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Palupiningsih, Pritasari
Institut Teknologi Perusahaan Listrik Negara
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Modification of Multi-Attribute Utility Theory in Determining Scholarship Recipient Students Arshad, Muhammad Waqas; Setiawansyah, Setiawansyah; Rahmanto, Yuri; Palupiningsih, Pritasari; Maryana, Sufiatul
BEES: Bulletin of Electrical and Electronics Engineering Vol 5 No 1 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v5i1.5523

Abstract

Educational scholarships are financial aid given to students or students to support the financing of their education. Mistakes in the assessment of scholarship recipients are often related to subjectivity and lack of transparency in the selection process. Unclear or inconsistent assessment criteria can lead to unfairness, where some deserving candidates may not get the same opportunities. The number of data used in Determining Scholarship Recipient Students is 10 students. The purpose of the MAUT modification research with geometric mean in producing criterion weights is to improve accuracy, stability, and consistency in the decision-making process. This study also aims to test the effectiveness of the geometric mean method in producing more objective and structured weights, as well as compare it with other traditional MAUT methods such as direct addition or multiplication. The modification of the MAUT method with a geometric mean is named G-MAUT. The results of the ranking of scholarship recipients using the G-MAUT method the first-place scholarship recipient with a final score of 1.0048 was obtained by Student 3, the second-place scholarship recipient with a final score of 0.6260 was obtained by Student 8, and the third-place scholarship recipient with a final score of 0.5048 was obtained by Student 5. This modification under the name G-MAUT allows for a more holistic and comprehensive assessment of potential recipients, ensuring that non-academic aspects are also taken into account proportionately.
The Decision Support System Uses the Preference Selection Index Method in Determining Healthy Cooperatives Sulistiani, Heni; Maryana, Sufiatul; Palupiningsih, Pritasari; Mehta, Abhishek
Bulletin of Informatics and Data Science Vol 2, No 2 (2023): November 2023
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v2i2.72

Abstract

Determining a healthy cooperative is a challenge that requires attention to several key aspects. Effective management, stable finances, active member involvement, and compliance with laws and regulations are key factors to be considered. By paying attention to all these factors and taking appropriate action, the cooperative can achieve optimal health levels and make a significant contribution to its members as well as the surrounding community. This study aims to determine healthy cooperatives using the Preference Selection Index (PSI) method in determining the best healthy cooperatives using the criteria of Capital, Quality of Productive Assets, Management, Efficiency, Liquidity, Independence, and Cooperative Identity so that the results of the best healthy cooperative ranking recommendations will be able to become recommendations for a decision. Based on the results of the calculation of the final value and ranking of the best healthy cooperatives using the PSI method, rank 1 is Koperasi-02 with a final value of 0.10737, rank 2 is Koperasi-01 with a final value of 0.10029, rank 3 is Koperasi-03 with a final value of 0.05223, rank 4 is Koperasi-04 with a final value of 0.0107. The results of testing using blackbox testing that has been carried out obtained the results of the number of answers from respondents have a value of 100% in accordance with testing the functionality of the system using blackbox testing
Employing PIPRECIA-S weighting with MABAC: a strategy for identifying organizational leadership elections Setiawansyah, Setiawansyah; Hadad, Sitna Hajar; Aldino, Ahmad Ari; Palupiningsih, Pritasari; Fitri Laxmi, Gibtha; Megawaty, Dyah Ayu
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7713

Abstract

The election of organizational leaders, especially in organizations whose members have diverse backgrounds and interests, can cause various problems. Problems in the selection of school organization leaders include the absence of an objective selection of organizational leadership candidates because they are selected based on comparisons between candidates without considering the criteria in the selection of organizational leadership candidates. Research related to the multi-attributive border approximation area comparison (MABAC) and simplified pivot pairwise relative criteria importance assessment (PIPRECIA-S) methods has never been conducted so far, so it is a reference in conducting this research using the MABAC and PIPRECIA-S methods. This study aims to select the head of the school organization using the MABAC method and PIPRECIA-S weighting can increase the objectivity of the criteria assessment results by relying on calculations from the PIPRECIA-S weighting method. Based on the selection results using the MABAC method and PIPRECIA-S weighting, candidate 1 was recommended as the leader of the school organization because it achieved rank 1 with a total score of 0.293. The contribution of this research is to help in the selection of the head of the organization using the PIPRECIA-S and MABAC methods as a decision-making solution.
Modification of the Grey Relational Analysis Method in Determining the Best Mechanic Arshad, Muhammad Waqas; Sulistiani, Heni; Maryana, Sufiatul; Palupiningsih, Pritasari; Rahmanto, Yuri; Setiawansyah, Setiawansyah
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.5678

Abstract

Determining the best mechanics in the industry has an important role to ensure the quality and reliability of the products and services offered. Competent and experienced mechanics are able to diagnose and repair accurately and efficiently, thereby minimizing operational downtime and increasing productivity. Without a structured system, mechanical performance appraisals tend to be subjective and inconsistent, which can lead to dissatisfaction among employees and customers. Mechanics may not get clear and constructive feedback on their performance, thus hindering skill development and professionalism. The purpose of the research of the modified Grey Relational Analysis (GRA) using standard deviation is to improve the accuracy and reliability of the decision-making process in situations where the data has a high degree of variability or significant uncertainty. By integrating standard deviations into the GRA, the study aims to account for variations and fluctuations in the data, which allows for more accurate and representative assessment of the criteria. This modification is expected to overcome the weaknesses of traditional GRAs that may not adequately consider data uncertainty, as well as produce more robust and realistic alternative rankings. The results of the best ranking of mechanics, Mechanic FR ranks first with a value of 0.11, followed by Mechanic HS with a value of 0.104. The third place was occupied by Mechanic AY with a score of 0.099.
PERBANDINGAN PERFORMA ARSITEKTUR CONVULUTIONAL NEURAL NETWORK UNTUK DETEKSI HAMA DAUN SAWI HIJAU Pratomo Prawirodirjo, Raden Ronggo Bintang; Meiwasandi, Putu Niar; Marcelindo, Fitto; Kusuma, Anndya Dyah; Palupiningsih, Pritasari
Jurnal Teknoinfo Vol 19, No 1 (2025): January 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v19i1.4453

Abstract

Sawi hijau merupakan komoditas pertanian penting di Indonesia, namun rentan terhadap serangan hama yang dapat menurunkan kualitas dan hasil panen. Penelitian ini mengeksplorasi penggunaan teknologi kecerdasan buatan, khususnya Convolutional Neural Networks (CNN), untuk mendeteksi hama pada tanaman sawi hijau secara akurat dan efisien. Tiga arsitektur CNN, yaitu VGG19, InceptionV3, dan Xception, diterapkan dan dibandingkan performanya dalam mengklasifikasikan citra daun sawi yang terserang hama. Metodologi meliputi pengumpulan dan preprocessing data citra, pemodelan dengan ketiga arsitektur, serta evaluasi menggunakan berbagai metrik kinerja. Hasil menunjukkan bahwa arsitektur VGG19 unggul dalam hal akurasi yaitu mencapai 96%, efisiensi penggunaan sumber daya, dan nilai MAPE terendah yaitu 4,61, menjadikannya pilihan optimal untuk implementasi sistem deteksi hama pada tanaman sawi hijau.
Hybrid Logarithmic Percentage Change-Driven Objective Weighting and Grey Relational Analysis Method in Employee Contract Renewal Setiawansyah, Setiawansyah; Rahmanto, Yuri; Aldino, Ahmad Ari; Yudhistira, Aditia; Palupiningsih, Pritasari; Sulistiyawati, Ari
TIN: Terapan Informatika Nusantara Vol 4 No 12 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i12.5121

Abstract

Contract employees are individuals who are hired for a specific period of time within a company or organization for a specific purpose. They usually do not have permanent employee status and are bound by work contracts that govern their tenure, salary, and other obligations. Despite not having long-term job security, contract employees often bring specialized skills or experience needed for specific projects. They are often instrumental in handling temporary projects, fulfilling temporary company needs, or filling temporary vacancies. One of the main problems in determining employee contract renewal is the lack of transparency and clear communication from the company. Employees often feel confused or uncertain about the criteria used by management in determining whether or not their contract will be renewed. Lack of clear information can cause anxiety and uncertainty among employees, and impair their performance and motivation. Hybrid Logarithmic Percentage Change-Driven Objective Weighting and Grey Relational Analysis (HLOPCOW-GRA) is an approach that combines two analysis methods, namely LOPCOW and GRA to improve accuracy and reliability in decision making. HLOPCOW-GRA provides an advantage in combining LOPCOW's advantage in handling dynamic data fluctuations with GRA's advantage in analyzing relative relationships between criteria, this approach allows decision makers to gain a deeper understanding of the factors that affect the final outcome. The results of alternative ranking showed that the first place with a GRA final value of 0.1406 was obtained by EM alternatives, second place with a GRA final value of 0.1366 was obtained by SVR alternatives, third place with a GRA final value of 0.1366 was obtained by SVR alternatives, third place with a GRA final value of 0.1406 was obtained by EM alternatives. The final GRA value of 0.1245 obtained alternative ASR.
Best Sales Selection Using a Combination of Reciprocal Rank Weighting Method and Multi-Attribute Utility Theory Palupiningsih, Pritasari; Setiawansyah, Setiawansyah
Journal of Computing and Informatics Research Vol 3 No 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i3.1496

Abstract

The best salespeople are individuals who are not only able to meet or exceed sales targets, but also demonstrate exceptional skills in building relationships with customers, understanding their needs, and offering effective solutions. The problem of selecting the best salespeople often involves the challenge of an objective and fair assessment, as diverse evaluation criteria can affect the final result. One of the main obstacles is the presence of subjectivity in judgment, which can arise from personal preferences or pressure to maintain good relationships. This study aims to implement a sales performance evaluation model that combines the Reciprocal Rank Weighting and Multi-Attribute Utility Theory (MAUT) methods to obtain a more accurate and objective assessment of sales performance. This research contributes to the management literature and decision support systems by offering a new approach in sales performance evaluation. This opens up opportunities for further research and practical applications in the field of performance evaluation and salesforce management. Based on the final score calculated using the MAUT method, the salesperson rank from best to lowest is as follows: Sales 7 is ranked top with a value of 0.646, indicating the best overall performance. Sales 3 followed in second place with a value of 0.6125, followed by Sales 9 with a value of 0.5604 in third position.
Optimizing the best student selection: hybrid K-Means approach and entropy-grey relational analysis Sulistiani, Heni; Setiawansyah, Setiawansyah; Palupiningsih, Pritasari; Ferico Octaviansyah Pasaribu, Ahmad; Andika, Rio; Hamdan Sobirin, Muhammad
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.8715

Abstract

The selection of the best students is an important process in recognizing students' achievements and dedication in various fields. Through careful and fair selection, students who stand out in both academic and non-academic terms can be identified and assigned. The purpose of the research on the use of hybrid entropy-grey relational analysis (GRA) and K-Means clustering in the selection of the best students is to develop a more objective, accurate, and comprehensive assessment system. The silhouette score results show that 2 clusters have a value of 0.5733, so in this study 2 clusters are used with the best cluster at cluster 0. Data from cluster 0 will be used in determining the best students using hybrid entropy-GRA. The results of the best student ranking using the hybrid entropy-GRA method, for the first best student with a final score of 0.25 were obtained by Mareta Amelia. The hybrid approach of K-Means and entropy-GRA offers a powerful tool to improve decision-making in the student selection process. The hybrid approach of K-Means grouping and entropy-GRA presents a powerful solution, improving the decision-making process and ensuring that high-achieving students are accurately recognized and rewarded.
Integration of G2M Weighting and MOORA in Accurate Decision Making for Best Alternative Selection Setiawansyah, Setiawansyah; Wang, Junhai; Palupiningsih, Pritasari
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 11, No 2 (2025): December 2025
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/coreit.v11i2.36679

Abstract

The goal of the integration of the G2M Weighting and MOORA methods is to produce the best alternative selection decisions that are more accurate and objective. By combining rational criteria weighting through G2M Weighting and alternative evaluation using MOORA, it is hoped that it can reduce bias and increase transparency in decision-making. In addition, this study compares alternative ratings from the application of the MOORA method and other weighting methods. The results of the evaluation and ranking of scholarship recipients using G2M weighting and MOORA, CF candidates managed to occupy the first position with a final score of 0.2727, showing the best performance among all candidates. In second place, UT candidates obtained a score of 0.2630, followed by DF candidates with a score of 0.2445 and SS candidates with a score of 0.2425. This approach makes it a very useful solution in the selection of the best alternatives in a wide range of multi-criteria decision applications. The results of the Spearman correlation test showed that the G2M weighting method had the highest correlation of 0.9879, which showed a very high similarity with the initial rating. The Entropy Weighting and CRITIC methods also showed a strong correlation, of 0.9515 and 0.9636, respectively, although there was slight variation in the alternate sequence. Meanwhile, the MEREC weighting has the lowest correlation of 0.9273, but still shows a very strong relationship. Overall, these results suggest that the G2M method produces rankings consistent with the initial rankings, with variations indicating sensitivity to criterion weighting.
Co-Authors Aditia Yudhistira Ahmad Ari Aldino Alwi Muhammad Andi Dahroni Andi Muhammad Fadel Omar Pasha Andi Nikma Sri Handayani Andika, Rio Ari Sulistiyawati Arshad, Muhammad Waqas Budi Prayitno Dahroni, Andi Dody Dody Eka Putra Ferico Octaviansyah Pasaribu, Ahmad Firmansyah Apryadhi Gibtha Fitri Laxmi Hamdan Sobirin, Muhammad Haryono Haryono Heni Sulistiani Kusuma, Anndya Dyah Marcelindo, Fitto Megawaty, Dyah Ayu Mehta, Abhishek Meiwasandi, Putu Niar Muhammad Fadli Pratama Muhammad fadli Prathama Muhammad Fadli Prathama Nasril Sany Pratomo Prawirodirjo, Raden Ronggo Bintang Prawirodirjo, Raden Ronggo Bintang Pratomo Putri Ayu Mardhiyah Rakhmadi Irfansyah Putra Rd.M.Dimas Burhanudin Akbar Riki Ruli A. Siregar, Riki Ruli A. Setiawansyah Setiawansyah Sitna Hajar Hadad Sufiatul Maryana Sujiwanto, Atam Rifa'i Wang, Junhai Yessy Asri Yuri Rahmanto