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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization Numeracy : Jurnal Ilmiah Pendidikan Matematika Dirasatul Ibtidaiyah
Prana Ugi
Department Of Mathematics, Universitas Sumatera Utara, Medan, 20155, Indonesia
Computer Science & IT Education Electrical & Electronics Engineering Mathematics

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Thermostats: an Open Source Shiny App for Your Open Data Repository Dasapta Erwin Irawan; Muhammad Aswan Syahputra; Prana Ugi; Deny Juanda Puradimaja
JOIV : International Journal on Informatics Visualization Vol 3, No 2-2 (2019): Internet of Things and Smart Environments
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1146.77 KB) | DOI: 10.30630/joiv.3.2-2.282

Abstract

Hydrochemical analysis has emerged as a powerful methodology in geothermal system profiling. Indonesia is the capital of geothermal energy with its more than 100 active volcanoes. Therefore we need to have an analytical, data-driven, and user-focused online application of geothermal water quality. Proudly we introduce Thermostats (https://aswansyahputra.shinyapps.io/thermostats/). We collected water quality from 416 geothermal sites across Indonesia. Three main objectives are to provide an online open-free to use data repository, to visualize the dataset to suit user’s needs, and to help users understand the geothermal system of each particular site. At the end, we hope they like this system and donate their own dataset to make it better for future users. We designed this online app using Shiny, because it’s open source, lightweight and portable. It’s very intuitive to load our descriptive, bivariate and multivariate statistics. We selected Principal Component Analysis and Cluster Analysis as two strong statistics for water sample classification. Users could add their own dataset by making a pull request on Github (https://github.com/dasaptaerwin/thermostats) or sending it to us by email to make it visible in the application and included in the visualization. We make this application portable, so it can be installed on a local computer or a server, to enable an easy and fluid way of data sharing between collaborators.
APLIKASI UJI MANN-WHITNEY DALAM MENENTUKAN ADA TIDAKNYA PERBEDAAN INDEKS PRESTASI KUMULATIF ANTARA MAHASISWA DOMINAN OTAK KANAN DAN MAHASISWA DOMINAN OTAK KIRI DI FMIPA USU Prana Ugiana Gio
Jurnal Numeracy Vol 1 No 2 (2014)
Publisher : Program Studi Pendidikan Matematika, Universitas Bina Bangsa Getsempena

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (197.965 KB) | DOI: 10.46244/numeracy.v1i2.122

Abstract

Terdapat beberapa metode atau uji yang disediakan dalam statistika untuk menguji beda dari dua rata-rata berdasarkan dua populasi yang independen. Salah satu uji untuk menguji ada tidaknya perbedaan rata-rata dari dua populasi yang berbeda adalah uji Mann-Whitney. Pada tulisan ini diterapkan uji Mann-Whitney untuk menentukan ada tidaknya perbedaan indeks prestasi kumulatif antara mahasiswa dominan otak kanan dan mahasiswa dominan otak kiri di FMIPA USU. Berdasarkan penelitian yang telah dilakukan, maka diperoleh hasil bahwa terdapat perbedaan yang signifikan secara statistik antara jumlah mahasiswa dominan otak kanan dan jumlah mahasiswa dominan otak kiri di FMIPA USU pada tingkat signifikansi 5%. Namun tidak terdapat perbedaan yang cukup signifikan secara statistik mengenai indeks prestasi kumulatif antara mahasiswa dominan otak kanan dan mahasiswa dominan otak kiri di FMIPA USU pada tingkat signifikansi 5%.
RESPON MAHASISWA PGMI TERHADAP PLATFORM WAKELET UNTUK PEMBELAJARAN ONLINE DI MASA PANDEMI COVID-19 Nashran Azizan; Maulana Arafat Lubis; Prana Ugiana Gio; Marhamah Marhamah
DIRASATUL IBTIDAIYAH Vol 1, No 1 (2021): DIRASATUL IBTIDAIYAH
Publisher : Pendidikan Guru Madrasah Ibtidaiyah Institut Agama Islam Negeri Padangsidimpuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1018.04 KB) | DOI: 10.24952/ibtidaiyah.v1i1.3567

Abstract

The COVID-19 pandemic has caused many changes in various aspects of life, including in the education sector and the learning system. The application of learning and teaching from home policies for students and lecturers alike changes the face-to-face learning perspective online by utilizing various applications and platforms. This study aims to determine the effectiveness of Wakelet for higher education and the benefits of Wakelet in online learning. This research method is descriptive quantitative through a survey. The population of this study was students of the PGMI IAIN Padangsidimpuan study program semester 6. The sampling technique used in this study was probability sampling which included simple random sampling. The sample was determined based on the Slovin formula assisted by Microsoft Excel software, so the sample was 94 respondents. The data collection technique used a questionnaire by Google Form. Analysis of research data using descriptive statistics assisted by STATCAL and EAVIS software. The results showed that the Wakelet platform was categorized as effective and efficient for use in the university environment, especially in the PGMI IAIN Padangsidimpuan Study Program based on student responses at a percentage of 78.72%. The Wakelet platform is also easily accessible and innovative, varied, and creative based on student responses, which are 80.85%. Besides having an attractive appearance, the Wakelet platform also has benefits, including bringing together all types of student work collected, such as videos, article texts, images, PDF files of papers/e-books / e-journals / e-proceedings, sharing web links, media links,social media and others.
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.
Metaheuristic nurse scheduling with hospital clustering using flower pollination algorithm Muhammad Khahfi Zuhanda; Hartono Hartono; Sayuti Rahman; Prana Ugiana Gio; Erianto Ongko
Bulletin of Electrical Engineering and Informatics Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i3.11243

Abstract

Effective nurse scheduling is essential to ensure balanced workloads, reduce fatigue, and maintain healthcare service quality. However, the nurse scheduling problem (NSP) is complex due to constraints related to nurse skills, task requirements, and legal working-hour limits. This study proposes an integrated framework combining a mathematical optimization model with metaheuristic algorithms to generate optimal daily nurse activity schedules. Genetic algorithm (GA) and simulated annealing (SA) are employed to produce near-optimal solutions for nurse populations ranging from 3 to 50 individuals, considering skill-level compatibility, workload balance, and maximum working hours. Experimental results using real scheduling data from 30 nurses across three skill levels demonstrate that all generated schedules satisfy the imposed constraints, with no nurse exceeding the 12hour daily working limit. Comparative analysis shows that GA achieves lower scheduling costs for larger nurse populations, while SA consistently requires significantly shorter computation times, making it suitable for time-sensitive applications. In addition, the flower pollination algorithm (FPA) is used to cluster 3,155 hospitals based on bed capacity, service variety, and workforce size, supporting data-driven workforce distribution analysis. The proposed framework integrates operational scheduling optimization with hospital-level clustering, providing practical decision support for healthcare workforce planning.
Co-Authors Agung Sutoto Ahmad Marzuqi Bens Pardamean Dasapta Erwin Irawan Deny Juanda Puradimaja Erianto Ongko Hartono Hartono Maengseok Noh Marhamah Marhamah Maulana Arafat Lubis Muhammad Aswan Syahputra Muhammad Khahfi Zuhanda Nashran Azizan Rahman, Sayuti Rezzy Eko Caraka Rumanintya Lisaria Putri Rung Ching Chen Tommy Novianto