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Jumanto Jumanto, Jumanto
Faculty of Humanities, Dian Nuswantoro University
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Journal : Journal of Student Research Exploration

 1 
Analysis of quality of service (QoS) wi-fi network in UNNES digital center building using wireshark Rianto, Nur Aziz Kurnia; Salsabila, Halimah; Jumanto, Jumanto
Journal of Student Research Exploration Vol. 1 No. 1: January 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v1i1.108

Abstract

The need for the internet is a very absolute target in today's all-digital era. The traffic of information that is so dense and always dynamic every second makes everyone want speed in capturing information circulating. The speed in gathering information in this all-digital era cannot be separated from the internet and networks. UNNES Digital Center is one of the facilities owned by Semarang State University which is used as a digital-based learning center to support the realization of the Smart Digital Campus. The availability of qualified network services at the UNNES Digital Center is needed to support the all-digital-based student learning process. This research was done to find out how fast and good the quality of the internet network provided by the UNNES Digital Center is. In the research conducted, the network analysis step uses the Quality of Service (QoS) method. In obtaining research data that will be used as a basis for analyzing throughput, packet loss, delay, and network jitter, Wireshark software is used as a tool. The research results show that the quality of the Digital Center's internet network is very good and very adequate for digital learning activities. This is evidenced by a network throughput value of 6122.37 /kbits/s, a packet loss value of 0.7%, a delay of 214 ms with a moderate or quite good value and jitter = 0.511 ms.
Increased accuracy in predicting student academic performance using random forest classifier Mulyana, Aditya Fajar; Puspita, Wiyanda; Jumanto, Jumanto
Journal of Student Research Exploration Vol. 1 No. 2: July 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v1i2.169

Abstract

This research aims to classify the academic performance of students who are successful and who have dropped out of school with high accuracy so that these matters can be addressed quickly. Things like this need fast handling to find out what factors influence it. In addition, this research was conducted to test how good the random forest algorithm is in classifying a problem. Random forest, which includes an algorithm that is commonly used for classifying a problem. By using the random forest algorithm, the accuracy results will be better than a single decision tree. This algorithm is quite good at handling and managing large datasets. From this study it can be concluded that this method can provide good prediction accuracy with a fairly high level of accuracy, namely 89%. Utilization of this random forest can be an alternative in classifying student academic achievement. This algorithm can work well in handling large datasets. This study discusses how the use of Random Forest can work to classify students' academic performance.
Analysis of k-means clustering algorithm in advanced country clustering using rapid miner Prabaswara, Ireneus; Pertiwi, Dwika Ananda Agustina; Jumanto, Jumanto
Journal of Student Research Exploration Vol. 2 No. 2: July 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v2i2.337

Abstract

In the era of globalization, the understanding of developed countries is no longer limited to the level of per capita income alone. As part of the analysis of developed countries based on aspects of government revenue, income balance, national savings, and domestic output based on sales. This research aims to cluster and to find out how these economic indicators are interrelated and affect the status of a country as a developed country. The K-means algorithm is used to identify patterns of countries with similar economic characteristics. From the research conducted, there are 4 clusters generated based on the characteristics of developed countries.
Sentiment analysis of youtube comments on the palestine-israel conflict: Performance comparison of SVM, KNN, and RFC Lintang, Irendra; Jumanto, Jumanto; Masa, Amin Padmo Azam
Journal of Student Research Exploration Vol. 3 No. 1 (2025): January 2025
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/josre.v3i1.426

Abstract

The Palestine-Israel conflict, rooted in territorial and religious identity disputes in the Middle East, notably over the sanctity of Jerusalem, is impacted by various political, economic, and social factors. This study employs text-mining techniques to analyze the sentiment of YouTube comments concerning the conflict. Utilizing data collected via the YouTube API, the study preprocesses, analyzes sentiment, and classifies comments using three machine learning algorithms: K-Nearest Neighbors (K-NN), Random Forest Classifier (RFC), and Support Vector Machine (SVM). The categorization report measures are utilized to compare how well the models performed in classifying estimation as positive or negative. Outflanking all other classifiers, the Irregular Woodland Classifier (RFC) accomplishes 78curacy with accuracy rates of 0.76 for positive and 0.79 for negative assumptions. With a precision rate of 77%, SVM illustrates an inclination in favor of negative sentiments, though K-NN, with an exactness rate of 60%, shows an imbalance favoring negative over positive estimations.
Co-Authors Ade Parlaungan Nasution, Ade Parlaungan Adi, Yogi Kuncoro Agus Harjoko Agustiani, Agustiani Al Hakim, M. Faris Alabid, Noralhuda N. Alamsyah - Anggit Grahito Wicaksono Apsari, Fitri Noor Ari Widodo Ascarya, Farrel Aulia, Muhammad Kahfi Aurelia, Bening Febri Badriyah, Fitria Nurul Budi Prasetiyo, Budi Cahyani, Yesy Tri Chairunnisa, Tsania Damayanti, Dela Rista Dewi, Meilina Taffana Dullah, Ahmad Ubai Dwi Anggraeni Dwi Eko Waluyo DWI HAPSORO Ema Butsi Prihastari Ratna Widyaningrum, Ema Butsi Prihastari Endang Sugiharti, Endang Faizal Risdianto Fatahillah, Dimas Ferdiansyah, Dicky Feri Faila Sufa, Feri Faila HAJRIAL ASWIDINNOOR Hakim, M. Faris Al Hanafi Handayani, Sri Haryati Sulistyorini Hendra Kurniawan Herlina Kurniawati Hidayat Hidayat Ilham Maulana Irmade, Oka Jati, Ismail Wahyu Khalifah, Viera Nur Khoirunnisa, Avicenia Nasywa KOSUKE MIZUNO, KOSUKE KURNIATI, SRI AYU Kurniawaty Iskandar Kusuma, Novelia Salsa Dara Lestari, Apri Dwi Ligia, Emila Lintang, Irendra Luh Titi Handayani, Luh Titi Lutfiyah, Nur Indah Sulistyowati Machfudz, Machfudz Mardiansyah, M Fadil Marshanda, Putri Martha Yohana Sinaga Masa, Amin Padmo Azam Mellisa, Mellisa Minghat, Asnul Dahar Bin Much Aziz Muslim Mukarom, Rosyid Fadhil Al Mulyana, Aditya Fajar Mulyaningtyas, Lintang Ayu Murtafiah, Eni Muzayanah, Rini Nikmah, Tiara Lailatul Nina Fitriani, Nina Ningsih, Maylinna Rahayu Nugraha, Faizal Widya NUGROHO, MUHAMMAD IRFAN Pertiwi, Dwika Ananda Agustina Prabaswara, Ireneus Prabowo Yudo Jayanto Pratama, Rizka Nur Prihatsari, Ema Butsi Puji Purwatiningsih, Aris Pulung Nurtantio Andono Puspita, Wiyanda Putri, Chindi Dwi Ayu Prabowo Putri, Salma Aprilia Huda Raden Arief Nugroho Rahayu, Emik Rahmanti Asmarani Ramadhan, Taufiq Brahmantyo Lintang ramayanti, ismarita Rawat, Bibek Rianto, Nur Aziz Kurnia Riza Arifudin Rizkasari, Elinda Rofik Rofik, Rofik RUSMILAH SUSENO Sa'ud, Udin Syaefudin Sagimin, Eka Margianti Salsabila, Halimah Sam’an, Muhammad Sarafuddin, Sarafuddin Sinaga, Markus Soehendro, Eunike Imanuela Subhan Subhan Subrata, Monika Rosalia Sudarsono Sugiaryo, Sugiaryo Surajaya, I Ketut Syamsu Rizal, Sarif Tanzilal Mustaqim Wahyu Sopandi Wibowo, Kevyn Aalifian Hernanda Wibowo, Kevyn Alifian Hernanda Wicaksono, Suntoro Widiaswara, R. Anantama Widyasari, Alma Wijaya, Dandi Indra Yahya Nur Ifriza Yosza Dasril Yulianingsih, Ratri Zaaidatunni'mah, Untsa