This research produces a system that can assist in providing decision support for hiring employees. So as to help the main director to determine and select employees who are accepted by the company PT. Andalusia Nur Ramadhan.
Implementasi Metode SAW dan TOPSIS dalam Penentuan Kinerja Karyawan Terbaik pada Perusahaan Penukaran Uang Nia Nuraeni
Jurnal Informatika Universitas Pamulang Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i3.6749

Abstract

Employees are the most important part in a company. In the process of managing employees or human resources department (HRD), it can affect many aspects that determine the success of the work at the company. In the process, the employee performance appraisal at money exchange companies is done manually, so that the employee performance appraisal is less objective and requires a long assessment process so it is inefficient and ineffective. With the system used in the performance appraisal process, it is hoped that it can help companies to assess employee performance quickly and precisely and objectively determine the best performing employees. The methods used in this employee performance appraisal system are the SAW and TOPSIS methods, where the results of the best employee performance appraisal process in both methods produce the same employee data recommendations.
Penerapan Algoritma Convolutional Neural Network dalam Klasifikasi Telur Ayam Fertil dan Infertil Berdasarkan Hasil Candling Muhammad Rizky Firdaus
Jurnal Informatika Universitas Pamulang Vol 5, No 4 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i4.8556

Abstract

Fertile chicken eggs are eggs that can hatch because these eggs have a development in the form of dots of blood and blood vessels or can be called an embryo, while infertile chicken eggs are a type of egg that cannot be hatched because there is no embryo development in the hatching process. Inspection of infertile chicken eggs must be carried out especially for breeders who will carry out the selection and transfer of fertile chicken eggs and infertile chicken eggs. However, currently, the selection of fertile and infertile chicken eggs is still using a less effective way, namely only by looking at the egg shell or called candling, this process is certainly less accurate to classify which eggs are fertile and infertile eggs because not all breeders are able to see the results of the eggs properly. candling so that the possibility of prediction errors. Therefore, in this study, a classification of fertile chicken eggs and infertile chicken eggs will be carried out based on candling results using the Convolutional Neural Network method. From the results of the classification carried out, the percentage of accuracy obtained for the classification of fertile and infertile chicken eggs is 98% and an error of 5%.
Performa Algoritma User K-Nearest Neighbors pada Sistem Rekomendasi di Tokopedia Rama Dian Syah
Jurnal Informatika Universitas Pamulang Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i3.6312

Abstract

The biggest marketplace in Indonesia such as Tokopedia has data on e-commerce activities that always increase with time. Large data growth in Marketplace can cause problems for users. Buyers who have difficulty in finding the best product that suits their needs and sellers who have difficulty in promoting products that are often visited by buyers can be overcome. The recommendation system can overcome these problems by providing specific product recommendations to be promoted and offered to buyers. This research implements the Recommendation System using the Item Rating Prediction Method by applying the User K-Nearest Neighbors Algorithm. The Recommendation System provides recommendations based on ratings on products given by the buyer. Algorithm performance in Recommendation System is measured by the parameters of Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Normalized Mean Absolute Error (NMAE). The performance values obtained are RMSE = 0.713, MAE = 0.488 and NMAE = 0.122. Perfomance values below 1 proves that the User K-Nearest Neighbors Algorithm is suitable as a rating prediction model on recommendation system.
Sistem Tracer Study dan Monitoring Alumni Universitas Pamulang Heri Haerudin; Ari Syaripudin; Dimas Abisono Punkastyo; Farida Nurlaila; Joko Riyanto
Jurnal Informatika Universitas Pamulang Vol 5, No 4 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i4.7086

Abstract

In the implementation of higher education, of course, the relevance of the curriculum is needed in improving the quality of learning. One of the efforts to fulfill this is through alumni tracking (tracer study). Tracer study is a strategy that allows higher education institutions to obtain input on adjusting the curriculum to current industry needs so that it can become the basis for future improvements. Lack of distribution and collection of questionnaires again became a problem for the tracer study team, because during its implementation there was little response from alumni and stakeholders. Therefore we need a system that can be used to collect and manage and present data accurately from the measurement results of the tracer study in the form of parameters such as work status, job relevance, level of importance of educational services, level of satisfaction of educational services, and the influence of thesis quality. As well as measuring the level of stakeholder satisfaction with alumni with parameters in the form of ethics and morals, expertise based on scientific fields, skills in communication, and teamwork. The results showed that the process of collecting and processing tracer study instruments according to the parameters required in the accreditation process was easier to do because it was website-based. Besides, it made it easier for alumni and stakeholders to fill out the questionnaire, so that more feedback was obtained by the tracer study team.
Daftar Isi Jurnal Informatika Universitas Pamulang Vol. 5 No. 3 September 2020 Journal Manager
Jurnal Informatika Universitas Pamulang Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i3.7338

Abstract

Daftar Isi Jurnal Informatika Universitas Pamulang Vol. 5 No. 4 Desember 2020 Journal Manager
Jurnal Informatika Universitas Pamulang Vol 5, No 4 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i4.9021

Abstract

Pemilihan Warga Penerima Bantuan Program Keluarga Harapan (PKH) Menggunakan Metode Simple Additive Weighting (SAW) dan User Acceptance Testing (UAT) Pujianto, Pujianto; Mujito, Mujito; Prabowo, Danang; Prasetyo, Basuki Hari
Jurnal Informatika Universitas Pamulang Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i3.6671

Abstract

PKH (Hope Family Program) is a government assistance program to help people experiencing poverty problems this program is an aid from the ministry of social affairs in order to reduce social inequality among poor groups. so it is hoped that in the long run it can break the relationship of poverty between generations. so that the next generation can come out of the abyss of poverty due to the increasing quality of human resources produced. The aspects used are health aspects, educational aspects and aspects of social welfare.  The selection of citizens who are not objective recipients of the PKH Program makes it a problem. Many protested against the village's devices in determining which residents were entitled to assistance and sometimes acts of vandalism. so that in this study want to help village devices in selecting citizens who are entitled to receive assistance using the system. The methods used are Simple Additive Weighting (SAW), and User Acceptance Testing (UAT) is used to test the feasibility of the application. A sample of 10 residents who were recommended to receive PKH assistance obtained the results that Mr. Anwar who ranked first for assistance with a score of 80.5 And for the testing UAT earned an average value of 87%.
Implementasi Sistem Mobile Learning pada MI Taufiqul Athfal Bogor Andi Prastomo
Jurnal Informatika Universitas Pamulang Vol 5, No 4 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i4.7821

Abstract

The application of technology in education is being developed very intensively today, especially the use of technology to support the teaching and learning process. The transfer of conventional learning methods such as face-to-face in the classroom towards a modern direction such as distance learning using computer-based systems or smartphones (Mobile Learning) has become a common thing implemented in today's education world. But not all educational institutions implement the same thing as MI Taufiqul Athfal Bogor. The purpose of this study was to design and implement a distance learning system based on android with smartphone media (Mobile Learning) to help MI Taufiqul Athfal Bogor in the teaching and learning process. The research method used is the Research & Development (R&D) method. System testing was carried out using the ISO 9126 method by distributing questionnaires to 20 respondents who were teachers at MI Taufiqul Athfal. The test results with four aspects of ISO 9126, namely aspects of Fuctionality, Reliability, Usability, and Efficiency produce an overall Actual Total score, namely Total% Actual of 90%, thus concluding that the quality of the system is Very Good to implement. The final result of this research is an Andiroid-based Mobile Learning system designed by researchers which is implemented very well at MI Taufiqul Athfal and helps support the distance teaching and learning process.
Analysis and Design of Decision Support System for Employee Performance Appraisal with Simple Additive Weighting (SAW) Method Taufiq, Rohmat; Septarini, Ri Sabti; Hambali, Ahmad; Yulianti, Yulianti
Jurnal Informatika Universitas Pamulang Vol 5, No 3 (2020): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v5i3.6777

Abstract

The decision support system (DSS) for employee performance appraisal is a decision support system used in the employee performance appraisal process at PT. Surya Toto Tbk. Currently, the employee performance appraisal process still done manually (paper-based) so that the reports produced were not real-time. From the existing problems, this research aimed to analyze and design a decision support system according to the existing criteria using the Simple Additive Weighting (SAW) method to be able to develop into a Web-based DSS. The method used began with communication with management, especially the perpetrators of employee performance appraisals. Furthermore, planning, the process of data collection, analysis, design, and finally making reports carried out. The conclusion of this study provided a suggestion to use the criteria that had given two more criteria. By giving weights and calculations carried out for three employees, the value obtained for employee C got the highest score (0.98) followed by employee B, and the lowest score (0.85) was employee A.

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