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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 48 Documents
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Analisis Pengaruh Kualitas Produk terhadap Keputusan Pembelian Sandal dan Sepatu Wanita dengan Metode COPRAS M. Faisal Afiff Tarigan; Sulystiani Sulystiani; Septia Ona Sutra
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 Pradani Ayu Widya Purnama; Indra Irawan; Nadya Alinda Rahmi; Desi Ardila; Kaila Azahra; Mutiara Sakinah
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

Pemasaran digital merupakan elemen penting dalam strategi bisnis modern, namun efektivitasnya sangat dipengaruhi oleh tren pasar, preferensi pelanggan, dan efisiensi iklan. Penelitian ini bertujuan mengoptimalkan strategi digital marketing di Toko Sumber Perabot dan Elektronik dengan menggunakan Sistem Pendukung Keputusan (SPK) berbasis metode Analytical Hierarchy Process (AHP) dan Evaluation based on Distance from Average Solution (EDAS). Metode AHP digunakan untuk menentukan bobot prioritas tiap kriteria pemasaran, sedangkan EDAS digunakan untuk merangking alternatif strategi berdasarkan jaraknya dari solusi rata-rata. Hasil penelitian menunjukkan bahwa strategi iklan di media sosial berbasis tren pasar memperoleh peringkat tertinggi dengan skor akhir 0,931, menandakan efektivitas yang lebih tinggi dibanding alternatif lainnya. Pendekatan ini membantu toko meningkatkan daya saing dan efisiensi pemasaran digital. Selain itu, metode AHP-EDAS terbukti mengurangi subjektivitas dalam pengambilan keputusan dan memberikan wawasan yang lebih akurat dalam menentukan strategi pemasaran yang optimal.
Sistem Pendukung Keputusan untuk Menetapkan Prioritas Pengembangan Pariwisata Menggunakan Metode TOPSIS-Borda Nurmaliana Pohan; Harlan Kurnia AR; Aulia Alsaf Salsabilla; Deli Kartika Abrianisyah; Dariana Tanjung
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

Pengembangan destinasi pariwisata di Provinsi Sumatera Utara memiliki potensi yang besar, namun masih menghadapi berbagai tantangan seperti keterbatasan infrastruktur dan belum diterapkannya perencanaan berbasis data. Penelitian ini bertujuan untuk mengembangkan Sistem Pendukung Keputusan (SPK) yang mengintegrasikan metode TOPSIS dan Borda guna menentukan prioritas pengembangan pariwisata secara lebih efektif. Metode TOPSIS digunakan untuk mengevaluasi alternatif destinasi berdasarkan kedekatannya dengan solusi ideal, sementara metode Borda memperkuat proses pengambilan keputusan melalui sistem pemeringkatan yang mencerminkan preferensi para pemangku kepentingan. Hasil penelitian menunjukkan bahwa Kampung Ulos Huta Raja, Paropo Silalahi, dan Desa Bakkara merupakan destinasi utama yang direkomendasikan untuk diprioritaskan dalam pengembangan. Integrasi metode TOPSIS dan Borda menghasilkan keputusan yang lebih objektif, konsisten, dan berbasis pada kriteria terukur. Pendekatan ini menawarkan solusi inovatif bagi pengelolaan pariwisata, mendukung transformasi digital, serta membantu pemerintah dan para pemangku kepentingan dalam mengambil keputusan yang lebih strategis dan efektif.
Optimasi Rute Terpendek pada Objek Wisata di Kabupaten Tangerang Menggunakan Algoritma Genetika dengan Pendekatan Travelling Salesman Problem Ramadhani Ramadhani; Ramadhanu Ramadhanu; Fahmi Fiddin
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

Kabupaten Tangerang memiliki banyak destinasi wisata yang tersebar di berbagai lokasi, namun wisatawan sering menghadapi kendala dalam menentukan rute perjalanan yang efisien akibat kepadatan lalu lintas dan jarak antar tempat yang tidak beraturan. Permasalahan ini menyebabkan waktu tempuh yang tidak optimal dan menurunkan kenyamanan selama perjalanan wisata. Penelitian ini bertujuan untuk mengoptimalkan rute perjalanan wisata di Kabupaten Tangerang menggunakan algoritma genetika dengan pendekatan Travelling Salesman Problem (TSP). Data diperoleh dari 17 objek wisata beserta koordinat geografisnya, yang kemudian diproses melalui tahapan algoritma genetika: inisialisasi populasi, seleksi, crossover, dan mutasi. Hasil penelitian menunjukkan bahwa algoritma genetika mampu menghasilkan rute optimal dengan total jarak 109,77 km dan nilai fitness terbaik sebesar 0,009110. Jika dibandingkan dengan jarak awal sebelum optimasi, yaitu 215,80 km, hasil ini menunjukkan peningkatan efisiensi jarak perjalanan sebesar 49,15%. Temuan ini menunjukkan bahwa pendekatan algoritma genetika dapat memberikan solusi yang efisien untuk perencanaan rute wisata. Hasil ini diharapkan dapat menjadi dasar pengembangan strategi promosi pariwisata dan peningkatan infrastruktur di Kabupaten Tangerang.
Penerapan Algoritma Decision Tree dalam Menentukan Kualitas Olahan Kopi Berdasarkan Preferensi Konsumen pada Kopi Beskabean M Arief Rahman
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.
Meningkatkan Administrasi Bisnis Melalui Sistem Pendukung Keputusan: Tinjauan Komprehensif Hewa Majeed Zangana; Azar Abid Salih
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 2 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i2.1138

Abstract

Decision Support Systems (DSS) are critical tools in modern business administration, aiding in data analysis, decision-making, and strategic planning, the evolution of DSS has been driven by advancements in technology, increasing the complexity and volume of data businesses handle, understanding the impact of DSS on business processes and outcomes is essential for leveraging their full potential. To review and synthesize existing research on the impact of Decision Support Systems on business administration, and to identify key benefits, challenges, and best practices associated with the implementation and use of DSS in business settings. Conducted a comprehensive literature review of academic journals, industry reports, and case studies on DSS in business administration, also analyzed data from studies focusing on different aspects of DSS, including implementation strategies, technological advancements, and their effects on decision-making processes. DSS significantly improve decision-making efficiency and accuracy by providing timely and relevant information, successful implementation of DSS is associated with enhanced strategic planning, better resource allocation, and improved overall business performance, common challenges include high implementation costs, complexity of integration with existing systems, and the need for ongoing user training and support. Decision Support Systems play a pivotal role in enhancing business administration by transforming data into actionable insights. Businesses that effectively implement and utilize DSS can achieve competitive advantages through improved decision-making capabilities. Future research should focus on addressing the challenges of DSS implementation and exploring emerging technologies that can further enhance their effectiveness
Sistem Pendukung Keputusan Berbasis AHP untuk Pemilihan Hunian di Kawasan Perkotaan yang Padat Yessy Evita Leony Aruan; Nanda Novita
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 2 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i2.1289

Abstract

Home selection is a critical and complex decision, particularly in densely populated urban areas such as Medan, where multiple factors including location, price, facilities, and environmental risks must be considered simultaneously. This study aims to develop a Decision Support System model based on the Analytical Hierarchy Process (AHP) to assist prospective buyers in making more objective and structured housing decisions. The research evaluated 20 housing alternatives selected through purposive sampling. Assessments of criteria and alternatives were conducted by five respondents, consisting of two property experts, two information systems academics, and one experienced homebuyer, using pairwise comparison questionnaires based on the Saaty scale. The analysis reveals that Location holds the highest weight (0.6333), followed by Income/Property Price (0.2605), and Facilities (0.1062). At the sub-criteria level, Flood-Free Area emerged as the most influential factor with a weight of 0.3533, followed by Property Price (0.1954) and Safe Neighborhood (0.1668). Among the 20 alternatives, Cempaka Lestari ranked first with a score of 0.9040, closely followed by Griya Indah (0.9033) and Anggrek Residence (0.8930). The consistency ratio for all calculations was below 0.10, confirming the reliability and logical validity of the judgments. These findings emphasize that location-specific environmental criteria, particularly flood risk, play a decisive role in homebuyer preferences in Medan. Practically, the proposed model provides prospective buyers with a rational decision-making framework and offers strategic insights for developers to align housing products with market demands in flood-prone urban areas.
Sistem Pendukung Keputusan untuk Memilih Program Kesehatan Sekolah Menggunakan COPRAS M. Ari Prayogo; Muhammad Labib Jundillah; Febri Ramanda; Muhammad Shodiq; Riendy Riendy
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 2 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i2.1304

Abstract

The School Health Program is a strategic initiative aimed at improving students’ health within the educational environment. However, selecting the most appropriate program often requires consideration of multiple complex criteria. This study develops a Decision Support System (DSS) using the COmplex PRoportional ASsessment (COPRAS) method to assist schools in determining the best health program. The alternative programs analyzed include Reproductive Health, Healthy School Cleanliness Competition, Smoke-Free School Area, Prevention of Drug Abuse (NAPZA), and Disease Control. The evaluation was conducted based on six main criteria: Implementation Cost, Student Participation, Program Effectiveness, Long-Term Health Impact, Relevance to School Needs, and Ease of Implementation. The results indicate that the third alternative (A3), namely the Smoke-Free School Area, is the most suitable school health program, achieving a utility value (Ui) of 100% among the five alternatives considered. This system is expected to make the decision-making process more objective, efficient, and supportive of fostering a healthier, more productive, and sustainable school environment.
Integrasi Artificial Intelligence dalam Sistem Manajemen Pendidikan Islam untuk Meningkatkan Efisiensi Administrasi Rahmadanni Pohan; Nurmaliana Pohan
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 2 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i2.1305

Abstract

Islamic educational institutions such as madrasas often experience delays and data errors in grade processing and report preparation because administrative processes are still carried out manually. This study aims to automate grade recaps and academic report generation by applying artificial intelligence (AI) to improve the efficiency and accuracy of educational management. The methods used include needs analysis in one Islamic high school (MA), AI-based system design, and implementation of a machine learning module for grade analysis. This trial was conducted in one Madrasah Aliyah (MA) with 150 student grade records collected between July and December 2024 and 20 teaching and education staff. The test results showed that the average grade recap time was reduced from approximately 2–3 days to only 8–10 minutes (≈97%), academic report generation from 3–5 days to 1–2 hours, and the input error rate decreased by more than 90%. A total of 85% of teaching and administrative staff stated that the system was very helpful in their work. These findings confirm that AI integration significantly improves the efficiency, accuracy, and transparency of Islamic educational administration while making an important contribution to the madrasah digitalization agenda. This research is expected to make a tangible contribution to the digitalization of Islamic education through the use of AI technology. Although the prototype was demonstrated at a single institution, its modular architecture illustrates a novel adaptation of AI in Islamic educational administration.
Hybrid Decision Support Framework with Explainable AI and Multi-Criteria Optimization Hewa Majeed Zangana; Noor Salah Hassan; Marwan Omar; Jamal N. Al-Karaki
Sistem Pendukung Keputusan dengan Aplikasi Vol 4 No 2 (2025)
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/spk.v4i2.1328

Abstract

Decision-making in domains such as healthcare, finance, and smart systems demands frameworks that combine model-driven expertise with data-driven adaptability. This paper proposes a hybrid decision support framework that integrates Explainable AI (XAI) with multi-criteria optimization to enhance transparency, robustness, and adaptability. Unlike traditional systems, our approach unifies mechanistic models with machine learning and embeds interpretability and optimization mechanisms. Comparative evaluation against state-of-the-art methods shows consistent performance gains, achieving 15–25% lower error rates compared with data-driven baselines and generating more diverse Pareto-optimal solutions. These improvements highlight the framework’s potential as a reliable, explainable, and scalable solution for complex, real-world decision-making

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