Article Per Year (5 Year)
p-Index From 2021 - 2026
2.189
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Robotics and Control (JRC) Jurnal Inovasi dan Teknologi Pembelajaran (JINOTEP) Kajian dan Riset Dalam Teknologi Pembelajaran Indonesian Journal of Computing, Engineering, and Design Jurnal Teknik Informatika (JUTIF) SinarFe7 Asian Journal Science and Engineering Evrimata: Journal of Mechanical Engineering
Pebrianti, Dwi
Unknown Affiliation
Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Pemilihan Skill Terbaik Menggunakan TOPSIS Berbasis OWA Untuk Game Nugroho, Fresy; Zidan, Muhammad; Lestari, Tri Mukti; Pebrianti, Dwi
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perkembangan game modern, khususnya pada genre Role Playing Game (RPG), menghadirkan tantangan baru bagi pemain dalam menentukan strategi yang efektif melalui pemilihan skill. Banyaknya pilihan skill dengan karakteristik beragam, ditambah dengan dinamika situasi pertempuran, sering kali menyulitkan pemain dalam memilih strategi yang paling optimal. Untuk mengatasi permasalahan tersebut, penelitian ini mengusulkan sistem rekomendasi skill pada game Pedjoeang dengan mengintegrasikan metode Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) dan Ordered Weighted Averaging (OWA). Integrasi ini memanfaatkan keunggulan TOPSIS dalam menghitung kedekatan relatif terhadap solusi ideal, sekaligus fleksibilitas OWA dalam mendistribusikan bobot kriteria secara lebih adaptif. Sistem ini mengevaluasi enam alternatif skill terhadap enam kriteria, dengan bobot kriteria ditentukan melalui perhitungan OWA. Hasil pengujian menunjukkan bahwa Skill 5 memperoleh nilai closeness coefficient tertinggi (0,4846) dan menempati peringkat pertama, sedangkan Skill 4 mendapatkan nilai terendah (0,4538) dan berada pada peringkat terakhir. Selain itu, perbandingan antara TOPSIS konvensional dengan metode TOPSIS–OWA menunjukkan adanya perbedaan peringkat, khususnya pada Skill 3 dan Skill 4, yang membuktikan bahwa penerapan OWA meningkatkan sensitivitas sistem terhadap kriteria tertentu. Kontribusi utama penelitian ini adalah membuktikan efektivitas integrasi OWA pada metode TOPSIS dalam sistem rekomendasi berbasis game, yang mampu menghasilkan rekomendasi lebih adaptif dan kontekstual. Temuan ini memperkaya literatur mengenai pengambilan keputusan multikriteria di lingkungan interaktif serta membuka peluang penerapan pada genre game lain dengan kompleksitas lebih tinggi. Lebih jauh, pendekatan ini dapat meningkatkan pengalaman pemain melalui rekomendasi skill yang lebih cerdas, sehingga mendukung pengambilan keputusan strategis dalam gameplay yang dinamis.
Using Content-Based Filtering and Apriori for Recommendation Systems in a Smart Shopping System Pebrianti, Dwi; Ahmad, Denis; Bayuaji, Luhur; Wijayanti, Linda; Mulyadi, Melisa
Indonesian Journal of Computing, Engineering, and Design (IJoCED) Vol. 6 No. 1 (2024): IJoCED
Publisher : Faculty of Engineering and Technology, Sampoerna University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35806/ijoced.v6i1.393

Abstract

This research is motivated by the increasing significance of online shopping platforms and the challenges faced by users in locating products that align with their preferences and requirements, which can significantly influence the sales performance of online retailers. Consequently, the primary objective of this study is to design and implement a recommendation system capable of identifying suitable products and forecasting the purchase frequency for various product combinations, while also integrating this recommendation system with a smart shopping platform. To achieve this objective, the research employs machine learning techniques, specifically content-based filtering and the Apriori algorithm. Content-based filtering is utilized to analyze user preferences and behavioral patterns related to visited products, while the Apriori algorithm is employed to evaluate support and confidence values for item set combinations, thereby generating frequency values for future transactions involving product combinations. Additionally, a smart shopping system is developed and integrated, enhancing the shopping experience through smartphone applications and streamlining the payment process to facilitate seamless product purchases. The research methodology involves data collection pertaining to products and user preferences, followed by several testing involving a sample group of user respondents. The results demonstrate that the developed recommendation system effectively delivers relevant product recommendations based on user preferences, achieving a confidence value up to 98%. Furthermore, the smart shopping system proves capable of independently assisting users throughout the transaction process, thereby enhancing overall user experience and convenience.
The Effect of Pin Length and Compressive Force in Double Side Friction Stir Welding on Bending Strength of AA1100 Sukma Satriawan; Setiawan, Agus; Pebrianti, Dwi; Binti MD. Zain, Zainah
Evrimata: Journal of Mechanical Engineering Vol. 01 No. 01, 2024
Publisher : PT. ELSHAD TECHNOLOGY INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70822/evrmata.vi.16

Abstract

Many new welding methods have emerged to improve connection results, including friction stir welding (FSW). FSW is a welding method that is widely used in welding aluminium alloys. FSW method on AA1100 aluminium material has not yet obtained the maximum bending strength so it is necessary to study the improvement of the quality of FSW joints using the welding method on both sides or double side friction stir welding (DFSW). This study aims to determine the effect of pin length and downward force on double side friction stir welding (DFSW) on the bending strength of AA1100 aluminium . The independent variables of this study are pin length (1.5 mm, 2 mm, 2.5 mm) and downward force (30 kg, 35 kg, 40 kg, 45 kg). The controlled variables are shoulder diameter of 25 mm, machine table translational speed of 10 mm/min, spindle rotation speed of 1750 rpm, base plate temperature of 250ºC, and AA1100 plate thickness of 3.6 mm with butt joint type welding connection model. The method used in this research is experimental using the factorial design of experiment (DOE) data analysis method. The results of this study indicate that pin length and downward force have a significant effect on the bending strength of DFSW welded joints on AA1100. The maximum bending strength value of the welded joint was 289.59 MPa at a pin length variation of 2 mm and a compressive force of 35 kg. The percentage of weld defects including tunnel and flash in welded joints with maximum bending strength is identified as the least and the micro test results also show the least FeAl3 particle grains.
Effect of Coconut Shell-Based Active Carbon Adsorbent on Motorcycle Exhaust Gas Emissions Putra Gitama, Nahindi; Hidayat, Najmul; Pebrianti, Dwi
Evrimata: Journal of Mechanical Engineering Vol. 01 No. 03, 2024
Publisher : PT. ELSHAD TECHNOLOGY INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70822/evrmata.v1i03.57

Abstract

This study focused on the utilization of active carbon derived from coconut shells as an adsorbent to reduce exhaust gas emissions in motorcycles. The research aimed to compare the exhaust emissions before and after installing active carbon in the muffler and to analyze its effect on the levels of CO, HC, and CO2 at different engine speeds. A laboratory experiment was conducted with varying masses of active carbon, and emission data were collected and analyzed using two-way ANOVA. The results demonstrated that with the use of 200 grams of active carbon, the CO emission decreased by 12.06%, HC by 16.96%, and CO2 by 9.17%. These reductions are attributed to the strong adsorptive properties of active carbon, which facilitated the physical and chemical separation of harmful gases. The study concluded that active carbon significantly reduces exhaust emissions, providing a practical solution for improving air quality in motorcycles. The findings offer an effective method for emission control that could be applied under various operating conditions, making it suitable for widespread implementation in emission-reduction systems for small engines.
Co-Authors Addie Irawan Agus Setiawan Ahmad, Denis Andalas Saputra, Meitro Hartanto Azahar, Mohd Iskandar Putra binti MD. Zain, Zainah Dian Maharani, Dian Fachri, Moch Fadhil Abas, Mohammad Faizal, Elka Fresy Nugroho Hadi Susilo, Sugeng Hammad, Jehad A.H. Hammad, Jehad AH Haris Kurniawan, Haris Herwan Sulaiman, Mohd Hidayat, Najmul Huda, Arif Nur I Gusti Putu Asto Buditjahjanto Lestari, Tri Mukti Luhur Bayuaji, Luhur Melisa Mulyadi Mohd Saad, Norhafidzah Muhammad Ridho Nurrahma ‘N, Alfina Nurrahma, Alfina Prakasa, Aji Bagas Pratama, Maulana Krisna Bayu Putra Gitama, Nahindi Roro Inda Melani Rusdah Rusdah Rusdah Sharif Zakaria, Mohd Sukma Satriawan Tri Ika Jaya Kusumawati Wijayanti, Linda Yulia Puspita Dewi Zidan, Muhammad