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All Journal Systemic: Information System and Informatics Journal Indonesian Journal of Business Intelligence (IJUBI) Jurnal Pengabdian Masyarakat dan aplikasi Teknologi Global Science: Journal of Information Technology and Computer Science
Yanuar Wicaksono
Universitas Alma Ata
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Other

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Pemetaan Strategi Promosi Penerimaan Mahasiswa Baru Menggunakan K-Means Yanuar Wicaksono; Ujang Nendra Pratama; Siti Nurhasanah; Tri Utari Ramadania; Wulandari Juslan
Systemic: Information System and Informatics Journal Vol. 7 No. 1 (2021): Agustus
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29080/systemic.v7i1.1268

Abstract

Universities need to have a special strategy to capture the target prospective students. The variety of promotional media needs to be analyzed so that the media distribution is right on target. The number of new student admissions in each year of a college is influenced by the promotional actions that have been carried out. Data mining is a method for finding useful new information from a large amount of data collection and can help in making decisions. The analysis of promotion strategies grouped with the K-means algorithm is expected to be used by the promotion team in determining promotion strategies to get new prospective students in accordance with the promotion target. Promotional media that can be accessed in all provinces are the internet and leaflets/posters. For close-range media in promoting higher education, benefits can still be taken such as school visits, educational exhibitions, newspapers, billboards/banners. However, for provinces outside Yogyakarta, there are promotion strategies that can be relied upon, namely student recommendations and alumni recommendations
SEGMENTASI PELANGGAN BISNIS DENGAN MULTI KRITERIA MENGGUNAKAN K-MEANS Yanuar Wicaksono
Indonesian Journal of Business Intelligence (IJUBI) Vol 1, No 2 (2018): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Program Studi S1 Sistem Informasi Fakultas Komputer dan Teknik Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (270.089 KB) | DOI: 10.21927/ijubi.v1i2.872

Abstract

Customer knowledge is an important asset, in gathering, and managing from sharing customer knowledge into valuable capital for the company. This causes the company to continue to innovate in producing products and serving according to customer needs. To find out the needs of each customer, the company needs to make customer segmentation. Customer segmentation is defined as the division into different groups with similar characteristics to develop marketing strategies that are tailored to customer characteristics. The easiest, simplest, well-known and commonly used model of customer characteristics is the model of the recency, frequency, monetary (RFM) criteria. The RFM model still has weaknesses in low customer segmentation capacity and does not provide information on the continuity of customer transactions in understanding customer loyalty. The research method used is the Knowledge Discovery in Database (KDD) method. The data is transformed into another format that suits the needs of analysis and then the customer is segmented using clustering data mining techniques with the K-Means algorithm. From the experiments, the RFM model guesses loyal customers when reviews, frequency and monetary are high. In reality, the recency only provides information on the customer making the last transaction and the high number of transaction frequencies can be done without the customer's stability in making transactions each period. Implementing multi-criteria in customer segmentation can be better than just RFM criteria. So it will not be wrong to treat customers according to the groups that have been formed.
Sosialisasi dan Pendampingan Pembuatan NIB pada Pelaku UMKM Pasar Kebon Empring Yanuar Wicaksono; Raden Nur Rachman Dzakiyullah; Tri Rochmadi; Mukhammad Izzat Azizi Muzaki
Jurnal Pengabdian Masyarakat dan aplikasi Teknologi (Adipati) Vol 2, No 2 (2023)
Publisher : Institut Teknologi Adhi Tama Surabaya

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Abstract

Terdapat 274 destinasi wisata di Daerah Istimewa Yogyakarta (DIY) yang terdaftar di dinas pariwisata DIY pada tahun 2021. Sektor pariwisata sangat mempengaruhi pendapatan domestik regonal bruto (PDRB) DIY yang dapat menunjang pertumbuhan perekomomian masyarakat. Pariwisata juga merupakan industri yang dapat meningkatkan kesejahteraan masyarakat, salah satu contohnya menumbuhkan usaha mikro kecil menengah (UMKM) yang berada di sekitar daerah destinasi wisata. UMKM sangat perlu mendapat perlindungan dalam menghadapi persaingan pasar bebas. Legalitas bisa digunakan UMKM untuk mempermudah dalam hal akses permodalan melalui pemberian kredit. Adanya legalitas resmi yang dikeluarkan oleh pemerintah menjadikan UMKM dalam menjalankan usaha agar dapat berjalan dengan baik dikarenakan memiliki legalitas yang jelas. Namun sebagian besar pelaku UMKM Pasar Kebon Empring enggan mengurus legalitas usahanya karena keterbatasan pengetahuan dan informasi. Masih banyak pelaku UMKM Pasar Kebon Empring yang berpandangan pengurusan legalitas usaha sangat rumit dan membutuhkan biaya yang besar. Pendekatan pengabdian kepada masyarakat (PKM) dengan participatory action research (PAR) merupakan pendekatan yang prosesnya bertujuan untuk pembelajaran dalam mengatasi masalah dan pemenuhan kebutuhan praktis masyarakat. Peningkatan pelaku UMKM Pasar Kebon Empring memiliki NIB sebesar 39,43% dari kepemilikan NIB 10,71% menjadi 50,14%. Untuk pelaku UMKM Pasar Kebon Empring yang belum memliki NIB sebesar 49,86% dikarenakan kesulitan pengoperasian online single submission (OSS) Indonesia dalam pendampingan pembuatan NIB.
Energy Aware Software Architecture Optimization Using Real Time Analytics and Self Adaptive Control in Intelligent Computing Systems Ardy Wicaksono; Mursalim Mursalim; Arif Tri Widiyatmoko; Deny Prasetyo; Ahmad Budi Trisnawan; Yanuar Wicaksono
Global Science: Journal of Information Technology and Computer Science Vol. 1 No. 4 (2025): December: Global Science: Journal of Information Technology and Computer Scienc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/globalscience.v1i4.195

Abstract

The increasing demand for intelligent computing systems, including cloud computing, artificial intelligence (AI), and the Internet of Things (IoT), has resulted in a significant rise in energy consumption, which poses both environmental and economic challenges. The high computational power required by these systems, coupled with the continuous operation of data centers and connected devices, has led to inefficiencies in energy usage. This paper explores the integration of real time analytics and self adaptive control mechanisms to optimize energy consumption in intelligent systems. By employing advanced software tools for real time monitoring, dynamic adjustments based on workload conditions, and adaptive algorithms for energy optimization, significant reductions in power usage were achieved without compromising system performance. The optimized architecture dynamically adjusts system parameters such as processor frequency, task scheduling, and voltage to ensure efficient energy consumption during varying operational demands. The results show a 24% reduction in energy usage during low demand periods, demonstrating the potential of real time energy management strategies. The study also compares the optimized architecture with conventional static systems, highlighting the benefits of dynamic energy management, including improved performance balance, reduced environmental impact, and lower operational costs. These findings suggest that the integration of energy efficient practices in software design, particularly through real time analytics and self adaptive mechanisms, offers a sustainable solution for modern computing systems. Future research could focus on improving self adaptive systems, incorporating renewable energy sources, and expanding the approach to other intelligent systems, such as autonomous vehicles or large scale smart grids. The practical applications of this research are vast, particularly in large scale applications such as data centers and cloud computing, where energy efficiency is critical for sustainability.
Co-Authors Ahmad Budi Trisnawan Ardy Wicaksono Arif Tri Widiyatmoko Deny Prasetyo Mukhammad Izzat Azizi Muzaki Mursalim Mursalim Raden Nur Rachman Dzakiyullah Siti Nurhasanah Tri Rochmadi Tri Utari Ramadania Ujang Nendra Pratama Wulandari Juslan