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LP3M Universitas Mulia Jl. Letjen Z.A. Maulani No. 9 Kelurahan Damai Bahagia Kecamatan Balikpapan Selatan Kota Balikpapan Provinsi Kalimantan Timur Indonesia
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METIK JURNAL
Published by Universitas Mulia
ISSN : 24429562     EISSN : 25801503     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering
Media Teknologi Informasi dan Komputer (METIK) Jurnal adalah jurnal teknologi dan informasi nasional berisi artikel-artikel ilmiah yang meliputi bidang-bidang: sistem informasi, informatika, multimedia, jaringan serta penelitian-penelitian lain yang terkait dengan bidang-bidang tersebut. Terbit dua kali dalam setahun bulan Juni dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 243 Documents
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Analisis DistilBERT dengan Support Vector Machine (SVM) untuk Klasifikasi Ujaran Kebencian pada Sosial Media Twitter Azmi Verdikha, Naufal; Habid, Reza; Johar Latipah, Asslia
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.583

Abstract

Hate speech is a significant issue in content management on social media platforms. Effective classification of hate speech plays a crucial role in maintaining a safe social media environment, combating discrimination, and protecting users. This study evaluates a hate speech classification model using SVM with linear and polynomial kernels. The dataset used consists of labeled Indonesian-language tweets. The importance of developing an effective classification model to address hate speech has led to the utilization of DistilBERT as a feature extraction method. However, DistilBERT has high-dimensional features, necessitating dimensionality reduction to reduce model complexity. Therefore, in this study, the PCA dimensionality reduction method is implemented with various scenarios of dimensionality, namely 10, 20, 30, 40, and 50. Evaluation is performed using F1-Score, and the entire study is evaluated using 10-fold cross-validation. The evaluation results indicate that in the scenario with a linear kernel, the model achieves the highest F1-Score of 0.75 in the 50-dimensional scenario. Meanwhile, in the scenario with a polynomial kernel, the model achieves the highest F1-Score of 0.7857 in the 50-dimensional scenario. These findings demonstrate that the use of a polynomial kernel with 50 dimensions yields the best performance in classifying hate speech.
Implementasi Algoritma K-Means Untuk Mengelompokkan Mahasiswa Program Studi Pendidikan Matematika Berdasarkan Sumber Belajarnya Rizki, Nanda Arista; Kurniawan, Kurniawan; Hasan, Isran K.; Sampe, Nofia
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.584

Abstract

Students must be able to utilize learning resources properly to improve academic achievement. Students can be grouped based on the learning resources they use frequently. Grouping results are helpful for lecturers in designing, evaluating, and analyzing learning in the classroom. This research aimed to implement the K-Means algorithm to classify student learning resources and determine which learning resources determine which groups. The population of this research were students of the Mathematics Education study program at Mulawarman University who are still taking courses. At the same time, the sample were active students from classes 2019, 2020, 2021, and 2022 of the Mathematics Education Study Program at Universitas Mulawarman who were still taking courses and were willing to fill out the questionnaire, namely as many as 111 Students. The data analysis used was clustering analysis using the K-Means algorithm with the Elbow method. New dummy data was formed from learning resource data because it was multiple choice. Based on the results, three main groups were obtained according to the use of learning resources. The learning resources that determine the distribution of groups were electronic books and journals. The first group used electronic books and journals, while the third group did not use either. While the second group only used electronic books. The Silhouette value for this cluster model was 0.615. The classification was classified as good.
Analisis Perbandingan Metode Decision Tree Dan K-Nearest Neighbor Untuk Klasifikasi Cyberbullying Pada Sosial Media Twitter Maradona, Maradona; Kusrini, Kusrini; Alva Hendi Muhammad
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.591

Abstract

This research focuses on analyzing the impact of social media on society, particularly addressing the issue of cyberbullying on the Twitter platform. Based on statistics, the majority of internet users in Indonesia actively utilize social networks, with Twitter being the most dominant platform used for communication and interaction. Therefore, cyberbullying cases often occur on this social media platform. In this study, two classification methods, namely Decision Tree and K-Nearest Neighbor (KNN), were employed to classify cyberbullying-related messages on Twitter. The aim of this research is to compare the performance of these two methods and to identify early signs of cyberbullying as relevant digital evidence for legal proceedings. The dataset used in this study consists of 650 comment records from the period 2019 to 2021, with predefined labels. The analysis results indicate that K-Nearest Neighbor achieved the highest accuracy, reaching 75.99%, compared to Decision Tree with 65.00%. Hence, K-Nearest Neighbor is considered a more effective method for cyberbullying analysis on the Twitter platform. Additionally, the identification of early signs of cyberbullying in comment id 2 can serve as relevant digital evidence for legal purposes. This research provides better insights into the effectiveness of classification in addressing cyberbullying issues on the Twitter platform.
Implementasi Framework Streamlit Sebagai Prediksi Harga Jual Rumah Dengan Linear Regresi Syafarina, Gita Ayu; Zaenuddin, Zaenuddin
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.608

Abstract

This research aims to develop an Artificial Intelligence (AI)-based application using the Streamlit framework to predict house sale prices in Banjarmasin City using Linear Regression methodology. The increase in demand and supply of properties in Banjarmasin City poses a complex challenge in determining house sale prices. The Linear Regression method was chosen as the primary analytical tool to identify factors influencing house sale prices. This application utilizes historical data of house sale prices and variables such as land area, building area, number of rooms, proximity to public facilities, and geographical location as inputs for the Linear Regression model. Furthermore, the Streamlit framework is employed to create an interactive and user-friendly interface for end-users. The outcome of this research is an AI application that assists potential buyers or sellers in Banjarmasin City in determining competitive prices. By inputting information about the property being evaluated, users can obtain a more accurate estimated sale price based on factors identified by the Linear Regression model. In testing the application, actual house sale price data from Banjarmasin City was used to assess the model's accuracy. The testing results indicate that the application is capable of providing reasonably accurate price estimates, achieving an accuracy level of 67.8%. Thus, this AI application holds the potential to be a valuable tool in the property industry in Banjarmasin City, aiding stakeholders in more informed and data-driven decision-making regarding house sale prices. Additionally, this application could serve as a foundation for further developments in AI research and property price analysis.
Analisis Cara Kerja Sistem Deteksi Infeksi Worm Pada Komputer Sumarno, Sumarno
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.636

Abstract

Worms are a type of malware that has the ability to develop and spread automatically to other computers on a network without human interaction. This fast and undetectable infection capability makes worms a serious threat in the world of computer security. This research aims to explore the mechanisms and behavior of worm infection systems on computers. This study involves an in-depth analysis of the functions and methods used by worms to enter, infect, and exploit target computers. This researchalso explain how worms can cause damage to computer systems, steal confidential information, or even create botnet networks to carry out large-scale attacks. Research methods include collecting data from existing worm detection systems, analyzing system logs that occur, as well as simulations to understand how worms work in various scenarios. In addition, this research also consider protection and prevention techniques that can be used to protect computers and networks from worm attacks. Based on observations and experiments, the results of this research can be concluded that the worm infection system spreads through computers connected to the network or through other media on the network and does not require a certain moment to be a trigger to infect the target. It is hoped that the results of this research provide an in-depth understanding of worm infection systems on computers, allowing researchers and computer security practitioners to develop more effective protection strategies. Prevention and early detection efforts will be key in dealing with the growing threat from worms and similar types ofmalware.
Aplikasi Rekomendasi Pemesanan Paket Wisata Menggunakan Metode Collaborative Filltering Ibrahim Asad; Muhhamad Zakariyah
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.639

Abstract

The advancement of information technology has led to the rapid growth of tourism information, causing difficulties for tourists to find relevant information according to their needs. Recommendation systems are one of the solutions to recommend tourist destinations based on user preferences. Tourism has become an industry that provides significant benefits to a region. Therefore, tourist attractions need to be developed to achieve maximum results. There are various impacts of tourism development, one of which is the improvement of the local economy in tourist areas. Yogyakarta is one of the cities with various tourist attractions and is a popular destination for people living in Central Java, specifically. However, the abundance of tourist destinations poses a challenge for tourists in making decisions. Tourism recommendations are made based on various factors, such as ticket prices, the distance of the tourist destination from the user's current location on maps, and facilities. The technique used is Collaborative Filtering (CF). Using this technique can provide accurate recommendations to each user. In this research, the Collaborative Filtering method is used to build a recommendation system by finding similarities among users.
Model Desain Sistem Informasi Pengembangan Pemasaran Hewan Qurban Berbasis Web Magdalena, Hilyah; Septryanti, Ade; Cillia, Cillia
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.662

Abstract

In Pangkalpinang City and its surroundings, people who need sacrificial animals only look for them in their area. However, currently marketing sacrificial animals can also use a web-based system. CV. Ternak Sejahtera developed its marketing system with a web system to reach customers outside Pangkalpinang. The development of this marketing system was carried out using the Rapid Application Development method which is able to accommodate user needs well and repeat the system analysis and design process if there are changes to system requirements. This web-based system is designed so that customers can view sacrificial animals and make transactions online. The system also provides installment payment facilities for customers who purchased long ago. Customers also receive a service to deliver sacrificial animals with the guarantee that the animals are in good health and meet the requirements for sacrificial animals.
Penerapan Data Mining Dalam Menganalisis Pola Belanja Konsumen Menggunakan Market Basket Analysis Sarifmata Purnomo; Heny Pratiwi; Sa'ad, Muhammad Ibnu
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.678

Abstract

Currently, almost every activity is related to data. in the business sector, daily sales transaction data stored in the database system will always increase and accumulate. The existing data is only used as an archive by the shop owner so that it has an impact on sales strategies that are not implemented well, even though the existing data can be processed into information to determine the layout of goods so that it has an impact on increasing the occurrence of impulse buying, increasing or maintaining turnover, and minimizing product waste. accumulate until it expires which can be detrimental to the shop.The aim of this research is to find consumer shopping patterns using Marker Basket Analysis. This research method is called market basket analysis or also called association rules, which is a data mining technique for finding patterns that often appear simultaneously in transaction data, so that it can be used as a method for finding information about what kinds of goods are frequently used. purchased by consumers simultaneously. The results of this research, based on data analysis using the Rapidminer application, found 25 associative relationships or rules with a lift ratio value of more than 1, these rules become a reference in determining the layout of goods. Providing recommendations for layout changes aims to make it easier for consumers to shop, increase the possibility of impulse buying by consumers, and maximize product display, thereby reducing the accumulation of goods in the Purnama Store Warehouse.
Perancangan Desain UI/UX Sistem Informasi Pengarsipan Surat Menggunakan Metode User Centered Design Titania , Dea Arius; Kurniawati, Laela; Haryanti, Tuti
METIK JURNAL (AKREDITASI SINTA 3) Vol. 8 No. 1 (2024): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v8i1.686

Abstract

Advances in technology have now spread to all aspects of life and profession. When archiving, it is appropriate to use a computerized system to make archiving and processing letters easier. However, there are still few who take advantage of current technological advances. One of them is the TEXMACO PURWASARI Vocational High School which still archives letters in paper form (hard copy). Manual archiving has weaknesses that pose many risks. By designing the UI/UX of an archival information system, it is hoped that it can solve existing problems. In designing the UI/UX, the user center design (UCD) method is applied, which is a method for analyzing the UI/UX design of an electronic archival information system. seen from the system user's side, so that the system design is designed according to the user's needs, the result of this research is an archival information system design plan which is equipped with a database plan that is tailored to the user's needs, then testing the system design that has been created using the system method usability scale (SUS).
Usability Testing Pada Aplikasi Undiknas Mobile Menggunakan Metode System Usability Scale Ngurah Darma Paramartha, I Gusti; I Putu Widia Prasetia; Kadek Kusuma Wardana
METIK JURNAL (AKREDITASI SINTA 3) Vol. 8 No. 1 (2024): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v8i1.735

Abstract

Universitas Pendidikan Nasional (Undiknas) Denpasar menjadi salah satu perguruan tinggi swasta di Bali yang memahami pentingnya digital dalam proses belajar mengajar saat ini adalah. Penerapan teknlogi informasi di Undiknas Denpasar telah mentransformasikan pembelajaran dari model tradisional konvensional menjadi digital. Undiknas telah menghadirkan aplikasi Undiknas Mobile memiliki tujuan untuk mempermudah mahasiswa dalam melakukan kegiatan akademik dan non- akademik di kampus. Untuk menjaga pengguna dan eksistensi dari sebuah aplikasi, maka salah satu hal yang harus diperhatikan adalah kepuasan pengguna dalam menggunakan aplikasi tersebut. Penelitian ini bertujuan mengetahui tingkat kepuasan dari aplikasi Undiknas Mobile menggunakan metode System Usability Scale (SUS). Untuk melakukan pengujian tersebut, penelitian in menggunakan metode deskriptif dan survei dengan melakukan penyebaran kuesoner kepada 20 mahasiswa aktif yang ada di Kampus Undiknas. Hasil uji coba penggunaan metode SUS pada penelitian ini menghasilkan skor dengan rata-rata sebesar 84,5 yang termasuk ke dalam Acceptability Ranges ‘ACCEPTABLE’. Jika diartikan, bahwa aplikasi Undiknas Mobile Admission Ganesha dapat digolongkan diterima oleh user dengan Grade Scale ‘B’ dan pada Adjective Ratings dikategorikan ‘Excellent.

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