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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,170 Documents
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Modified K-Means Clustering with Semi Grouping Perspective : A Study Al Afghani, Said; Chandra, Gerry
The Indonesian Journal of Computer Science Vol. 12 No. 2 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i2.3141

Abstract

In this note, we will provide some results of a literature study related to one of the clustering methods, namely K-Means, but with some modifications, devoted to the case of computation time. Modifications were made at the time of determining the cluster center by previously applying principal component analysis (PCA), other researchers [4] proposed this method first, which differs in this note, namely in the preprocessing of the data before principal component analysis is carried out. Comparison of the accuracy of the cluster results is also given in this note.
Penerapan Metode Winter Exponential Smoothing Dalam Memprediksi Stok Produk Benang Cahyani, Winda; Suendri
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3143

Abstract

Kegiatan untuk memperkirakan apa yang akan terjadi pada masa yang akan datang disebut dengan peramalan. Metode Winter Exponential Smoothing adalah metode peramalan yang menggunakan tiga persamaan pola, yaitu stationer, trend, dan musiman. Teknik peramalan dapat diterapkan dalam memprediksi stok produk benang pada PT. Jangkar Mas di periode selanjutnya. Untuk itu peneliti bermaksud membangun sebuah sistem peramalan agar mempermudah perusahaan dalam memprediksi stok produk benang. Melalui sistem peramalan ini diperoleh data prediksi stok produk benang menggunakan metode winter exponential smoothing dengan menggunakan data jenis benang katun pada bulan Januari 2021 hingga Desember 2022 menghasilkan Mean Absolute Percentage Error (MAPE) sebesar 10% dengan data hasil peramalan benang katun pada Januari 2023 sebanyak 3.390,86 roll masuk pada kategori 10-20% yang artinya hasil peramalan baik, dimana nilai α = 0.4, β = 0.1 dan μ = 0.3 hal ini menunjukkan bahwa peramalan menggunakan metode winter exponential smoothing dapat memberikan hasil sesuai dengan yang diharapkan.
Prediction of Student Scholarship Recipients Using the K-Means Algorithm and C4.5 Wandri, Rizky; Arta, Yudhi; Hanafiah, Anggi; Oktaviaani, Rizka
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3145

Abstract

The government has a program called "KIP Lectures" to assist students in financing education. Where PTS makes the selection manually, with the Data Mining technique, a process will be carried out to speed up the manual process. This research will apply the clustering method with the K-Means algorithm and the classification method with the C4.5 algorithm, as well as a test using the RapidMiner application, which utilizes applicant data in 2022 with a total of 1298 participants. The test results found that 327 participants were in the highest cluster, "cluster_0", then the results of the c4.5 algorithm test obtained a decision tree if the participant has a KIP Card and the value obtained from the "Total Income" Criterion is more than 70 points, then the participant concerned is entitled to scholarship where 317 participants meet the criteria, and the university only has to choose participants from the results obtained in accordance with a predetermined quota.
Voice Assistant Integrated with Chat GPT Shafeeg, Abdulla; Shazhaev, Ilman; Mihaylov, Dimitry; Tularov, Arbi; Shazhaev, Islam
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3146

Abstract

AI has become deeply ingrained in the everyday life. The matter in question does not only touch upon the mobile phones that almost everyone carries within easy reach. Today, voice assistants and smart speakers are mainly used to turn on music, turn off the lights or forecast the weather. AI chatbots are getting smarter. The use of new technologies and the general development of neural networks makes it possible to chat or answer questions, write a script, a scientific work, or program code. One of the key differences from previous GPTs is that the new version is trained to continue the text and answer questions. The answers that the bot gives surprise users around the world. Yes, there are still questions about these answers and their validity, and everyone is sure that technology needs to be improved. For a technology to become revolutionary, it must find a better, new, breakthrough application. Although no, such an application has already been invented. Farcana decided to combine the functionality of the GPT chatbot and a voice assistant. By offering players a new approach to familiarizing themselves with game mechanics and general account management, Farcana promotes its advantages over others and rapidly contributes to AI's overall development in the digital society.
Social Media Advertising: How Do Consumers Respond to Ads on Instagram? Rabbani, Maheswara; Burhan, Angelina Gracia Eddyputri
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v10i2.3149

Abstract

Utilization of social media marketing greatly influences a brand in terms of awareness, the relationship between the organization and consumers, and purchase intention. Therefore this research was conducted to study the interactions that social media users give to image or video advertisements displayed on Instagram. The research model used in this study is descriptive quantitative, by distributing questionnaires to respondents online via Google form. The study uses descriptive statistical analysis to measure the average, frequency distribution, and calculate the value of the distribution in the resulting data. The results of this study indicate that there is an influence on consumer response to advertisements on social media Instagram. This study shows that Instagram is the right choice for one of its marketing strategies because consumers give a good response.
Motivation to Use Gamification Elements in E-Learning for Formal and Non-Formal Education Afirando, Rio; Santoso, Harry Budi; Junus, Kasiyah; Putra, Panca O. Hadi; Lawanto, Oenardi
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3151

Abstract

The implementation of gamification in e-learning is not new, both within the context of formal and informal. Formal education is a learning activity organized by both public and private parties that refers to the official education system of a country. Meanwhile, informal education is another learning activity that does not refer to the official education system of a country. Not only visually appealing, but gamification elements also have a certain motivation and emotional value for the user. This study seeks to compare the use of gamification elements and their motivation between formal and nonformal education. The method used was a Systematic Literature Review using the Kitchenham method. From the selected databases, 65 articles were obtained that had implemented gamification in e-learning. The gamification elements were grouped by motivation and emotion based on the Octalysis framework. The results showed that ownership and possession were the most prominent motivations for implementing gamification.
Instrumental Music Emotion Recognition with MFCC and KNN Algorithm Santoso, Tri Budi; Dutono, Titon
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3152

Abstract

Every piece of music contains emotion in every sound presented. Detection of the music emotion is quite difficult to do because the emotions felt are subjective. Based on this problem, it is necessary to have an automatic classification system to detect the emotions produced in music. In this paper, an explanation of the result to develop an emotional classification system of instrumental music. This system described the process starting with the receiving an input in the form of a music file in the format wav. Furthermore, the feature extraction process is carried out using Mel-Frequency Cepstral Coefficients (MFCC). The result of the extraction of such features are used in the classification process using the K-Nearest Neighbor (K-NN). The system produced output in the form of happy, relaxed, and sad emotions. The output of the system has a classification achieved an accuracy of 97.5% for the value of k = 1, reaching an accuracy of 95% for the value of k = 2.95% and for k = 3, reaching an accuracy of up to 90%.
Analisis Load Balancing Round Robin dan Fault Detection pada Software Defined Network Berbasis P4 Setiawan, Yanto; S, Rizal Cerdas Kurniawan; Mahesa Farosh, Gamel
The Indonesian Journal of Computer Science Vol. 12 No. 2 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i2.3153

Abstract

Tujuan penelitian ialah mengoptimalkan kinerja server pada jaringan Software Defined Network berbasis P4 language dengan menerapkan load balancing round robin. Metode penelitian dibagi menjadi identifikasi masalah, perancangan dan implementasi, pengujian dan analisa. Load balancing adalah mekanisme yang digunakan untuk membagi workload pada beberapa server yang dijalankan dengan tujuan untuk mengoptimalkan resource yang ada, meningkatkan nilai throughput, serta meningkatkan kinerja server agar tidak mendapatkan workload berlebih yang dapat menurukan kualitas layanan. Hasil Penelitian adalah throughput pada implementasi 4 server memiliki nilai rata-rata 632,09Kb/s, 3 server memiliki rata-rata 632,14Kb/s, dan 2 server memiliki rata-rata 632,10Kb/s. Hasil pengukuran request loss pada implementasi 4 server memiliki nilai rata-rata 0%, 3 server memiliki rata-rata 0%, dan 2 server memiliki rata-rata 0%. Hasil pengukuran response time pada implementasi 4 server memiliki nilai rata-rata 3.9ms, 3 server memiliki rata-rata 0,73ms, dan 2 server memiliki rata-rata 0,87ms. Hasil pengukuran fairness index pada implementasi pada server yang diuji memiliki nilai rata-rata 1. Disimpulkan beban kerja pada masing-masing server load balancing round robin dengan fault detection dapat mengoptimalkan kinerja server.
Analisis Sentimen Pengguna Sosial Media Twitter Terhadap Perokok Di Indonesia Dewi Setiyawati; Cahyono, Nuri
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3154

Abstract

One of the tools web users use to access, share, and discuss subjects of interest is social media. One social networking site, Twitter, is often used in real time to communicate this. Due to its significant negative impacts on both health and the economy, smoking is still a topic of regular debate and debate in Indonesia. This research was conducted to assess sentiment towards smokers and differentiate between positive and negative emotions. The data used in this study were obtained by crawling the Twitter social media network. Three Bayes techniques (NB), Support Vector Machine (SVM), and Logistic Regression are used in this study. In this study, 40.25% of Twitter users agreed with the existence of smokers in Indonesia, while 59.74% disagreed. The Naive Bayes method was used in this study, giving the highest accuracy value = 62.1% using 60% training data and 40% test data.
Analisis Topic Modelling Persepsi Pengguna Internet Menggunakan Metode Latent Dirichlet Allocation Angga Reni Dwi Astuti; Cahyono, Nuri
The Indonesian Journal of Computer Science Vol. 12 No. 1 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i1.3155

Abstract

Technological advances have undoubtedly had a major impact on information media. One impact of technological progress is the existence of news media as a source of publik information. There is also regional information, both domestic and foreign, and of course there are various discussions. News data from online news portals can be used as a source of information as a source of research and analysis. Of course, newa portals cover all types of news on various topics. Indentifying frequently discussed topics on news portal will denfinitely take a lot of time. Therefore, this research focuses on applying a topic modelling system to implement a news topic decision system using the Latent Dirichlet Allocation (LDA) method. This research successfully applies the Latent Dirichlet Allocation (LDA) method in determining news topics, of which there are three topic categories that are often discussed on the online news portal detik.com. topic 1 contains natural disaster event, topik 2 contins political figures and issues, topik 3 conttains news about the world cup.

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