Article Per Year (5 Year)
p-Index From 2021 - 2026
1.152
P-Index
This Author published in this journals
All Journal TEKNIK INFORMATIKA Jurnal Informatika Infotronik : Jurnal Teknologi Informasi dan Elektronika Innovation in Research of Informatics (INNOVATICS) Jurnal Abdimas Sang Buana Multifinance Jurnal Isu Teknologi JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Slamet Risnanto
Universitas Sangga Buana
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
IMPLEMENTASI FAILOVER GATEWAY RECURSIVE DAN LOAD BALANCING MENGGUNAKAN METODE PER CONNECTION CLASSIFIER Darmawan, Muhammad Farhan; Risnanto, Slamet
Jurnal Teknologi Informasi dan Elektronika (INFOTRONIK) Vol 8 No 2 (2023): Vol 8 No 2 Tahun 2023
Publisher : Universitas Sangga Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32897/infotronik.2023.8.2.1887

Abstract

Kebutuhan internet pada zaman ini sangat berperan penting. Maka diperlukan koneksi yang sangat stabil untuk menunjang kebutuhan internet yang maksimal. Dengan koneksi jaringan internet satu internet service provider (ISP) saja ternyata masih mengalami performa yang buruk sehingga mengganggu aktivitas kebutuhan internet tersebut dan dibutuhkan solusi agar performa menjadi lebih baik lagi. Salah satu untuk meningkatkan performa jaringan internet diperlukan lebih dari dua ISP yaitu dengan menggunakan failover dan load balancing. Pada penelitian ini mencoba menerapkan failover recursive gateway dan load balancing metode PCC menggunakan mikrotik. Dengan mengamati parameter quality of service (QOS) nilai rata-rata dari throughput, packet loss, delay dan jitter. Hasil diterapkan failover gateway recursive dan load balancing metode PCC adalah failover gateway berhasil membantu di saat koneksi mengalami kendala terputus maka failover bekerja untuk memindahkan koneksi sementara ke ISP lain yang menjadi backup sedangkan load balancing berhasil menyeimbangkan traffic agar stabil pada high traffic. Hasil pengamatan parameter QOS dari kinerja jaringan penelitian ini mendapatkan nilai rata-rata throughput 2750 Kbps, packet loss 0%, delay 2,984, jitter 2.98 dengan mendapatkan indeks 3.75 dan kategori memuaskan dengan hasil sesuai yang diharapkan. 
Comparison of Naïve Bayes and Random Forest Algorithm in Webtoon Application Sentiment Analysis Admojo, Fadhila Tangguh; Risnanto, Slamet; Windiawati, Ai Wulan; Innuddin, Muhammad; Mualfah, Desti
Innovation in Research of Informatics (Innovatics) Vol 6, No 1 (2024): March 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i1.10636

Abstract

The Webtoon application has become one of the popular platforms for reading comics digitally. Webtoons, as a form of digital comics, present various types of comic content. The success of a Webtoon application depends greatly on understanding the preferences and views of its users. User evaluations of Webtoon applications can provide valuable insight into user satisfaction levels, as well as identify problems that need to be fixed by developers. In this research, Sentiment Analysis was applied to user reviews of the Webtoon Application on the Google Play Store. This research uses two different classification algorithms, namely Naïve Bayes and Random Forest, with the aim of comparing their performance in the context of sentiment analysis of user reviews of Webtoon applications. The results of this research are expected to provide an overview of the most suitable algorithm for conducting sentiment analysis classification in Webtoon applications. In collecting the dataset, we involved webtoon user reviews covering various sentiments, such as positive, negative, and neutral. However, in this analysis, the focus is given to two types of sentiment, namely positive and negative. We apply Naïve Bayes and Random Forest algorithms to perform sentiment classification on the reviews. Performance evaluation is carried out by considering metrics such as accuracy, precision, recall, and F1-score. The results of implementing these two algorithms are an accuracy of 74% Naïve Bayes, and 88% Random Forest. It can be concluded that the Random Forest algorithm is superior to the Naïve Bayes algorithm. With this, the Random Forest algorithm becomes a recommendation for classifying sentiment analysis for Webtoon applications with greater accuracy.
BEHAVIORAL FINANCE: THE IMPACT OF HERDING BEHAVIOR ON INVESTMENT DECISIONS: The Case Of Companies Listed In The Lq-45 Index In The Indonesian Stock Exchange (BEI) For The Period 2018-2020 Khalingga, Muhammad Ariq; Galih, Wening; Risnanto, Slamet; Abimanyu, Ketut
Multifinance Vol. 2 No. 2 (2024): Multifinance
Publisher : PT. Altin Riset Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61397/mfc.v2i2.253

Abstract

The purpose of this study is to describe and analyze the effect of herding behavior on investment decisions in companies included in the LQ-45 index of the Indonesia Stock Exchange (IDX) for the period 2018-2022 Research method will use descriptive verification method. To test the hypothesis to determine the influence or causal relationship of the hypothesis that has been proposed. In this study, the verification method is used to determine how much influence herding behavior has on investment decisions.  Findings show the results of hypothesis testing that, the independent variable herding behavior has a positive and significant effect on investment decisions, which means that with the panic of investors over the unclear sources of information and market conditions that will affect portfolio performance or can be said to be informational cascades conditions cause the loss of objectivity of an investor and lead to an irrational attitude so that investment decisions are made by following signals and information owned by other investors who are considered high skilled to be used as a reference for portfolio performance.  Value, according to the test results that have been carried out, the herding behavior variable results in a coefficient value of 1.61 with a significance level of 0.0198 <0.05, and the test results for the Coefficient of Determination in this study, show an RSquare value of 0.081119, meaning that 8.1% of the dependent variable Investment Decision can be explained by the independent variable, namely Herding Behavior. For 91.9% can be explained by other factors outside of Herding Behavior.
Determining Potential Players For The Indonesian Senior National Team In The 2026 World Cup Qualifications Using K-Means Risnanto, Slamet; Alfian, Fikri; Faiz, Moh Imam; Nizar, Moh.; Widarti, Dinny Wahyu
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 3 (2024): October
Publisher : Lumina Infinity Academy Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Football is a very popular sport, and the Indonesian National Team is the pride of the Indonesian people. In an effort to improve team performance, especially in facing the 2026 World Cup qualifiers, optimal player selection is a major challenge. This study applies data mining technology to determine potential players who can strengthen the Indonesian Senior National Team. Player data is taken from the Transfermarkt site which includes attributes such as player market value, club, and league. The methods used include data collection, data cleaning and normalization, and analysis using the K-Means clustering algorithm. The analysis process successfully grouped players into four clusters based on their potential. Players in clusters 1 and 3 have high potential to fill the main lineup, while players in cluster 0 show long-term development prospects. Visualization and manual evaluation support the interpretation of the results for strategic decision making. This study shows that the use of data mining can improve efficiency and accuracy in player selection, providing a more objective data-based approach. However, this study has limitations, such as the lack of consideration of non-technical factors. With the addition of data from other sources and the use of additional algorithms, this method can be further developed to support the performance of the Indonesian National Team optimally in the future.
Optimizing Naïve Bayes Method for Felder-Silverman Learning Style Model Identification Asmi, Hanatyani Nur; Risnanto, Slamet; Mohd, Othman Bin
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i1.40936

Abstract

One important issue in education institusion is the differences in students learning styles, which requires educators to pay attention to individual learning preferences. The manual learning style identification method is considered less effective in terms of time and data accuracy. This study aims to develop a student learning style identification system using the Felder-Silverman model and the Naïve Bayes method, This system is designed to assist lecturers in adjusting learning strategies according to student learning preferences, thus increasing the effectiveness of the learning process. The Naïve Bayes method was applied by analyzing student datasets and determining the accuracy of learning style identification. The validation results showed significant identification accuracy: 85% for the active-reflective dimension, 96% for the sensitive-intuitive dimension, 98% for the verbal-visual dimension, and 91% for the sequential-global dimension. The results of user validation show the effectiveness of the learning style identification application that has been tested based on the percentage value of each statement, and an average percentage value of 85.6% was obtained for all statements, indicating that the system functions well in identifying students' learning styles, while the results of expert validation state that the statements are in accordance with the indicators, the statements use simple and easy-to-understand language, and the identification results are appropriate. This study is expected to contribute to helping universities identify student learning styles efficiently, improve the quality of learning in higher education, and contribute to supporting an inclusive learning approach in higher education environments.
Co-Authors Admojo, Fadhila Tangguh Alfian, Fikri Anita Syafariah Asep Dion Nugraha Asmi, Hanatyani Nur Balango, Andrew Bambang Sugiarto Biller Pandjaitan Cecep Deni Mulyadi Darmawan, Muhammad Farhan Demsi Minar Didi Supardi Dinny Wahyu Widarti Djogo, Ony Djoko Pitoyo Dody Kusmana Faiz, Moh Imam Finny Redjeki Galih, Wening Gunawan Gunawan Gunawansyah Hendajany, Nenny Ivany Syarief Ketut Abimanyu Munastha Khalingga, Muhammad Ariq Komara, Erwan MAXSI ARY Mohd, Othman Bin Mualfah, Desti Muhammad Innuddin Nizar, Moh. Phitsa Mauliana, Phitsa Purwanto, Wisnu R. Didin Kusdian Riffa Haviani Laluma Rodiah Rodiah Roni Tabroni Sanusi, Nunung Solihin, Hanhan Hanafiah Suhanda Suhanda Suharjanta Wisnu Pitara Suharsono, Teguh Nurhadi Tata Zaenal Mutaqin Tia Sugiri Triyani Hayati Wildan Wiguna Windiawati, Ai Wulan Wisnu Wijaya Yushar Kadir