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p-Index From 2021 - 2026
0.444
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All Journal Journal Informatic, Education and Management (JIEM) Ceddi Journal of Information System and Technology (JST)
Aditya Halim Perdana Kusuma
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Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Other

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Python-Powered Precision: Unraveling Consumer Price Index Trends in Makassar City through a Duel of Long Short-Term Memory and Gated Recurrent Unit Models Abd. Rahman; First Wanita; Rose Arisha; Aditya Halim Perdana Kusuma; Azhary, Zulmy
Ceddi Journal of Information System and Technology (JST) Vol. 2 No. 2 (2023): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v2i2.44

Abstract

This research aims to carry out a predictive analysis of the Consumer Price Index in the city of Makassar to anticipate possible impacts on inflation and deflation in the future. The Consumer Price Index is an indicator that can be used as a basis for measuring changes in the prices of goods and services purchased by consumers which have an impact on inflation in a region. The CPI is very useful for knowing the level of increase in prices, services, and income, as well as measuring the amount of production costs. This data was obtained through the official website of the Central Statistics Agency (BPS) for the Makassar city area. The methods used in this research are Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU). The results of this research show that based on analysis and testing, the LSTM model has an MAE of 1.0849 and the GRU model has an MAE of 0.9915, which shows that there is no significant difference between the two methods and both methods can work very well, however, The lowest error value was obtained in the GRU model using a 70:30 dataset ratio, 9 number of sequences, 16 neurons in hidden layer 1 and 32 neurons in hidden layer 2, and 1000 number of epochs.
RESOURCE-BASED VIEW (RBV) AND VALUE CHAIN BASED INTERNAL CAPABILITY ANALYSIS IN MAINTAINING COMPETITIVE ADVANTAGE IN BANKING SERVICES: A CASE STUDY OF PT BANK CENTRAL ASIA TBK Aditya Halim Perdana Kusuma; Ackhriansyah Ahmad Gani; Muthia Indah Permatasari; Andi Muh Adib Asharil; Muh. Farhan Firman
Journal Informatic, Education and Management (JIEM) Vol 8 No 2 (2026): AUGUST
Publisher : STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61992/jiem.v8i2.408

Abstract

The acceleration of financial technology (fintech) and digital banks (neobanks) has created a highly competitive landscape in the national banking industry. This study aims to analyze the internal capabilities of PT Bank Central Asia Tbk. (BCA) in identifying core competencies and mapping value creation to maintain its position as a market leader. The theoretical framework applied is the Resource-Based View (RBV) through the VRIO matrix (Value, Rarity, Inimitability, Organization) and Value Chain Analysis. The research method employs a descriptive qualitative approach with secondary data collection sourced from annual reports, corporate sustainability reports, and related scientific literature. The Value Chain analysis reveals that BCA generates superior value added in operational activities (IT system security) and services (customer service quality and omnichannel ecosystem). Furthermore, the VRIO analysis indicates that its brand equity as a secure transactional bank, massive low-cost funding base (CASA), and adaptive information technology infrastructure are strategic resources that meet the criteria for a sustainable competitive advantage. Conversely, the high investment cost for maintaining the physical network (branch offices and ATMs) is identified as an internal weakness in the digitalization era. This study recommends that BCA accelerate the migration of physical services to cloud-based digital platforms to reduce long-term operational costs.
Co-Authors Abd. Rahman Ackhriansyah Ahmad Gani Andi Muh Adib Asharil Azhary, Zulmy First Wanita Muh. Farhan Firman Muthia Indah Permatasari Rose Arisha