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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Computer Science
Maengseok Noh
Pukyong National University
Computer Science & IT

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Supply chain strategy during the COVID-19 terms: sentiment analysis and knowledge discovery through text mining Muhammad Khahfi Zuhanda; Yuan Anisa; Desniarti Desniarti; Muhammad Hafiz; Anil Hakim Syofra; Rezzy Eko Caraka; Maengseok Noh
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1120-1127

Abstract

The coronavirus pandemic has affected not only health but also the economy. The use of big data in finding information can be used to gain profits that logistics companies can utilize to survive during the pandemic. This study conducted text-mining research on service consultant sites in the logistics sector. This study aims to present frequency diagrams, analyze sentiment using the National Research Council (NRC) lexicon, present bigrams, and seek knowledge about strategies to minimize shipping costs and maintain inventories of manufactured goods. The words "supply", "chain", and "COVID-19" are words that are used frequently throughout the article. The results of this study showed that the words that often appear from word excavation are the words "supply", "chain", "logistics", "kpis," and "inventory". Then emotion trust becomes an emotional word that often appears in articles. The words "Supply" and "pandemic" are the words that seem the most positive and negative words, respectively. The words "COVID-19", "safety stock", and "inventory management" are words that often appear together. The result of discovery knowledge is that logistics consultants offer emotions of trust and provide many insights on minimizing shipping costs and maintaining inventory during a pandemic.
Geographically weighted regression analysis of electricity consumption in Indonesian households: aligning with SDG 7 Tommy Novianto; Rezzy Eko Caraka; Prana Ugiana Gio; Rumanintya Lisaria Putri; Agung Sutoto; Rung Ching Chen; Maengseok Noh; Bens Pardamean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.26051

Abstract

The objective of this study is to establish a thorough comprehension of the interaction of population dynamics, poverty rates, minimum wage levels, and regional GDP in relation to household electricity consumption. The main objective is to improve the precision of electricity demand predictions and prevent planning mistakes, such as the considerable surplus of 6-7 GW in the Java Bali system between 2020 and 2023, resulting in major financial losses. We evaluate and compare the models by employing several approaches, such as ordinary least square (OLS) and geographically weighted regression (GWR) with fixed and adaptive bandwidths. We use modified R-squared and corrected Akaike Information Criterion (AICc) values for this assessment. The GWR with adaptive bandwidth is shown to be the most resilient method and is subsequently chosen for modeling. The results indicate that there is a strong correlation between the number of impoverished individuals and electricity use, with a coefficient range of 0.35-0.55. Furthermore, the correlation between poverty rates and power usage is defined by a coefficient that varies between -0.0010 and -0.0030. There is a direct relationship between regional GDP and power growth, as indicated by coefficients ranging from 1,000,000 to 5,000,000. Moreover, the impact of minimum wage levels differs among different locations.
Unlocking insights from Ministry of Marine Affairs and Fisheries annual reports using LDA: a deep dive into SDG 14 Ahmad Marzuqi; Rezzy Eko Caraka; Prana Ugiana Gio; Rung Ching Chen; Maengseok Noh; Bens Pardamean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 4: August 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i4.26063

Abstract

Annual reports serve as vital instruments for government ministries and agencies, enabling transparency and accountability in managing state budgets (APBN) and activities, thereby fulfilling a crucial role in public accountability, particularly in the context of sustainable development goal (SDG) 14. However, due to their extensive nature, it becomes imperative to conduct topic modeling analysis to discern trends and topics within these reports. In this study, latent Dirichlet allocation (LDA), a prominent topic modeling technique, is employed to analyze the annual reports of the Ministry of Marine Affairs and Fisheries (KKP) Indonesia from 2015 to 2022. Utilizing the coherence score as an evaluation metric, we assess the quality of topic models across each report year. Our findings underscore the consistent emphasis on fisheries and marine-related initiatives, emphasizing their relevance to SDG 14 and Indonesia’s maritime landscape. Ultimately, this study offers valuable insights to inform strategic planning and decision-making processes within the KKP, contributing to the advancement of SDG 14 and promoting sustainable development in Indonesia’s fisheries and marine sectors.
Co-Authors Agung Sutoto Ahmad Marzuqi Anil Hakim Syofra Bens Pardamean Desniarti Desniarti Muhammad Hafiz Muhammad Khahfi Zuhanda Prana Ugi Rezzy Eko Caraka Rezzy Eko Caraka Rumanintya Lisaria Putri Rung Ching Chen Tommy Novianto Yuan Anisa