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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 6 Documents
 1 
Search results for , issue "Vol 4 No 2 (2025)" : 6 Documents clear
Meningkatkan Administrasi Bisnis Melalui Sistem Pendukung Keputusan: Tinjauan Komprehensif Zangana, Hewa Majeed; Salih, Azar Abid
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 Aruan, Yessy Evita Leony; Novita, Nanda
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 Prayogo, M. Ari; Jundillah, Muhammad Labib; Ramanda, Febri; Shodiq, Muhammad; 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 Pohan, Rahmadanni; Pohan, Nurmaliana
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 Zangana, Hewa Majeed; Hassan, Noor Salah; Omar, Marwan; Al-Karaki, Jamal N.
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
Prediksi Gap-Up Saham Berbasis Logistic Regression Menggunakan Indikator Teknikal Anisa, Yuan; Hafiz, Muhammad; Hadijah, Hadijah; Gani, Abdul
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.v4i2.1334

Abstract

This research aims to construct and test a predictive model for the gap-up phenomenon in stocks on the Indonesia Stock Exchange (IDX), with a case study on PT Bank Mandiri Tbk. (BMRI) stock. The research uses a quantitative approach by applying a Binary Logistic Regression model to analyze 1,213 daily historical data points from January 1, 2019, to January 1, 2024.Five technical analysis-based independent variables—vol_spike, rsi, prev_return, macd, and stochastic—were used to predict the probability of a stock gap-up occurrence.The analysis results show that the model as a whole is statistically significant (LLR p-value < 0.05), with an LLR p-value of (8.544e-11) and a Pseudo R-squared of 0.03389. Of the five variables, stochastic, macd, and prev_return were identified as significant predictors. Specifically, a high Stochastic Oscillator value has a strong positive influence on the probability of a gap-up. On the other hand, Moving Average Convergence Divergence (MACD) and Previous Return show a significant negative influence.These findings provide empirical evidence that a combination of technical indicators can be used to model and predict stock price movements at market opening. The implications of this research offer valuable insight for investors who rely on technical analysis as a basis for decision-making.

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