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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Computatio : Journal of Computer Science and Information Systems Jurnal Akuntansi Jurnal CoreIT Jurnal Komputasi Network Engineering Research Operation [NERO] BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Teknoinfo Krea-TIF: Jurnal Teknik Informatika Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Madani Jurnal Tekno Kompak Building of Informatics, Technology and Science Jurnal Sistem Informasi dan Informatika (SIMIKA) Journal of Computer System and Informatics (JoSYC) TIN: TERAPAN INFORMATIKA NUSANTARA JiTEKH (Jurnal Ilmiah Teknologi Harapan) Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Mattawang: Jurnal Pengabdian Masyarakat JTIKOM: Jurnal Teknik dan Sistem Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Ilmiah Infrastruktur Teknologi Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal Pendidikan dan Teknologi Indonesia KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Telematics and Information Technology (TELEFORTECH) Jurnal Ilmiah Sistem Informasi Akuntansi (JIMASIA) Paradigma Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Edutic : Pendidikan dan Informatika Malcom: Indonesian Journal of Machine Learning and Computer Science Journal of Computing and Informatics Research JEECS (Journal of Electrical Engineering and Computer Sciences) Bulletin of Informatics and Data Science Jurnal Ilmiah Computer Science Jurnal Informatika dan Rekayasa Perangkat Lunak Journal of Social Sciences and Technology for Community Service Jurnal Komputasi
Dedi Darwis
Universitas Teknokrat Indonesia
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Combination of MOORA and ITARA Methods in Decision Support Systems for Measuring the Performance of Quality Control Teams Hendrastuty, Nirwana; Wang, Junhai; Sulistiyawati, Ari; Darwis, Dedi; Setiawansyah, Setiawansyah; Jumaryadi, Yuwan; Sumanto, Sumanto
TIN: Terapan Informatika Nusantara Vol 6 No 6 (2025): November 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i6.8382

Abstract

The problems that often arise in evaluating the performance of the Quality Control team are the subjectivity in determining the weight of criteria and the limitations of traditional methods in producing objective and consistent rankings. To address this issue, this research integrates the Indifference Threshold-based Attribute Ratio Analysis (ITARA) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) methods within a decision support system. The ITARA method is used to determine the weights of criteria based on data variation, making them more representative of real conditions, with the result that Accuracy of Product Defect Identification becomes the most dominant criterion with a weight of 0.3999, followed by Response Speed to Issues at 0.1877, while other criteria have lower weights. Furthermore, the MOORA method is used to calculate the preference of alternatives, resulting in a final ranking. The analysis results indicate that the Quality Assurance Team ranks first, followed by the Quality Improvement Team in second place, while the Quality Inspection Team is in the last position. To test the reliability of the model, a sensitivity analysis was conducted by varying the weights of the main criteria. The results show that the ranking structure is relatively stable, with changes only occurring in the positions of the first and second ranks when the accuracy weight is reduced by 0.2. In conclusion, the combination of ITARA-MOORA proves to be capable of producing objective, robust, and reliable performance evaluations as a basis for strategic decision-making in enhancing the quality of the quality control teams.
Decision Support System for Selecting the Best Restaurant Waiter Using a Combination of WENSLO Weighting and AROMAN Methods Aryanti, Riska; Wang, Junhai; Wahyudi, Agung Deni; Setiawansyah, Setiawansyah; Darwis, Dedi
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i2.4

Abstract

The quality of service staff is a key factor in determining business success because they are the front line that interacts directly with consumers. However, performance evaluations of service staff are often still carried out subjectively, based only on the supervisor's perception or brief experiences with customers. This research discusses the application of a decision support system to determine the best restaurant service by combining the Weights by Envelope and Slope (WENSLO) method in criteria weighting and the Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN) in the alternative ranking process. The dataset used in this study was collected in 2025 from one of the restaurants in the Lampung area, involving nine waiters as evaluation candidates using six criteria. The six criteria used consist of four benefit criteria: service speed, friendliness, accuracy, and customer satisfaction. The weighting results using the WENSLO method indicate that the order mistakes criterion received the highest weight of 0.7253, followed by completion time with a weight of 0.1700, while the other criteria have relatively small weights. The AROMAN method is used to calculate the final values of alternatives based on the specified weights, resulting in a ranking of restaurant servers. The analysis shows that alternative Waiters KS ranks first with the highest score of 1.6097, followed by Waiters QN and Waiters RB. This finding proves that the combination of the WENSLO and AROMAN methods can produce objective, systematic results, and supports restaurant management in making strategic decisions regarding the selection of the best employees.
PERBANDINGAN METODE NAÏVE BAYES DAN SVM UNTUK SENTIMEN ANALISIS MASYARAKAT TERHADAP SERANGAN RANSOMWARE PADA DATA KIP-K Nabil Safiq Ramadan; Dedi Darwis
Jurnal Sistem Informasi dan Informatika (Simika) Vol. 8 No. 1 (2025): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v8i1.3621

Abstract

This research examines ransomware attacks on KIP-K data by analyzing the opinions of Social Media X users, using the naïve bayes classifier (NBC) and support vector machine (SVM) methods. The rapid development of technology not only brings great benefits but also increases the risk of digital attacks by certain parties. One example is a ransomware attack that caused a KIP-K data leak. In this study, sentiment analysis was applied to identify public opinions or responses obtained from Social Media X, with the help of python programming and google colab. Of the total 2,648 raw data collected, pre-processing was carried out resulting in 1,738 cleaned data. The study compared two methods, namely Naïve Bayes and Support Vector Machine, to determine what method is more effective in analyzing public sentiment related to ransomware attacks on KIP-K data. The focus of this study is to understand the percentage of Social Media X users' comments and responses related to the KIP-K ransomware taken from media sosial X. The stages of sentiment analysis in this study include crawling, labeling, preprocessing, method classification, and visualization. Before the classification process was carried out, the data was divided into two parts, namely 30% for test data and 70% for training data. Data labeling resulted in 1,313 negative data, 957 positive data and 377 neutral data. The classification results show that the NBC method has an accuracy of 70%, while the SVsM achieves an accuracy of 88%. Based on these results, SVM is proven to be superior in data analysis compared to NBC, especially for big data.
Komparasi Metode Scoring System dan Profile Matching untuk Mengukur Kinerja Karyawan pada PT Wahana Rahardja Dedi Darwis
Jurnal Komputasi Vol. 7 No. 2 (2019)
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v7i2.2424

Abstract

PT Wahana Rahardja is one of the companies in the field of material supply located in Bandarlampung. In this company, one of the management activities undertaken is to evaluate and evaluate employee performance so that based on the results of the assessment and evaluation, reward and punishment can be determined for employees. Currently, the way leaders in assessing employees are still based on perceptions and analysis so as not to produce an objective assessment. Therefore, a method is needed to measure employee performance so that the assessment can be more objective. In this study the method applied is scoring syetem and profile matching, the two methods will be compared and tested which is better and suitable to be applied in assessing employee performance at PT Wahana Rahardj. Employee performance appraisal is carried out using 3 aspects namely intelligence aspects, aspects of work attitudes and behavioral aspects and each aspect has sub-criteria. The results obtained from testing the Scoring System and Profile Matching methods show different results, the Profile Matching method is the method that will be recommended as the most appropriate method in evaluating employee performance because it can provide more objective results.
Aplikasi Web Pemetaan Wilayah Kelayakan Tanam Jagung Berdasarkan Hasil Panen di Kabupaten Lampung Selatan Agung Tri Prastowo; Dedi Darwis; Nurhuda Budi Pamungkas
Jurnal Komputasi Vol. 8 No. 1 (2020)
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v8i1.2531

Abstract

South Lampung Regency is a district with the capital city of Kalianda which dominates agricultural areas, one of which is corn. With the corn harvest spread in each district in the South Lampung Regency, it will attract investors to invest or invest in corn farming in the South Lampung region. This application was built with the aim of making it easier for the community and potential investors to see the potential of the sub-district corn planting area based on the yield in the form of map visualization to make it easier to find the location of the area to be planted with corn. The result of this application is a web-based system in the form of map visualization to show potential areas for planting corn. Based on the results of tests conducted, this application has a percentage score of 85.96% meaning this application is very good to be implemented.
Optimizing E-Commerce Platform Selection Using Root Assessment Method and MEREC Weighting Junhai Wang; Dedi Darwis; Rakhmat Dedi Gunawan; Fenty Ariany
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 1 (2025): Volume 6 Number 1 March 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i1.6

Abstract

The number of users of e-commerce platforms has increased significantly in recent years, and consumers are now more likely to shop online due to ease of access, diverse product choices, and flexibility in transaction times. The difficulty in determining the best e-commerce platform is often caused by subjectivity in the weighting of the criteria used for evaluation. The weighting process is carried out based on the preferences of certain individuals or groups, without considering objective data. This research aims to apply an objective, structured, and accurate approach in evaluating and ranking e-commerce platforms based on relevant multi-dimensional criteria. By using the root assessment method, the evaluation process can be carried out systematically through hierarchical analysis, while the MEREC weighting ensures that the weight of each criterion reflects its real impact on the outcome of the decision. Through the combination of these two methods, this research is expected to make a significant contribution to improving the quality of decision-making, especially in helping users or business people choose the e-commerce platform that best suits their needs. The results of the final score calculation Platform E was ranked first with the highest score of 4.87083, Platform A was ranked second with a score of 4.85162, and Platform B was ranked third with a score of 4.83842. Future research should address the identified limitations by exploring the integration of advanced predictive analytics and artificial intelligence techniques to improve the adaptability and resilience of models. In addition, sensitivity analysis of the MEREC Root Assessment and Weighting Methods should be performed to understand its performance under various data conditions.
Decision Support System for Selecting the Best Restaurant Waiter Using a Combination of WENSLO Weighting and AROMAN Methods Riska Aryanti; Junhai Wang; Agung Deni Wahyudi; Setiawansyah Setiawansyah; Dedi Darwis
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 10 No. 2 (2025): December
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v10i2.4

Abstract

The quality of service staff is a key factor in determining business success because they are the front line that interacts directly with consumers. However, performance evaluations of service staff are often still carried out subjectively, based only on the supervisor's perception or brief experiences with customers. This research discusses the application of a decision support system to determine the best restaurant service by combining the Weights by Envelope and Slope (WENSLO) method in criteria weighting and the Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN) in the alternative ranking process. The dataset used in this study was collected in 2025 from one of the restaurants in the Lampung area, involving nine waiters as evaluation candidates using six criteria. The six criteria used consist of four benefit criteria: service speed, friendliness, accuracy, and customer satisfaction. The weighting results using the WENSLO method indicate that the order mistakes criterion received the highest weight of 0.7253, followed by completion time with a weight of 0.1700, while the other criteria have relatively small weights. The AROMAN method is used to calculate the final values of alternatives based on the specified weights, resulting in a ranking of restaurant servers. The analysis shows that alternative Waiters KS ranks first with the highest score of 1.6097, followed by Waiters QN and Waiters RB. This finding proves that the combination of the WENSLO and AROMAN methods can produce objective, systematic results, and supports restaurant management in making strategic decisions regarding the selection of the best employees.
The Combination of WENSLO and MUNRA Method in Selecting the Best Employees Based on Multiple Criteria Junhai Wang; Setiawansyah Setiawansyah; Adhie Thyo Priandika; Dedi Darwis; Ari Sulistiyawati
Journal of Computing and Informatics Research Vol 5 No 2 (2026): March 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v5i2.2472

Abstract

This study examines the application of a combination of the WENSLO and MUNRA methods in selecting the best employees based on various criteria to address issues of subjectivity and instability in employee rankings that often arise when data is heterogeneous and criteria are conflicting. The WENSLO method is used to assess and prioritize criteria through structured and preference-based weighting, while MUNRA plays a role in consistently normalizing data and calculating weighted scores for each alternative. The integration of these two methods allows for a more objective evaluation, reduces subjective bias, and produces stable employee rankings even in the presence of data variations or conflicting criteria. The Employee Ranking results show that the top-performing employee is Lestari with a score of 1.3092, followed by Susilo with a score of 1.3080 and Maharani with a score of 1.3003, indicating superior and relatively balanced performance. These findings confirm that the combination of WENSLO and MUNRA can produce clear, objective, and effective employee rankings, as well as provide an adaptive framework to support strategic human resource management.
Penerapan Aplikasi FashionFleet Berbasis AI untuk Meningkatkan Omset Penjualan dan Pengelolaan Manajemen Usaha Yusra Fernando; Dedi Darwis; Febrian Eko Saputra
Journal Social Science And Technology For Community Service Vol. 6 No. 2 (2025): Volume 6, Nomor 2, September 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v6i2.863

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kinerja usaha UMKM Toko Baju Starly melalui penerapan aplikasi FashionFleet berbasis Artificial Intelligence (AI). Permasalahan utama mitra meliputi pencatatan transaksi yang masih manual, kesulitan dalam perhitungan harga pokok penjualan (HPP), kurangnya pengelolaan stok, serta strategi pemasaran digital yang belum optimal. Metode yang digunakan dalam kegiatan ini mencakup pendekatan partisipatif, kolaboratif, dan pemberdayaan melalui pelatihan, pendampingan, serta implementasi aplikasi. Hasil evaluasi menunjukkan adanya peningkatan signifikan pada berbagai aspek, antara lain pemahaman penggunaan aplikasi (45% menjadi 85%), manajemen stok (40% menjadi 90%), pencatatan transaksi (50% menjadi 92%), strategi pemasaran digital (35% menjadi 88%), serta pengelolaan keuangan (48% menjadi 90%). Selain itu, omset penjualan juga meningkat sekitar 56% setelah penggunaan aplikasi. Dengan demikian, penerapan FashionFleet terbukti mampu meningkatkan efisiensi operasional, memperluas jangkauan pasar, dan mendukung kemandirian mitra dalam menghadapi tantangan era digital.
Optimizing Employee Admission Selection Using G2M Weighting and MOORA Method Yuri Rahmanto; Junhai Wang; Setiawansyah Setiawansyah; Aditia Yudhistira; Dedi Darwis; Ryan Randy Suryono
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 1 (2025): March 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i1.8224

Abstract

An objective and effective employee admission selection process is a crucial step for the success of the organization in achieving its goals. Problems in employee recruitment selection often arise due to a lack of good planning and system implementation, namely decisions are often influenced by personal preferences, stereotypes, or non-relevant factors, thus reducing objectivity in choosing the best candidates. Objective selection ensures that candidate assessments are conducted based on measurable, relevant, and bias-free criteria, so that only individuals who truly meet the company's needs and standards are accepted. The purpose of developing an optimal approach in employee admission selection using G2M weighting and MOORA is to create a more objective, efficient, and accurate selection process. This approach aims to integrate the calculation of criterion weights mathematically, such as those offered by G2M, in order to eliminate subjective bias in determining criterion prioritization. The MOORA method of evaluating alternative candidates is carried out through ratio analysis that takes into account various criteria simultaneously, resulting in a transparent and data-driven ranking. The results of the employee admission selection ranking based on the criteria that have been evaluated, Candidate 3 obtained the highest score of 0.4177, indicating that this candidate best meets the expected criteria. The second position was occupied by Candidate 6 with a score of 0.3886, followed by Candidate 9 with a score of 0.3528. This research contributes to the recruitment process, by providing a more reliable, transparent, and less subjective way of selecting the right candidates for the positions that companies need.
Co-Authors . Yuniarwati ., Rusliyawati Abhishek R Mehta Abhishek R. Mehta Ade Dwi Putra Ade Surahman Ade Surahman Aditia Yudhistira Agung Saputra Agus Wantoro Agustina, Intan Ahmad Ari Aldino Ahmad Ari Aldino Ahmad Suhendri Aidil Akbar Alita, Debby Andi Ilham Rahmansyah Andre Setiawan An’ars, M. Ghufroni Aprian Nuriansah Ari Sulistiyawati Ari Sulistiyawati Arie Qur’ania Aulia Mustika Sari Ayu Vidiasari Bambang Dwi Setyarto Bayu Dwi Juniansyah Budiawan, Aditia Chaswarina Nimas Maharani Cici Dian Paramita Damayanti, Damayanti Dartono Dartnono Dartono Dartono Dartono Dartono Depriansah Depriansah Dini Wahyuni Ditha Nurjayanti Dwi Andika Dwi Maila Pauristina Dwi Rahma Sari Eka Shintya Pratiwi Elvano Delisa Mega Endi Febrianto Fadila Shely Amalia Fahri Hanif Fatmawati Isnain Febrianto, Endi Fenty ariany Fernando, Yusra Fikri Hamidy Gunawan, Rakhmat Dedi Heni Sulistiani HOTIMAH, NURUL I Gede Heri Susanto Ichtiar Lazuardi Putra Ikbal Yasin Ilham Muhammad Ghoffar Ilham Utama Putra Imam Ahmad Ismail, Izudin Ismail, Izzudin Isnain, Auliya Rahman Jumaryadi, Yuwan Junhai Wang Junhai Wang Kencono, Lintang Khoirunnisa, Yosi Kisworo Kisworo Kisworo KISWORO Lusiana Indawa M Joko Priono Maria Ainun Nazar Marzuki, Dwiki Hafizh Maulana, Nanda Arif Megawaty, Dyah Ayu Mehta, Abhishek R Meylinda Meylinda Mirza Wijaya Putra Muhammad Bakri Muhammad Fauzan Ramadhani Muhammad Khotimul Anwar Nabil Safiq Ramadan Nirwana Hendrastuty Nora Fitaria Nova Evrilia Novi Eka Wati Nugraha Ashari Nurhuda Budi Pamungkas Nurhuda Budi Pamungkas Pasaribu, A. Ferico Octaviansyah Prabowo, Rizky Pramita, Galuh Pramuditya, Andri Prastowo, Agung Tri Pratiwi, Eka Shintya Priandika, Adhie Thyo Prita Dellia Purnomo Aji Putra, Ade Dwi Putri Lestari Rachmad Nugroho Rayin Biilmilah Rika Mersita Riska Aryanti Riskiono, Sampurna Dadi Ryan Randy Suryono Saefulloh Saefulloh Salsa Safhira Sampurna Dadi Riskiono Sanriomi Sintaro Saputra, Febrian Eko Sari, Priskila Lovika Setiawansyah Setiawansyah Sitna Hajar Hadad suaidah suaidah Sumanto Sumanto Surahman, Ade Surya Indra Gunawan Tika Yusiana Tithania Marta Putri Trisnawati, Fika Ummy Permata Hakim Vera Herlinda Very Hendra Very Hendra Saputra Very Hendra Saputra Very Hendra Saputra Wahyudi, Agung Deni Wamiliana Wamiliana Wang, Junhai Waqas Arshad, Muhammad Wayan Kresna Yogi Swara yasin, ikbal Yuri Rahmanto Yusra Fernando Yusri Kusumayuda