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Sistem Pendukung Keputusan dengan Aplikasi
Published by Ali Institute of Research and Publication
ISSN : 28292820     EISSN : 28292189     DOI : https://doi.org/10.55537/spk
Core Subject : Science,
Decision Sciences, Operations Research & Management
Artikel yang diterbitkan dalam Sistem Pendukung Keputusan dengan Aplikasi adalah relevansinya dengan masalah teoretis dan teknis dalam mendukung pengambilan keputusan yang ditingkatkan. Naskah dapat diambil dari beragam metode dan metodologi, termasuk dari teori keputusan yang didukung komputer.
Arjuna Subject : Ilmu Pengambilan Keputusan (semua kategori) - Ilmu Pengambilan Keputusan (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 4 No 1 (2025)" : 5 Documents clear
Analisis Pengaruh Kualitas Produk terhadap Keputusan Pembelian Sandal dan Sepatu Wanita dengan Metode COPRAS Tarigan , M. Faisal Afiff; Sulystiani, Sulystiani; Sutra, Septia Ona
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 1 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i1.895

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh kualitas produk terhadap keputusan pembelian sandal dan sepatu wanita menggunakan metode COPRAS. Kualitas produk didefinisikan sebagai kapasitas produk untuk memenuhi fungsi, yang mencakup aspek daya tahan, kemudahan servis, estetika, dan kualitas yang dirasakan. Data dikumpulkan melalui observasi dan wawancara dengan pemilik usaha, kemudian dianalisis dengan COPRAS untuk mengidentifikasi alternatif dengan nilai tertinggi. Hasil penelitian menunjukkan bahwa produk dengan kualitas bahan unggul, kenyamanan tinggi, dan model produk lengkap memperoleh nilai tertinggi, yang mengindikasikan bahwa peningkatan kualitas produk secara signifikan dapat meningkatkan minat pembelian. Temuan ini memberikan kontribusi praktis bagi perusahaan dalam meningkatkan strategi pemasaran dan pengembangan produk.
Penerapan Sistem Pendukung Keputusan untuk Strategi Digital Marketing Menggunakan AHP dan EDAS Purnama, Pradani Ayu Widya; Irawan, Indra; Rahmi, Nadya Alinda; Ardila, Desi; Azahra, Kaila; Sakinah, Mutiara
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 1 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i1.1098

Abstract

Digital marketing is a crucial element in modern business strategies, yet its effectiveness is often influenced by various factors such as market trends, customer preferences, and advertising efficiency. This study aims to optimize the digital marketing strategy at Toko Sumber Perabot dan Elektronik using a Decision Support System (DSS) based on the Analytical Hierarchy Process (AHP) and Evaluation based on Distance from Average Solution (EDAS) methods. The AHP method is used to determine the priority weight of each marketing criterion, while the EDAS method ranks alternative strategies based on their distance from the average solution. The study results indicate that the social media advertising based on market trends strategy achieved the highest ranking with a final score of 0.931, demonstrating greater effectiveness compared to other alternatives. This approach enables the store to enhance its competitiveness and digital marketing efficiency. Additionally, the AHP-EDAS method proves to reduce subjectivity in decision-making and provides more accurate insights for determining the optimal marketing strategy.
Sistem Pendukung Keputusan untuk Menetapkan Prioritas Pengembangan Pariwisata Menggunakan Metode TOPSIS-Borda Pohan, Nurmaliana; AR, Harlan Kurnia; Salsabilla, Aulia Alsaf; Abrianisyah, Deli Kartika; Tanjung, Dariana
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 1 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i1.1099

Abstract

The development of tourist destinations in North Sumatra Province holds significant potential but is hindered by challenges such as limited infrastructure and the absence of data-driven planning. This study aims to develop a Decision Support System (DSS) that integrates the TOPSIS and Borda methods to more effectively determine tourism development priorities. The TOPSIS method is employed to evaluate destination alternatives based on their closeness to the ideal solution, while the Borda method enhances the decision-making process through a ranking system that reflects stakeholder preferences. The results identify Kampung Ulos Huta Raja, Paropo Silalahi, and Desa Bakkara as the top destinations recommended for priority development. The integration of TOPSIS and Borda produces decisions that are more objective, consistent, and based on measurable criteria. This approach provides an innovative solution for tourism management, supports digital transformation, and enables governments and stakeholders to make more strategic and effective decisions.
Optimasi Rute Terpendek pada Objek Wisata di Kabupaten Tangerang Menggunakan Algoritma Genetika dengan Pendekatan Travelling Salesman Problem Ramadhani, Ramadhani; Ramadhanu, Ramadhanu; Fiddin, Fahmi
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 1 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i1.1125

Abstract

Tangerang Regency has numerous tourist destinations spread across various locations. However, tourists often face difficulties in determining an efficient travel route due to traffic congestion and irregular distances between sites. This issue leads to suboptimal travel time and reduces the overall comfort of the tourism experience. This study aims to optimize tourism travel routes in Tangerang Regency using a genetic algorithm approach based on the Travelling Salesman Problem (TSP). Data were collected from 17 tourist attractions, including their geographical coordinates, and processed through several genetic algorithm stages: population initialization, selection, crossover, and mutation. The results show that the genetic algorithm successfully produced an optimal route with a total distance of 109.77 km and the best fitness value of 0.009110. Compared to the initial distance before optimization, which was 215.80 km, this result indicates a travel distance efficiency improvement of 49.15%. These findings suggest that the genetic algorithm approach provides an effective solution for tourism route planning. The results are expected to serve as a basis for developing tourism promotion strategies and improving infrastructure in Tangerang Regency.
Penerapan Algoritma Decision Tree dalam Menentukan Kualitas Olahan Kopi Berdasarkan Preferensi Konsumen pada Kopi Beskabean Rahman, M Arief
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 1 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i1.1129

Abstract

This research aims to apply the Decision Tree algorithm in determining the quality of processed Beskabean coffee based on consumer preferences. Beskabean coffee is one of the local coffee products that is unique in its flavor, processing method, and brewing variety. In the face of market competition and rising consumer expectations, a deep understanding of the factors that influence preferences is essential to support product innovation. Data collection was conducted through distributing questionnaires to consumers who have tasted various variants of Beskabean coffee. The variables analyzed included acidity, viscosity, aroma, aftertaste, and brewing methods such as V60, French press, and tubruk. All data collected was then analyzed using the Decision Tree algorithm with the Classification and Regression Tree (CART) approach. The results of the analysis show that aroma and aftertaste are the two most dominant factors influencing consumer preferences for Beskabean coffee. The Decision Tree model successfully categorizes coffee quality based on a combination of sensory attributes and consumer preferences with a fairly high level of accuracy. These findings provide valuable insights for coffee businesses, especially MSMEs, to develop products that are more in line with market desires. The application of the Decision Tree algorithm is proven to be effective in identifying consumer decision patterns and can be used as a decision-making system.

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