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All Journal JURNAL SISTEM INFORMASI BISNIS AJIE (Asian Journal of Innovation and Entrepreneurship) International Journal of Artificial Intelligence Research Jurnal Teknik Informatika (JUTIF) JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) ELECTROPS : Jurnal Ilmiah Teknik Elektro
Burhandenny, Aji Ery
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering

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Analysis Potential of Solar and Wind as Power Plant in Bontang Kuala Using Software Homer: Analisis Potensi Energi Matahari dan Angin Sebagai Pembangkit Listrik di Bontang Kuala Menggunakan Software Homer Sakti, Bima; Burhandenny, Aji Ery; Utomo, Restu Mukti; Nugroho, Happy; Wirawan, Adi Pandu
JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Vol. 8 No. 1 (2024): April
Publisher : Muhammadiyah University, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jeeeu.v8i1.1670

Abstract

The increasing need for electrical energy is becoming a problem due to limited fossil energy, so it is necearry to know locations that have the potential to generate electricity from renewable energy. This study simulates and analyzes the potential of solar and wind energy in Bontang Kuala as a power plant using Homer software. Load planning uses a peak load of 38,44 kW and usage of 471,56 kWh/day from the results of a survei conducted at one of the RTs in Bontang Kuala. The simulation produces three optimal configurations of three types of generators, namely Solar Cell, Hybrid Power Plant and Wind Power Plant. The most optimal configuration is the Solar Cell system with the smallest NPC value of Rp3,6 B and this system has a solar panel capacity of 142 kW, a battery capacity of 461 kWh and an inverter capacity of 50 kW.
Analisis QoS Menggunakan Load Balancing Dengan Metode Nth Dan Failover Pada Mikrotik Di SMKN 1 PPU Rahmadhani, Rizal; Burhandenny, Aji Ery; Wirawan, Adi Pandu; Suprihanto, Didit; Nugroho, Happy
ELECTROPS : Jurnal Ilmiah Teknik Elektro Vol 3, No 1 (2024): ELECTROPS : Jurnal Ilmiah Teknik Elektro
Publisher : Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/electrops.v3i1.12964

Abstract

A fast and stable internet connection is the hope of all agencies and companies in their efforts to improve online performance. However, sometimes there are many obstacles to getting the desired connection quality, especially if we expect it from only 1 internet service provider. Adding an ISP in an effort to improve connection quality could be a solution if configured correctly. Load Balancing is a way to combine two network connections into one. The solution that can be taken to overcome this problem is by implementing the Nth method of load balancing and failover techniques which function to divide and balance the traffic load on the two existing connection lines and failover functions to back up if one of the ISPs goes down. The failover method test results showed that Indihome was 1 second and Indosat LTE was 2 seconds, with these results being categorized as very fast. For the Nth method load balancing results, the average Throughput results were 14472 kbps for 360p, 45501 kbps for 480p, and 27678 kbps for 720p. These results can be categorized as very good from the TIPHON standard, for an average delay of 87.25 ms for 360p, 340.6 ms for 480p and 375 ms for 720p from these results can be categorized as sufficient from the TIPHON standard, finally the average packet loss is 0.6% for 360p, 0.4% for 480p and 0.3% for 720p from these results can be categorized as very good by TIPHON standards.
Information System Development of Cattle Weight Recording and Forecasting Using Website-Based Linear Regression Suprihanto, Didit; Delwizar, Muhammad Arya; Burhandenny, Aji Ery; Harjanto, Arif; Nugroho, Happy; Rumawan, Fatkhul Hani
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp293-300

Abstract

Cattle plays an important role in meeting food demand in Indonesia, especially in the livestock sector, where cattle farms must be prepared to provide beef supply to various regions in Indonesia. On the other hand, in East Kalimantan, the demand for beef is also increasing along with the growth of population and economic activity. The role of technology is also quite important in meeting the need for beef. One of them is the use of website information system technology as a recording and reporting application. One of the distributors also involved in cattle farming in East Kalimantan is PT XYZ, which was newly established in 2020. The need for technology includes recording system, reporting system and cattle weight forecasting system. The purpose of this study is to design a web-based application that helps PT XYZ to record, report and predict cattle weight. The application development used Laravel framework to predict the increase in cattle weight using linear regression method. While the methodology used to develop the application was Waterfall method which included the phases of requirement analysis, application design, software development, testing and implementation. The application testing results showed that the application complied with the design that has been implemented and all the functions on the application page worked properly. The cattle weight recording and forecasting information system generated various reports, such as monthly cattle weight progress, monthly cattle sales reports, cattle weight growth forecast analysis, and cattle sales profit reports.
Penjadwalan Optimal Perangkat IoT Menggunakan Algoritma Round Robin dalam Sistem Pemantauan Lingkungan: Sebuah Pendekatan Simulasi: english Burhandenny, Aji Ery; Pranoto, Sarwo; Suprihanto, Didit
Asian Journal of Innovation and Entrepreneurship Volume 09, Issue 02, May 2025
Publisher : UII

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/ajie.vol9.iss2.art2

Abstract

This study explores the application of the Round Robin algorithm for scheduling tasks in Internet of Things (IoT) systems designed for environmental monitoring, such as temperature and humidity tracking. Efficient task scheduling is critical to minimize latency and energy consumption in IoT networks. Using a Python-based simulation, this research evaluates the performance of the Round Robin algorithm in managing 10 to 50 virtual IoT devices tasked with environmental data collection, comparing it with Priority with Aging and Genetic Algorithm approaches. The simulation results indicate that Round Robin reduces the average waiting time by 15% compared to random scheduling, while the Genetic Algorithm outperforms Round Robin by approximately 20% in high-density networks. This approach provides valuable insights into IoT scheduling efficiency without requiring physical deployment, making it relevant for large-scale IoT system development.
An extraction of shapes and support vector machine methods for identification of decorative wall “Lamin” motifs of the Dayak Kenyah Pampang tribe Haviluddin, Haviluddin; Wati, Masna; Alfred, Rayner; Burhandenny, Aji Ery; Pratama, Arief Ardi
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.475

Abstract

One of the Dayak cultures of Kalimantan Island, Indonesia is a traditional house called Lamin where each wall is decorated according to tribal characteristics. This study aims to identify the image on the Lamin wall using the Support Vector Machine (SVM) method based on the eccentricity and metric parameter values. The data of this study consisted of 50 types of images of the Lamin wall motifs of the Dayak Kenyah tribe consisting of tebengaang, dragon, crocodile, tiger, and arch which were taken from the tourist village, Pampang, Samarinda, East Kalimantan. Based on the experiment, the shape feature extraction method has produced the highest value of the eccentricity parameter which is 0.6979 and the metric parameter is 0.9953 on the image of the arch. Motif identification using the SVM method using linear, Gaussian/RBF, and polynomial kernel parameters has resulted in the highest accuracy with 80% image composition of kernel polynomial at 85%, Gaussian/RBF at 80%, and linear at 78%.
COMPARISON OF SUPPORT VECTOR MACHINE AND INDOBERT IN NON-FUNCTIONAL REQUIREMENT CLASSIFICATION OF APPLICATION USER REVIEWS Rais Kumar, Abdul Ghofur; Sukmono, Yudi; Burhandenny, Aji Ery
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.1424

Abstract

User reviews of mobile applications have become a valuable source of information for evaluating the quality of an application. It is crucial for application developers to understand what users express in their reviews. One aspect that can be analyzed from user reviews is Non-Functional Requirement (NFR). Classifying reviews based on NFR is essential in understanding how an application can be enhanced. Although user reviews have the potential to provide valuable insights into NFR, manually processing thousands of user reviews is a laborious and inefficient task. Therefore, artificial intelligence methods are employed to automatically classify user reviews into relevant NFR categories. This research discusses the performance comparison of the SVM and IndoBERT algorithms in NFR classification. The study involves collecting application review data from 2018 to 2023, sourced from Google Playstore and Apple Appstore, followed by annotating the review data based on ISO 25010. Subsequently, the data is allocated into training and testing sets with an 80:20 ratio. Further, a data preprocessing phase is conducted, which includes steps such as lowercasing, tokenization, special character removal, text normalization, and text stemming. The next step involves training the SVM and IndoBERT algorithms on the dataset. Finally, the evaluation is carried out by calculating the F1-score. The research results indicate that the IndoBERT model outperforms the SVM model. The IndoBERT algorithm excels in recognizing NFR in reviews, achieving an F1-score of 93%, while the SVM algorithm achieves an F1-score of 91%.
Co-Authors Arif Harjanto Delwizar, Muhammad Arya Didit Suprihanto, Didit Haviluddin Haviluddin Nugroho, Happy Pranoto, Sarwo Pratama, Arief Ardi Rahmadhani, Rizal Rais Kumar, Abdul Ghofur Rayner Alfred Rumawan, Fatkhul Hani Sakti, Bima Utomo, Restu Mukti Wati, Masna Wirawan, Adi Pandu Yudi Sukmono, Yudi