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All Journal Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Education Enthusiast : Jurnal Pendidikan dan Keguruan Bulletin of Information Technology (BIT) Jurnal Pengabdian Masyarakat Gemilang (JPMG) Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Masyarakat: Jurnal Pengabdian TECHNOLOGIC
Aulia, Ananda
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Journal : bulletin of information technology bit

 1 
Implementasi Algoritma Naïve Bayes Dalam Menganalisis Jumlah Live Stream VTuber Skem Aulia, Ananda; Tanjung, Miftah Rusydi; Iqbal, Muhammad; Wijaya, Rian Farta
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.899

Abstract

YouTube is evidence of the development of leading digital technology in the media and entertainment sector. YouTuber is a term for those who create content or broadcast live on YouTube media. Not all YouTubers are able to express themselves directly in the content they create. For this reason, Virtual YouTubers were created, which are 2-dimensional or 3-dimensional virtual characters created using computer software to make it easier for YouTubers to interact with viewers. This research aims to analyze the live broadcasts of VTuber HoloH3ro, namely Kaela Kovalskia, Vestia Zeta, and Kobo Kanaeru, which contain schemes during the live streaming. With a large amount of data for each live stream time, a Naïve Bayes algorithm is needed through the use of range and frequency features, so accuracy results will be obtained which will be tested using the Confusion Matrix. The dataset used was taken from the kaggle.com site regarding the scheme live stream schedule conducted by HoloH3ro.
Implementasi Sistem Pendukung Keputusan dalam menentukan Kecamatan Terbaik Menggunakan Algoritma Entropy dan Additive Ratio Assessment (ARAS) Ernawati, Andi; Ofta Sari, Ayu; Sofyan, Siti Nurhaliza; Aulia, Ananda; Sitorus, Zulham; Khairul
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1066

Abstract

In the context of regional development and decision making related to determining the best village, the use of a Decision Support System (DSS) with the application of the Entropy and Additive Ratio Assessment (ARAS) algorithms is a very important approach. The main objective of this research is to propose and implement a method that utilizes the Entropy algorithm to evaluate criteria weights and ARAS to rank villages based on predetermined criteria. This approach begins the process by identifying relevant criteria to determine the best village in an area. Next, the Entropy algorithm is used to measure the level of importance or relative weight of each predetermined criterion. This step helps in assessing how informative each criterion is in the decision-making process regarding determining the best Village. After determining the criteria weights using Entropy, the approach continues with the application of the ARAS method. ARAS is used to rank villages based on normalized values ​​from previously determined criteria. The data normalization process is carried out to ensure the validity of comparisons between villages. The final result of this approach is a ranking of villages indicating the best villages based on the criteria considered. This method was tested in a case study using a dataset involving a number of relevant criteria for assessing village development potential. Experimental results show that the use of the Entropy and ARAS algorithms in the Decision Support System provides an effective and informative framework for decision makers in determining the best Village. In conclusion, this approach provides a solid foundation to support a more effective and precise decision-making process in regional development based on clearly defined criteria.
Application of the C45 Algorithm to Predict Student Academic Scores Ernawati, Andi; Sitorus, Zulham; Aulia, Ananda; Ayu Ofta
Bulletin of Information Technology (BIT) Vol 5 No 2 (2024): Juni 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i2.1251

Abstract

Student grades are the results of teaching and learning activities on a campus. So you can know your target for completing your studies. This research uses the C4.5 Algorithm which can help predict the results of student assessments. The dataset consists of student achievement index, place of residence, discipline, lecturer's role in lectures. From 40 datasets we have obtained a decision on student academic achievement and obtained performance results from accuracy results of 86.36% with class precision predicate Yes=84.62%, No=88.89% and class recall Yes=91.67%, No=80.00%.
Implementation of E-Commerce System as SME Development Strategy in the Digital Era Saputra, Maulian; Susilawati; Nurhaliza Sofyan, Siti; Aulia, Ananda; Ernawati, Andi; Oftasari, Ayu; Farta wijaya, Rian
Bulletin of Information Technology (BIT) Vol 5 No 3: September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i3.1545

Abstract

The implementation of e-commerce systems has become one of the main strategies in the development of Small and Medium Enterprises (SMEs) in the digital era. E-commerce allows SMEs to expand market reach, improve operational efficiency, and strengthen relationships with consumers through better data access. In addition, this digital platform offers benefits such as distribution cost savings, business process automation, and improved customer service. However, challenges in e-commerce adoption for SMEs include limited digital literacy, uneven technology infrastructure, and cybersecurity issues. To achieve the full potential of e-commerce, support from the government and private sector in the form of adequate policies, infrastructure, and training is required. This research aims to identify the benefits, challenges and solutions in implementing e-commerce for SMEs, in order to improve their competitiveness in an increasingly competitive global market.
Analisis Data Mining Dalam Pemilihan Smartphone dan Klasifikasi di Berbagai Perangkat Menggunakan Random Forest Aulia, Ananda; Wahyuni, Sri
Bulletin of Information Technology (BIT) Vol 5 No 4: Desember 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v5i4.1703

Abstract

Abstract− Smartphone technology continues to develop rapidly, driving the need for effective analysis methods to assist users in selecting devices that suit their needs. This research aims to implement data mining using the Random Forest method in the process of selecting smartphones and classifying devices based on their technical specifications. The Random Forest method was chosen because of its reliable ability to handle data with a large number of attributes, produce an accurate classification model, and minimize the risk of overfitting. The dataset used includes technical specifications of various smartphones, such as camera resolution, chipset, RAM capacity, screen resolution, and support for 4K video recording. The research process involved data collection, pre-processing to handle missing values ​​and data transformation, as well as model training using the Random Forest algorithm.  The research results show that the Random Forest method is able to classify devices with high accuracy, helping users determine smartphones that meet their criteria, such as support for 4K video recording and overall performance. Additionally, this research provides insight into the importance of certain attributes in smartphone selection. Thus, implementing data mining using Random Forest can be an effective solution in supporting data-based decision making in the field of consumer technology. Keywords: Data Mining, Random Forest, Smartphone, Classification, Technical Specifications
Co-Authors Andi Ernawati Ayu Ofta Ayu Septiani, Widya Binsamaae, Suhaila Destiniar Destiniar, Destiniar Fahriza Fuadiah, Nyiayu Farta wijaya, Rian Khairul Khairul, K Marhamah Marhamah Misdalina Misdalina Muhammad Iqbal Munirah Nila Kesumawati Nurhaliza Sofyan, Siti Ofta Sari, Ayu Oftasari, Ayu RATNAWATI Rosyidi, Edwar Saputra, Maulian Saputri, Yuni Siregar, Andree Risky Yuliansyah Siti Suwadah Rimang, Siti Suwadah Sitorus, Zulham Sofyan, Siti Nurhaliza Sri Wahyuni Sugeng Santoso Susilawati Syahril Ardi Tanjung, Miftah Rusydi Wijaya, Rian Farta