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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering International Journal of Reconfigurable and Embedded Systems (IJRES) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics CommIT (Communication & Information Technology) International Journal Science and Technology (IJST)
Agung Trisetyarso
Bina Nusantara University
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering

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Energy saving on IoT using LoRa: a systematic literature review Mochammad Haldi Widianto; Arief Ramadhan; Agung Trisetyarso; Edi Abdurachman
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 11, No 1: March 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v11.i1.pp25-33

Abstract

The development of devices connected to the internet is very significant, encouraging the creation of the internet of things (IoT). With remote systems, IoT is not enough to use in case of internet instability. By using long range (LoRa), IoT systems can now solve this problem. Millions of data make IoT-LoRa have to spend a lot of energy. This paper helps discover where recent studies offer a broad perspective on energy savings using the systematic literature review (SLR). The paper extracted 252 articles from IEEE, ACM, MDPI, Springer, Hindawi, ScienceDirect, and IAES. 44 articles passed the specified inclusion and exclusion criteria. The article focuses on knowledge about IoT-Lora, energy saving needs, energy saving factors, and the paper demographics. The author synthesizes studies for that purpose on IoT applications using LoRa.
Confidence of AOI-HEP Mining Pattern Harco Leslie Hendric Spits Warnars; Agung Trisetyarso; Richard Randriatoamanana
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 3: June 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i3.5303

Abstract

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) has been proven can mine frequent and similar patterns and the finding AOI-HEP patterns will be underlined with confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern, and each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence per AOI-HEP pattern will show how interested each of AOI-HEP pattern, whilst confidende per dataset will show how interested each dataset between frequent and similar patterns. The experiments for finding confidence of each AOI-HEP pattern showed that AOI-HEP pattern with growthrate under and above 1 will be recognized as uninterested and interested AOI-HEP mining pattern since having confidence AOI-HEP mining pattern under and above 50% respectively. Furthermore, the uniterested AOI-HEP mining pattern which usually found in AOI-HEP similar pattern, can be switched to interested AOI-HEP mining pattern by switching their support positive and negative value scores.
INDONESIA DIGITAL GOVERNMENT AUDITING MODEL USING RULE BASED AND CLOUD CASE-BASED REASONING Hari Setiabudi Husni; Arief Ramadhan; Edi Abdurachman; Agung Trisetyarso
International Journal Science and Technology Vol. 1 No. 2 (2022): July: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (335.679 KB) | DOI: 10.56127/ijst.v1i2.147

Abstract

This paper explores the possibility of combining process model of Digital Government auditing, Rule Based and Cloud Case-Based Reasoning. Digital Government and Digital Government Auditing definition retrieve from Indonesia Presidential Regulation number 95-year 2018. consist two goals that the regulation aims, the first was to realize good governance clean, effective, transparent, and accountable as well as quality and reliable public services an digital government system is required; and second was to improve cohesiveness and efficiency of the electronic-based government system governance and management required national digital government; The existence variation of regulations and auditing standard creating complex reference database and hard to find solution for assessment and auditing Indonesia Digital Government. Rule-based and Case-based reasoning could help auditor in searching and documenting unsolved and solved auditing problem. The result shown that there is possibility to enhance audit process to create better audit result and more efficient in audit working time.
Acceptance of augmented reality in video conference based learning during COVID-19 pandemic in higher education Sunardi Sunardi; Arief Ramadhan; Edi Abdurachman; Agung Trisetyarso; Muhammad Zarlis
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4035

Abstract

Three years after the COVID-19 pandemic emerged, we have adapted to the new normal, especially in the education field. Learning with video conferences has become our daily activity, and learning tools have gotten more prominent attention to gain student engagement, especially in emergency remote teaching (ERT). Since the trends of metaverse campaigns by meta, augmented reality (AR) has increased recognition in education contexts. However, very little research about the acceptance of augmented reality in video conferences, especially among university students. This paper aims to measure acceptance of AR in video conferences to motivate and inspire students to gain benefits and get impactful technology in the learning process. The research gathered data from a survey of 170 university students (from 5 majors in the study program and 17 different demographic areas) using unified theory of acceptance of technology 2 (UTAUT2). The result reveals that variables significantly impact acceptance: performance expectancy, hedonic motivation, and habit. The least significant but still positive effects are effort expectancy, social influence, and facilitating conditions. The study will provide helpful information on AR technology in video conferences and help top-level management in the university that provides online/distance learning in the early diffusion stage for metaverse in education.
Fish Classification System Using YOLOv3-ResNet18 Model for Mobile Phones Suryadiputra Liawatimena; Edi Abdurachman; Agung Trisetyarso; Antoni Wibowo; Muhamad Keenan Ario; Ivan Sebastian Edbert
CommIT (Communication and Information Technology) Journal Vol. 17 No. 1 (2023): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v17i1.8107

Abstract

Every country in the world needs to report its fish production to the Food and Agriculture Organization of the United Nations (FAO) every year. In 2018, Indonesia ranked top five countries in fish production, with 8 million tons globally. Although it ranks top five, the fisheries in Indonesia are mostly dominated by traditional and small industries. Hence, a solution based on computer vision is needed to help detect and classify the fish caught every year. The research presents a method to detect and classify fish on mobile devices using the YOLOv3 model combined with ResNet18 as a backbone. For the experiment, the dataset used is four types of fish gathered from scraping across the Internet and taken from local markets and harbors with a total of 4,000 images. In comparison, two models are used: SSD-VGG and autogenerated model Huawei ExeML. The results show that the YOLOv3-ResNet18 model produces 98.45% accuracy in training and 98.15% in evaluation. The model is also tested on mobile devices and produces a speed of 2,115 ms on Huawei P40 and 3,571 ms on Realme 7. It can be concluded that the research presents a smaller-size model which is suitable for mobile devices while maintaining good accuracy and precision.
Machine learning in drug supply chain management during disease outbreaks: a systematic review Gunadi Emmanuel; Arief Ramadhan; Muhammad Zarlis; Edi Abdurachman; Agung Trisetyarso
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5517-5533

Abstract

The drug supply chain is inherently complex. The challenge is not only the number of stakeholders and the supply chain from producers to users but also production and demand gaps. Downstream, drug demand is related to the type of disease outbreak. This study identifies the correlation between drug supply chain management and the use of predictive parameters in research on the spread of disease, especially with machine learning methods in the last five years. Using the Publish or Perish 8 application, there are 71 articles that meet the inclusion criteria and keyword search requirements according to Kitchenham's systematic review methodology. The findings can be grouped into three broad groupings of disease outbreaks, each of which uses machine learning algorithms to predict the spread of disease outbreaks. The use of parameters for prediction with machine learning has a correlation with drug supply management in the coronavirus disease case. The area of drug supply risk management has not been heavily involved in the prediction of disease outbreaks.
Co-Authors Antoni Wibowo Arief Ramadhan Edi Abdurachman Edi Abdurachman Gunadi Emmanuel Hari Setiabudi Husni Ivan Sebastian Edbert Mochammad Haldi Widianto Muhamad Keenan Ario Muhammad Zarlis Richard Randriatoamanana Sunardi Sunardi Suryadiputra Liawatimena Warnars, Harco Leslie Hendric Spits