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All Journal Jurnal Ilmiah KOMPUTASI Jurnal Mandiri IT Jurnal ICT : Information and Communication Technologies
Muhammad Azhar Prabukusumo
Universitas Budi Luhur
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Library & Information Science Mathematics Mechanical Engineering

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Pemodelan Pola Belanja Pelanggan Produk Infrastruktur dan Security menggunakan Algoritma FP-Growth: Array Muhammad Azhar Prabukusumo; Nurdin Sidik
Jurnal Ilmiah Komputasi Vol. 21 No. 3 (2022): Jurnal Ilmiah Komputasi : Vol. 21 No 3, September 2022
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.21.3.3021

Abstract

Data transaksi pembelian produk infrastruktur dan security yang diperoleh dari departe- men produk dan sales selama ini hanya menjadi data arsip belaka. Untuk mengoptimalkan penggunaan data transaksi ini, maka dibutuhkan model pola belanja agar menghasilkan infor- masi yang bermanfaat dan dapat meningkatkan penjualan. Tujuan penelitian ini adalah untuk menghasilkan list produk dengan kombinasi item barang yang paling laku, sehingga sales bisa memaksimalkan penjualan dari hasil pemodelan yang dibuat. Metode penelitian menggu- nakan salah satu teknik data mining yang membantu mengidentifikasi dan memprediksi per- ilaku pembelian pelanggan berdasarkan pola pembelian semua pelanggan sebelumnya yang dikenal dengan Market Basket Analysis atau association rule. Data yang diambil yaitu data purchase order tahun 2016 dan 2019 dan algoritma FP- Growth dipilih dalam penelitian ini untuk menentukan himpunan data yang paling sering muncul (frequent itemset ) dalam data. Input dari algoritma ini berupa nilai minimum support dan confidence dan output nya berupa aturan asosiasi. Setelah itu algoritma fp-growth dibandingkan dengan algoritma apriori untuk memastikan kebenaran dari aturan asosiasi dari masing-masing algoritma. Hasil dari pemod- elan ini yaitu aturan asosiasi dari kombinasi itemset dengan jumlah minimum support sebesar 5% dan minimum confidence sebesar 50% menghasilkan 2 pola (rules) terbaik yaitu satu at- uran asosiasi dengan kombinasi produk item Fortinet, Cisco dengan nilai support 12,025% nilai confidence 52,778% dan nilai lift ratio 1,14 dan yang kedua aturan asosiasi dengan kom- binasi Rack, APC dengan nilai support 7,594% nilai confidence 57,143% dan nilai lift ratio 1,53 yang artinya kedua aturan asosiasi mempunyai lift ratio>1, valid dan benar dibeli se- cara bersamaan. Hasil pengujian metode blackbox testing dengan pendekatan metode McCall menyatakan bahwa sistem sesuai dan dapat memenuhi kebutuhan user dengan nilai sebesar 77,6 % (Baik)
Decision Support System for Determining Marketing Strategy Using SWOT and AHP Methods Prabukusumo, M. Azhar
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 1 (2024): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i1.162

Abstract

In the competitive global business era, determining an effective marketing strategy is crucial for companies. This research integrates SWOT (Strengths, Weaknesses, Opportunities, Threats) and Analytic Hierarchy Process (AHP) methods to develop a decision support system in this context. The objective is to identify internal and external factors that affect the performance of manufacturing and service companies, and rank strategic priorities based on the relative weight of each SWOT factor using AHP. By analyzing case studies of several companies in the manufacturing and service industries, the results show that advanced production infrastructure and efficient supply chain management dominate as major internal strengths, while raw material price fluctuations and market competition as significant external threats. The implication is that international expansion strategies and improvements in digital service capacity are key in responding to current global market dynamics. This research not only provides new strategic insights for practitioners, but also provides a theoretical foundation for the development of more advanced analytical methodologies in corporate strategic analysis.
Use of Geographic Information System (GIS) in Decision Support System for Optimal Location Selection for Opening Ayam Geprek Branch Offices Prabukusumo, M. Azhar
Jurnal ICT : Information and Communication Technologies Vol. 15 No. 1 (2024): April, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jict.v15i1.163

Abstract

Determining the optimal location for opening Ayam Geprek branch offices in Medan City faces complex challenges as it must consider various demographic and economic factors. This research aims to develop a decision support system using Geographic Information System (GIS) that is effective in identifying strategic locations for business expansion. The research method involved analyzing data on population density, accessibility, and culinary competition, which were then integrated in the GIS to generate a map of optimal locations. The results of the analysis showed that the GIS was able to identify several potential locations that met strategic and economic criteria, and had a positive impact on local economic development. The implications of this research show that the use of GIS not only facilitates the business decision-making process, but also contributes to the sustainability and inclusiveness of economic development in the area
Energy consumption prediction and optimization for Ki Hajar Dewantara student dormitory Using Extreme Gradient Boosting (XGBoost) algorithm Sinaga, Jeremia; Manurung, Jonson; Prabukusumo, M. Azhar
Jurnal Mandiri IT Vol. 14 No. 3 (2026): Jan: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i3.482

Abstract

Energy consumption optimization in student dormitories requires accurate prediction and strategic intervention strategies. This study presents a comprehensive prediction and optimization system for energy usage at Ki Hajar Dewantara Student Dormitory, Indonesia Defense University, utilizing Extreme Gradient Boosting (XGBoost) algorithm integrated with temporal operational scheduling features a novel approach for institutional dormitory energy forecasting. The system analyzes over 3,900 electrical devices across three dormitory buildings, incorporating temporal features and operational schedules to predict hourly energy consumption. The XGBoost model demonstrates excellent prediction performance with R² = 0.9482 and MAPE = 10.24%, significantly exceeding established benchmarks for building energy forecasting. Feature importance analysis reveals working hours as the dominant factor (>85%) influencing consumption patterns, followed by occupancy rate and temperature. The analysis identifies air conditioning systems as the primary energy consumer, accounting for over 80% of total consumption. The optimization framework identifies potential energy savings of approximately 28% through strategic device replacement and schedule modifications, translating to annual cost savings of over Rp 600 million with economically viable return on investment periods. This machine learning-based approach demonstrates practical applicability for student dormitory energy management and provides a replicable methodology adaptable to diverse residential institutional buildings in tropical climates.
Decision-making model for cadet selection using the AHP TOPSIS method Tsany, Tazky; Manurung, Jonson; Prabukusumo, M. Azhar
Jurnal Mandiri IT Vol. 14 No. 3 (2026): Jan: Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i3.486

Abstract

Cadet selection in defense institutions requires a comprehensive assessment process because it must cover the academic, psychological, health, physical, and ideological integrity aspects of prospective participants. This multidimensional complexity poses challenges in producing decisions that are objective, consistent, and free from assessor bias. Therefore, a quantitative approach-based evaluation model is needed that can integrate all assessment components in a measurable manner. This study developed a cadet selection decision-making model using a combination of the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. AHP is used to determine the weight of importance of the seven main criteria: Academic Potential Test, Academic Interview, Psychological Test, Ideological Mental Test, Ideological Mental Interview, Health Test, and Physical Test, while TOPSIS is used to determine the ranking of candidates based on their proximity to the ideal profile of a cadet. The results of the study show that the integration of AHP–TOPSIS is able to provide evaluation results that are more objective, transparent, and accountable than conventional assessments. In addition to formulating a selection model, this study also discusses alternative methods in multi-criteria decision making as material for developing a selection system in the future. Overall, this model is expected to become a scientific basis for defense institutions in improving the quality and accuracy of the cadet selection process.
Co-Authors Manurung, Jonson Nurdin Sidik Sinaga, Jeremia Tsany, Tazky