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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Ekonomi dan Bisnis Islam Konvergensi SYIRKAH Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Dialektika: Jurnal Ekonomi dan Ilmu Sosial Jurnal Informasi dan Teknologi MALIA: Journal of Islamic Banking and Finance Bima Abdi: Jurnal Pengabdian Masyarakat Brilliance: Research of Artificial Intelligence Insand Comtech : Information Science and Computer Technology Journal Journal of Artificial Intelligence and Digital Business
Ubaidi, Ubaidi
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Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Application of Internet of Things Technology in Monitoring Water Quality in Fishponds Putra , Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Saputra, Rama Nurja; Haris, Farras Maulana; Barokah, Selviana Nur Rizqi
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4231

Abstract

Monitoring water quality in fish ponds is essential to maintain fish health and productivity. In recent years, Internet of Things (IoT) technology has emerged as an effective solution to efficiently monitor and manage water quality. This article describes the application of IoT technology in monitoring the water quality of aquaculture ponds with the aim of improving fish productivity and welfare. Data on water quality parameters such as temperature, dissolved oxygen, pH, ammonia levels, and turbidity can be monitored in real time through a network of connected sensors. The main advantage of using IoT for fish pond water quality monitoring is that it can provide accurate and fast information on water conditions. This allows fish farmers to proactively take appropriate actions to maintain an optimal water environment for fish growth. In addition, integration with data management and remote monitoring systems allows fish pond owners to continuously monitor water conditions, even in remote locations. This helps reduce the risk of environmental damage and fish loss due to inappropriate water quality conditions. Therefore, the use of IoT technology for water quality monitoring in fish ponds not only increases productivity but also ensures the well-being of fish and reduces negative impacts on the environment.
Improving Network Service Quality in parts of Sampang City: QoS Evaluation and User Perception of QoE Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Aziz, Mohammad; Irfan, Moh.; Alim, Royfal
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4311

Abstract

In an era of rapid urbanization, the quality of network services in urban environments is becoming increasingly important. This article explores efforts to improve network service quality in several sampang cities through an evaluation of Quality of Service (QoS) and user perceptions of Quality of Experience (QoE). The research is based on a survey conducted at various locations in sampang city to collect data on the reliability, speed, and availability of network services. The survey involved a diverse sample of users, covering a wide range of ages, professions, and levels of technology usage. In addition, we also analyzed users' perceptions of service quality based on their experiences of using the network in an urban environment. The results highlighted several key challenges in improving QoS, such as user density, signal interference, and network infrastructure limitations. However, we also found that strategies such as the use of advanced network technologies, such as 5G and beamforming, as well as traffic prioritization based on application type, can help to significantly improve QoS. In addition, we found a strong positive correlation between improved QoS and improved QoE, suggesting that improved quality of service has a direct impact on improving user experience. These findings provide valuable insights for network operators and policy makers in their efforts to improve network services in dense urban environments. The research also recommends further investment in network technologies and the development of policies that support more effective management of network traffic to ensure optimal quality of service.
Effect Of Distance On Wi-Fi Signal Quality In The Home Environment Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Kusuma, R. Okky Firmansyah; Syam, Abd Mu’iz; Efendy, Satrio Ananta
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4319

Abstract

This study aims to analyze the effect of distance on Wi-Fi signal quality in a home environment. With the increasing use of wireless devices and applications that rely on internet connectivity, Wi-Fi signal quality has become crucial to support daily activities such as streaming, online gaming, remote work, and smart home automation. This research employs an experimental method by measuring signal strength and data transmission speed at various distances from the Wi-Fi router. Measurements were taken at several points, ranging from 1 meter to 15 meters from the router, in different rooms and through different obstacles like walls and furniture.To conduct the analysis, a Wi-Fi analyzer was used to measure signal strength (in dBm) and a speed test was employed to determine data transmission speed (in Mbps) at each distance. The results showed that the greater the distance from the router, the Wi-Fi signal strength decreased significantly, leading to a corresponding decrease in data transmission speed. In addition, obstacles such as walls and electronic interference further degraded the signal quality.This study concludes that optimizing router placement and using signal booster devices, such as Wi-Fi extenders or mesh networks, can be effective solutions to improve Wi-Fi signal quality at home. It also highlights the importance of understanding and managing home network infrastructure to maximize Wi-Fi usage efficiency. By strategically placing routers and employing additional network hardware, users can ensure a stable and fast internet connection throughout their home, enhancing the overall user experience and productivity. Research provides valuable insights for homeowners and technology enthusiasts on how to achieve optimal Wi-Fi performance in various home environments.
Computer Network Management Optimization Through Big Data Analysis Using Time Series Analysis Method Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Huda, Moh Abroril; Hasbullah, Hasbullah; Rohman, Abd
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4373

Abstract

Efficient management of computer networks is becoming increasingly important in the ever-evolving digital age. With the ever-increasing volume of data in the network environment, sophisticated approaches are needed to analyse and optimise network performance. One promising approach is the use of big data analysis with time series analysis methods. In this context, this research aims to explore the potential application of big data analysis using the time series analysis method in computer network management. By combining the power of big data analysis with time series analysis methodology. One of the main applications of  big data analysis in computer networks is security threat detection. By analysing unusual traffic patterns or suspicious behaviour, the system can identify potential attacks or data leaks more quickly and efficiently. In addition, big data analytics can also be used to optimise network performance by identifying bottlenecks, predicting capacity requirements, and improving the efficiency of resource usage by utilising big data analytics in the context of computer networks. However, challenges related to data privacy and security remain a major concern that must be addressed in the application of this technology. Therefore, it is important to develop a framework that takes into account the security and privacy aspects of data throughout the big data analysis process. Through this research, it is hoped that innovative solutions to the challenges of managing complex computer networks in the evolving digital era can be found, as well as provide a solid foundation for further research in this field.
4G LTE Network Performance Analysis Provider 3 In Pamekasan Using The G-Nettrack Application Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Mahendra, Mahendra; Surur, Miftahus; Rizki, Abdulloh
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4376

Abstract

This research evaluates the performance of 4G LTE Provider 3 network services in Pamekasan City using the drive test method using the G-NetTrack application. The goal is to understand network performance in providing high-quality internet access in the ever-evolving digital era. This research is important because people's needs for fast and reliable internet access are increasing, especially in cities with high population density such as Pamekasan. Field measurement results show that Provider 3's 4G LTE network has good service quality with stable download and upload speeds and adequate signal strength. Drive tests were conducted by driving along predetermined routes while recording data on signal strength, internet speed, latency, and other relevant parameters. The data collected from each location was analyzed to compare the performance of various service providers. This analysis provides a comprehensive picture of network performance and can be used to provide recommendations to both consumers and other concerned parties. The conclusion of this study includes an evaluation of the performance of each provider based on the drive test results, as well as providing recommendations for future service improvements. The results of this study provide useful insights to understand and improve user experience in telecommunication connectivity in Pamekasan City, and can be used to improve user experience.
Netvista Public Wireless Network Quality Analysis Using Quality Of Service Parameters Putra, Fauzan Prasetyo Eka; Ubaidi, Ubaidi; Mayangsari, Dwi; Hasanah, Nor
Brilliance: Research of Artificial Intelligence Vol. 4 No. 1 (2024): Brilliance: Research of Artificial Intelligence, Article Research May 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i1.4388

Abstract

The use of public wireless networks is increasingly used by the public because it is able to touch all walks of life using the internet because of its affordable prices. Apart from the affordable price, the ease of accessing this network so that many people prefer to take advantage of public wifi. However, with the increasing number of network users, of course, it will affect the quality of the network. Based on these problems, the researcher decided to conduct a study to analyze the quality of the public wireless network from NETVISTA. The NETVISTA public wireless network can be accessed in Kangenan Gg. 1, so the researcher decided to conduct research at the location for 2 days. This study aims to determine the quality of the internet connection network based on QoS parameters by knowing the delay, throughput, and packet loss obtained from the axence nettols application which will later be compared with the TYPHON standard so that the quality of the NETVISTA public wireless network can be known. The method used in this study is descriptive analysis. From this study, the results were obtained that many users (category: "Busy") the quality of Netvista's public wireless network was less satisfactory or at point 2.6, while when there were few users (category: "Not Busy") the quality of Netvista's wireless network was satisfactory or at point 3.1. The best time on holidays is between 11.00-12.00 and 22.01-00.00, while the best time on active days is 04.01-10.59 and 12.01-16.00.
POS Tagging Bahasa Madura dengan Menggunakan Algoritma Brill Tagger Dewi, Nindian Puspa; Ubaidi, Ubaidi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020722449

Abstract

Bahasa Madura adalah bahasa daerah yang selain digunakan di Pulau Madura juga digunakan di daerah lainnya seperti di kota Jember, Pasuruan, dan Probolinggo. Sebagai bahasa daerah, Bahasa Madura mulai banyak ditinggalkan khususnya di kalangan anak muda. Beberapa penyebabnya adalah adanya rasa gengsi dan tingkat kesulitan untuk mempelajari Bahasa Madura yang memiliki ragam dialek dan tingkat bahasa. Berkurangnya penggunaan Bahasa Madura dapat mengakibatkan punahnya Bahasa Madura sebagai salah satu bahasa daerah yang ada di Indonesia. Oleh karena itu, perlu adanya usaha untuk mempertahankan dan memelihara Bahasa Madura. Salah satunya adalah dengan melakukan penelitian tentang Bahasa Madura dalam bidang Natural Language Processing sehingga kedepannya pembelajaran tentang Bahasa Madura dapat dilakukan melalui media digital. Part Of Speech (POS) Tagging adalah dasar penelitian text processing, sehingga perlu untuk dibuat aplikasi POS Tagging Bahasa Madura untuk digunakan pada penelitian Natural Languange Processing lainnya. Dalam penelitian ini, POS Tagging dibuat dengan menggunakan Algoritma Brill Tagger dengan menggunakan corpus yang berisi 10.535 kata Bahasa Madura. POS Tagging dengan Brill Tagger dapat memberikan kelas kata yang sesuai pada kata dengan menggunakan aturan leksikal dan kontekstual.  Brill Tagger merupakan algoritma dengan tingkat akurasi yang paling baik saat diterapkan dalam Bahasa Inggris, Bahasa Indonesia dan beberapa bahasa lainnya. Dari serangkaian percobaan dengan beberapa perubahan nilai threshold tanpa memperhatikan OOV (Out Of Vocabulary), menunjukkan rata-rata akurasi mencapai lebih dari 80% dengan akurasi tertinggi mencapai 86.67% dan untuk pengujian dengan memperhatikan OOV mencapai rata-rata akurasi 67.74%. Jadi dapat disimpulkan bahwa Brill Tagger dapat digunakan untuk Bahasa Madura dengan tingkat akurasi yang baik. Abstract Bahasa Madura is regional language which is not only used on Madura Island but is also used in other areas such as in several regions in Jember, Pasuruan, and Probolinggo. Today, Bahasa Madura began to be abandoned, especially among young people. One reason is sense of pride and also quite difficult to learn Bahasa Madura because it has a variety of dialects and language levels. The reduced use of Bahasa Madura can lead to the extinction of Bahasa Madura as one of the regional languages in Indonesia. Therefore, there needs to be an effort to maintain Madurese Language. One of them is by conducting research on Madurese Language in the field of Natural Language Processing so that in the future learning about Madurese can be done through digital media. Part of Speech (POS) Tagging is the basis of text processing research, so the Madura Language POS Tagging application needs to be made for use in other Natural Language Processing research. This study uses Brill Tagger by using a corpus containing 10,535 words. POS Tagging with Brill Tagger Algorithm can provide the appropriate word class to word using lexical and contextual rule. The reason for using Brill Tagger is because it is the algorithm that has the best accuracy when implemented in English, Indonesian and several other languages. The experimental results with Brill Tagger show that the average accuracy without OOV (Out Of Vocabulary) obtained is 86.6% with the highest accuracy of 86.94% and the average accuracy for OOV words reached 67.22%. So it can be concluded that the Brill Tagger Algorithm can also be used for Bahasa Madura with a good degree of accuracy.
Penerapan Hidden Markov Model (HMM) dan Mel-Frequency Cesptral Coefficients (MFCC) pada E-Learning Bahasa Madura untuk Anak Usia Dini Ubaidi, Ubaidi; Dewi, Nindian Puspa
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020722477

Abstract

Bahasa Madura is a regional language used in Madura island. This language has many variations of pronunciation and dialect that makes it not easy to learn, even by the local people especially children. There hasn’t been any interesting learning media to learn Bahasa Madura so far. In fact, a fun learning activity is needed to help children to enhance their ability in pronouncing animals’ names, numbers, fruits and things in Bahasa Madura. Thus, it’s considered important to create Bahasa Madura e-learning by implementing the recognition of voice patterns in order to make it easier for the children to learn Bahasa Madura which has several variations of pronunciation only for one single object. This Bahasa Madura e-learning application for young learners is used to introduce Bahasa Madura vocabularies by recognizing the voice pattern recordings which have been processed through MFCC technique as the extracted voice features and HMM as the learning techniques. The implementation of MFCC and HMM as the learning tool to introduce the pronunciation of regional language vocabularies especially Bahasa Madura has never been done before. Therefore, this research is expected to help the young learners to be able to pronounce Bahasa Madura vocabularies properly.  In this study, a number of young learners’ voices were recorded and were set as the trial data. Only the proper voice data that were used—voice data that were considered to be pronounced correctly. The trial method was done through one-single model and multi-model. After doing several simultaneous trials, the result showed the accuracy level. The average accuracy level for one-single model system was 73% (with the highest accuracy reached 75%) and the average accuracy level for multi-model system was 80% (with the highest accuracy reached 81%).
Co-Authors Abd Rohman, Abd Abd. Wahab Syahroni Aini, Septi Dariyatul Alim, Royfal Amir Hamzah Arifin, Mohammad Nazir Aziz, Mohammad Barokah, Selviana Nur Rizqi Dewi, Nindian Puspa Dwi Mayangsari Efendi, Reynal Widya Efendy, Satrio Ananta Fauzan Prasetyo Haris, Farras Maulana Hasbullah Hasbullah Huda, Moh Abroril Imron Mawardi Irfan, Moh. Irwan Darmawan Ismail Moadz, Ulin Najah Jannah, Ukhti Raudhatul Kusuma, R. Okky Firmansyah Laily, Nurhikmatul Mahendra, Mahendra Maulidia, Siti Nur Miftahus Surur, Miftahus Nindian Puspa Dewi Nor Hasanah Nuraini, Alief Pramadi, Walid Agel Prasetya, Andhis Yoga Puspa Dewi, Nindian Putra , Fauzan Prasetyo Eka Ramadhani, Nilam Rizki, Abdulloh Rosyidi, Luthfi Said, Badar Saputra, Rama Nurja Syafitri, Andriati Aziizah Syam, Abd Mu’iz Tamam, Alief Badrit Zakaria, Nor Balkish