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Journal of Artificial Intelligence and Innovative Applications (JOAIIA)
Published by Universitas Pamulang
ISSN : 27161501     EISSN : 27754057     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 155 Documents
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Implementasi Metode Analytical Hierarchy Process (AHP) Untuk Evaluasi dan Pemilihan Karyawan Terbaik Berdasarkan Kinerja dan Kompetensi Studi Kasus Burger KiNG Cipondoh Raya Anggi Pradana Yoani; Endar Nirmala
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/joaiia.v7i1.57485

Abstract

Human resources are a crucial asset in supporting organizational success, particularly in the fast-food restaurant industry, which demands optimal employee performance and competence. However, employee evaluation processes that are still conducted manually tend to cause subjectivity and inconsistency in decision-making. This study aims to design and implement a decision support system to evaluate and determine the best employee at Burger King Cipondoh Raya using the Analytical Hierarchy Process (AHP) method. The AHP method was selected because it is capable of decomposing complex problems into a hierarchical structure and producing objective priority weights through pairwise comparisons. The evaluation criteria consist of two main aspects, namely performance, which includes responsibility, productivity, and work discipline, and competence, which covers knowledge, skills, and work attitude. The system was developed as a web-based application using the PHP programming language and MySQL as the database, following the waterfall development model. The data processing results indicate that the system is able to generate an objective employee ranking, in which the employee with the highest preference value obtained a final score of 0.449, and was therefore determined as the best employee. These results demonstrate that the implementation of the AHP method can assist management in conducting employee evaluations in a more accurate, fair, and measurable manner, as well as supporting accountable managerial decision-making.
Aplikasi Sistem Penujang Keputusan Penilaian Karyawan Terbaik dengan Metode Multi Attributive Border Approxmation Area Comparsion (MABAC) (Studi Kasus : PT. Wirasandi) Edison Putra Zebua; Shandi Noris
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/joaiia.v7i1.57505

Abstract

Employee performance evaluation is an important process in improving company productivity and work quality. However, the employee evaluation process at PT. Wirasandi was previously conducted manually, which could lead to subjectivity and inaccuracies in decision making. Therefore, this study aims to design and develop a Decision Support System (DSS) application for selecting the best employees using the Multi-Attributive Border Approximation Area Comparison (MABAC) method. The system is developed as a web-based application using PHP as the programming language and MySQL as the database management system. The MABAC method is applied to assist decision making by considering multiple evaluation criteria that have been determined. The stages of the MABAC method include constructing the decision matrix, normalization, weighting, determining the border approximation area, and calculating preference values to rank employees. The results of system testing using White Box and Black Box testing methods indicate that all system functions operate according to the specified requirements. The developed application is able to generate employee rankings objectively, accurately, and systematically. Therefore, this decision support system is expected to assist the management of PT. Wirasandi in determining the best employees effectively and efficiently.
Impelementasi Sistem Absensi Karyawan dengan Metode SAW Untuk Evaluasi Penilaian Kerja Karyawan di PT. Sejahtera Abadi Muhammad Rifal Junaidi; Dimas Abisono Punkastyo
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/joaiia.v7i1.57514

Abstract

Employee performance assessment is very important to determine the extent to which employees contribute to the company. At PT. Sejahtera Abadi, the employee evaluation process is still carried out in writing and is less objective, especially in assessing employee discipline and work attendance to get a bonus. Therefore, this study aims to build a digital-based employee attendance system equipped with the Simple Additive Weighting (SAW) method to help the employee work evaluation process more objectively and measurably. The SAW method is used because it is able to calculate and compare employee values ​​based on several criteria such as number of attendance, punctuality of arrival, and level of discipline. This system is designed in the form of a web-based application so that it is easily accessible to all employees. The results of the system implementation show that the SAW method is effective in helping companies conduct employee assessments fairly and accurately. With this system, it is hoped that the evaluation process will be faster, more efficient, and more transparent.
Penerapan Metode Profile Matching dalam Sistem Penunjang Keputusan untuk Menentukan Kelayakan Siswa PAUD Naik ke Jenjang Taman Kanak-kanak (TK) Berbasis Website di Pos PAUD Anggrek RW 09 Fathan Khaiza Septiansyah; Fadly Ariadi
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/joaiia.v7i1.57646

Abstract

Advances in information technology have encouraged educational institutions to improve the effectiveness of data-based evaluation and decision-making processes. POS PAUD Anggrek RW 09 still uses manual and subjective assessment methods to determine student eligibility for advancement to kindergarten (TK), resulting in an evaluation process that is inaccurate, unstructured, and time-consuming. This study aims to develop a website-based Decision Support System (DSS) using the Profile Matching method to help educators conduct objective, systematic, and measurable assessments. The Profile Matching method is used because it is able to compare students' ability profiles with ideal profiles based on child development criteria, such as motor skills, letter recognition, social interaction, vocabulary, counting, and independence. This system performs automatic calculations, starting from the GAP value, Core Factor and Secondary Factor weighting, to producing a final score and recommendations on student eligibility status. This study used observation, interviews, and literature review methods in data collection, and applied a system development method through the stages of analysis, design, implementation, and testing. The results showed that the decision support system that was developed was able to produce accurate and objective calculations to determine the eligibility of students to advance to kindergarten. The system also simplifies the data management process, improves evaluation efficiency, and provides transparency in the decision-making process at POS PAUD Anggrek RW 09. Thus, this website-based DSS can be an important tool in supporting the improvement of early childhood education quality.  
Sistem Pendukung Keputusan Pemilihan Bayi Stunting di Desa Parumasan Kabupaten Pandeglang menggunakan Metode Simple Additive Weighting (SAW) M Samsul Aripin; I Made Sugi Ardana
Journal of Artificial Intelligence and Innovative Applications (JOAIIA) Vol. 7 No. 1 (2026): February
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/joaiia.v7i1.58113

Abstract

Stunting remains a major public health issue in Indonesia, including in Parumasan Village, Pandeglang Regency, due to its long-term impacts on children’s growth, cognitive development, and overall health. The determination of stunting status at Puskesmas Cipeucang is still conducted manually through posyandu records and Excel-based recapitulation, which may lead to data inaccuracies and delays in treatment. To address these limitations, this study develops a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method as a structured assessment approach based on multiple health criteria relevant to stunting risk. The SAW method was selected for its ability to perform weighting and data normalization in a simple and accurate manner, making it suitable for implementation by healthcare workers. Data were collected through observations, interviews, and literature reviews. The results show that the SAW-based DSS processes child data more quickly and integratively compared to manual systems, thereby enhancing the effectiveness and efficiency of stunting risk identification. This system is expected to support healthcare workers in making more accurate decisions and contribute to stunting prevention efforts in the Puskesmas Cipeucang area.

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