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Strategic alignment maturity assessment on conventional bank’s information technology Nia Budi Puspitasari; Singgih Saptadi; Aditya Dwi Rahmadi
Journal of Engineering and Applied Technology Vol 3, No 2 (2022): (August)
Publisher : Faculty of Engineering, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jeatech.v3i2.48859

Abstract

Strategic alignment between information technology and business strategy is needed to achieve an organization's performance excellence. Bank X is a bank that focused on serving the micro, small and medium enterprise (MSME) market segments. Bank X provided a variety of banking services which are generally grouped into activities of raising and distributing funds. Banking services are carried out conventionally. At the end of 2019, Bank X was acquired by an investment holding company. The objective of the acquisition is to develop Bank X into a bank with a digital platform. This study aims to measure the maturity level of strategic alignment of information technology with business strategies at Bank X. A conceptual framework is developed based on relevant literature. The level of strategic alignment is measured based on Luftman's Strategic Alignment Maturity Model (SAMM) framework. The results of the analysis show that the strategic alignment maturity level of Bank X is at level 3. Several recommendations are given to improve the maturity level of Bank X's strategic alignment.
Solar power plant on the rooftop of the Diponegoro University Rectorate: a technical and economic study Jaka Windarta; Asep Yoyo Wardaya; Singgih Saptadi
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.3497

Abstract

Diponegoro University's Rectorate building uses electricity from the National Electricity Company with a S2 social subscription type of 105 kVA. The designed solar power plant has a capacity of 25 kW, or 25% of the installed electrical capacity. This research aims to compare the solar panels and inverter configurations that will be used in solar power plants. Moreover, this study aims to find out which configuration will provide the best results and the biggest savings. Technical analysis is carried out with the photovoltaic system (PVSyst) software to calculate the energy produced by solar panels, inverter losses, and other results. On the other hand, economic analysis is carried out with RetScreen software to calculate net present value (NPV), benefit cost ratio (BCR), and payback period (PP). Based on the PVSyst simulation results, the estimated energy production for each variant is 39,684 kWh; 39,633 kWh; 39,507 kWh; and 39,446 kWh. The first variant has the biggest performance ratio value of 84.1%. Based on the Retscreen calculation result, the third variant has an NPV value of $22,698, a BCR value of 2, and a PP of 8.7 years, which has the best result and the highest advantages.
Descriptive data mining for multi-shelf product allocation in traditional retail Singgih Saptadi; Wiwik Budiawan; Ary Arvianto; Purnawan Adi Wicaksono; Chaterine Alvina Prima Hapsari; Dhimas Wachid Nur Saputra
International Journal of Advances in Applied Sciences Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v15.i2.pp830-843

Abstract

The business expansion of minimarkets in small cities is one of the serious threats to the sustainability of traditional retail businesses or small independent retailers. Many traditional retailers eventually closed due to their inability to maintain competitiveness, as customers increasingly prefer shopping at modern retail outlets. A well-organized store layout can improve the shopping experience of customers, which has an impact on customer satisfaction and retail competitive advantage. Currently, shelf space allocation in traditional retail is still inattentive, making the placement of products on the shelf random and erratic. Based on these problems, this research aimed to design multi-shelf product allocation according to customer shopping patterns by combining clustering algorithms and market basket analysis (MBA). Clustering aims to divide data points into two different clusters, namely dominant product and less favored product, while MBA aims to identify the customer purchase pattern and preferences. The three MBA scenarios produced four, twelve, and forty rules. The research successfully designed two layouts by utilizing a combination of clustering and MBA algorithms. The utilization of data mining allows traditional retailers to extract information from the database to be arranged into a layout design that fits the shopping patterns and customer preferences.