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All Journal Indonesian Journal on Computing (Indo-JC) IJoICT (International Journal on Information and Communication Technology)
Kusuma Adi Achmad
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Computer Science & IT

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Information Technology Governance Analysis Using COBIT 5 Framework: (Case Study : PLANT Division PT Pamapersada Nusantara) Kurniawan, Kelvin; Kusuma Adi Achmad; Satria Akbar Mugitama
Indonesian Journal on Computing (Indo-JC) Vol. 8 No. 1 (2023): April, 2023
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2023.8.1.686

Abstract

PT Pamapersada Nusantara or better known as PAMA is a subsidiary of PT United Tractors Tbk. There are several divisions in PAMA, one of which is the PLANT Division which is the focus of this research. To improve this performance, a special Information Technology System was created for employees. In order for application development to run better and in line with the company, an analysis is carried out which is expected to be a benchmark and company recommendation to optimize the information system. The analysis was carried out using the COBIT 5 framework method, the researcher focused on the MEA01 (Monitor, Evaluate, Assess Performance and Conformance) domain. Then for the method is observation and interview, researchers use this method to be able to collect accurate data With this method, researcher can provide recommendations regarding the results of the IT governance analysis to ensure and optimize that the information system runs according to the company’s wishes based on the COBIT 5 framework standardization. The average result obtained is level 3 for the current condition and level 4 for the expected condition. The recommendation of this study is that companies can implement regular monitoring SOPs on existing IT management and governance.
Socio-user Context Aware-Based Recommender System: Context Suggestions for A Better Tourism Recommendation Kusuma Adi Achmad; Lukito Edi Nugroho; Achmad Djunaedi; Widyawan
International Journal on Information and Communication Technology (IJoICT) Vol. 9 No. 2 (2023): Vol.9 No. 2 Dec 2023
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v9i2.858

Abstract

The existing tourism recommender system model is mostly predictive analytics for destination recommendations (item recommendation). Limited research has been conducted in the discussion of a recommender system model, particularly context suggestion. Thus, it is necessary to develop a recommender system model not only to predict tourism destinations but also to suggest contexts appropriate for tourist preferences (context suggestions). A deep learning method was used to create a model of the socio-user context aware-based recommender system for context suggestions. The attribute used as a label to suggest context was uHijos, uCuisine, uAmbience, and uTransport. The accuracy of the socio-user context aware-based recommender system in suggesting the context of uHijos, uAmbience, and uTransport was 100% with an error rate of 0%. It was found that only the level of recognition of the model in suggesting uCuisine was less accurate (below 30%) with a classification error for more than 70%. Performance evaluation of the socio-user model context-based recommender system was considered efficient, particularly for the evaluation of the level of accuracy, completeness (recall/sensitivity), precision, and a harmonic average of precision and recall (F-score), mainly for label/context of uHijos, uAmbience, and uTransport.
Co-Authors Achmad Djunaedi Kurniawan, Kelvin Lukito Edi Nugroho Satria Akbar Mugitama Widyawan