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All Journal EGALITA JURIKOM (Jurnal Riset Komputer) Infotekmesin Journal of Innovation Information Technology and Application (JINITA) Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Journal of English Language and Education UNNES International Conference on ELTLT Pengabdian Jurnal Abdimas ⁠International Journal of Sustainable Social Culture, Science Technology, Management, and Law Humanities
Sari, Laura
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Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mechanical Engineering Social Sciences Other

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Journal : Infotekmesin

 1 
Perbandingan Pendekatan Machine Learning untuk Mendeteksi Serangan DDoS pada Jaringan Komputer Sari, Laura; Faiz, Muhammad Nur; Muhammad, Arif Wirawan
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2556

Abstract

Distributed Denial of Service (DDoS) attacks are a serious threat to computer network security. This study offers a comprehensive evaluation by considering accuracy, detection time, and model complexity in simulation scenarios. Using the CICDDoS2019 dataset, which includes modern attack variations and complete features, this research compares the effectiveness of Naïve Bayes (NB), Random Forest (RF), and Decision Tree (DT) algorithms in detecting DDoS attacks. The results show that RF achieves the highest accuracy (99.95%), while DT excels in recall (99.83%). These findings provide a foundation for developing hybrid ML-DL models to enhance real-time attack detection. However, limitations such as using a single dataset and offline simulations restrict the generalizability of results to real-world network conditions. This study highlights opportunities for more comprehensive future research in real-world scenarios.
Implementasi Metode Research and Development Pada Pengembangan Pembelajaran Matematika Berbasis Multimedia Perdana Wanti, Linda; Sari, Laura
Infotekmesin Vol 12 No 1 (2021): Infotekmesin: Januari 2021
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v12i1.279

Abstract

Mathematics is a lesson that is still a frightening specter for some students. There are several methods used to make mathematics fun to learn. One of them is to package material in mathematics to be more attractive and interesting, especially for children this can make them become interested in learning mathematics. The developed using research and development methods. This method begins by exploring the problem, collecting data needed, designing the product to be developed, validating the product design, testing the use of the system to be developed, revising the product, testing the product, revising the product and product design if there are errors or deficiencies and the last is mass production of product. This research aims to develop an interactive multimedia-based mathematics learning which can later be optimized to increase student interest in learning mathematics and be used to improve the quality of education.
Sistem Pakar Deteksi Dini Penyakit Preeklamsia pada Ibu Hamil Menggunakan Metode Certainty Factor Adi Prasetya, Nur Wachid; Perdana Wanti, Linda; Sari, Laura; Puspitasari, Lina
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.1050

Abstract

Preeclampsia is a disease in pregnant women characterized by high blood pressure and positive urine protein. The disease has a high risk of maternal and fetal death, so there is a need for early detection of mothers at risk of preeclampsia. Early online detection of preeclampsia is the best solution during the Covid-19 pandemic by analyzing the influencing factors. The purpose of this study is to build an expert system for early detection of preeclampsia in pregnant women using the Certainty Factor method and the waterfall system development model in order to provide the possibility of pregnant women suffering from preeclampsia. Testing the accuracy of 30 medical record data for pregnant women resulted in a system accuracy level of 90%, while usability testing resulted in a user satisfaction level of 55 with the System Usability Testing (SUS) score criteria being "Poor", therefore improvements are needed on expert system in the future.
Penerapan Data Mining dalam Analisis Prediksi Kanker Paru Menggunakan Algoritma Random Forest Sari, Laura; Romadloni, Annisa; Listyaningrum, Rostika
Infotekmesin Vol 14 No 1 (2023): Infotekmesin: Januari, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i1.1751

Abstract

Cancer is the second highest cause of death in the world. In Indonesia, it is a disease with a high mortality rate. Most patients do not realize that they have lung cancer thus the treatment is sometimes too late. A prediction method with a high degree of accuracy is needed to detect lung cancer earlier. Previous research used data mining calcification methods with the Naïve Bayes algorithm to predict lung cancer. This research resulted in high recall values for the positive class (Yes class) but low for the negative class (No class). This research was made using the Random Forest algorithm which is known to have good performance. The modeling is optimized by applying the K-fold Cross Validation technique. The Random Forest algorithm produces a higher Accuracy value than the Naïve Bayes algorithm, which is 98.4%. This algorithm produces 100% Recall for the positive class, 80% for the negative class and provides a 100% correct prediction as can be seen from the AUC value of 1. Although a statistical test with a significance level of 5% shows the results of the two algorithms are not significantly different.
Metode Fuzzy Time Series Markov Chain Untuk Peramalan Curah Hujan Harian Sari, Laura; Romadloni, Annisa; Listyaningrum, Rostika; Hazrina, Fadhilla; Rahadi, Nur Wahyu
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.2182

Abstract

Cilacap Regency has diverse topography and geographical conditions which cause this region to have rainfall that varies spatially and temporally; therefore, a forecasting method to overcome these uncertainties and fluctuations is needed. Fuzzy Time Series Markov Chain utilizes Fuzzy logic which provides flexibility in handling uncertain and unstructured data. Moreover, the addition of Markov chain elements that utilize Fuzzy logic concepts provides flexibility in handling data allowing the model to capture inter-time relationships and changes in system state that depend on previous states. Therefore, the research aims to see the suitability of the Fuzzy Time Series Markov Chain for predicting daily rainfall in Cilacap Regency. The method is suitable for predicting rainfall data for Cilacap Regency. The accuracy value in this study can be seen from the RMSE and SMAPE values ​​on the training data (in-sample), respectively, which are 58.76469 and 0.7227493. Meanwhile, the testing data (out sample) was 56.01818 and 0.7055117.
Perbandingan Pendekatan Machine Learning untuk Mendeteksi Serangan DDoS pada Jaringan Komputer Faiz, Muhammad Nur; Muhammad, Arif Wirawan; Sari, Laura
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2556

Abstract

Distributed Denial of Service (DDoS) attacks are a serious threat to computer network security. This study offers a comprehensive evaluation by considering accuracy, detection time, and model complexity in simulation scenarios. Using the CICDDoS2019 dataset, which includes modern attack variations and complete features, this research compares the effectiveness of Naïve Bayes (NB), Random Forest (RF), and Decision Tree (DT) algorithms in detecting DDoS attacks. The results show that RF achieves the highest accuracy (99.95%), while DT excels in recall (99.83%). These findings provide a foundation for developing hybrid ML-DL models to enhance real-time attack detection. However, limitations such as using a single dataset and offline simulations restrict the generalizability of results to real-world network conditions. This study highlights opportunities for more comprehensive future research in real-world scenarios.
Kontrol Kecepatan Berbasis PWM (Pulse Width Modulation) Untuk Mesin Pemarut Kelapa Bertenaga Surya Fadhillah Hazrina; Prima Dewi, Riyani; Widianingsih, Betti; Sari, Laura; Zulfahmi Muassar, Mifta
Infotekmesin Vol 16 No 2 (2025): Infotekmesin: Juli 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i2.2794

Abstract

Solar energy is a new renewable energy (EBT) that can be used as an alternative energy source for electricity generation to replace fossil fuels or supplies from the National Electricity Company (PLN). One of its uses can be applied in everyday life in household appliances, namely, coconut grater machines. Coconut grater machines used in the market still use fossil fuels to crush coconut meat, so solar energy is implemented as an alternative energy to operate the coconut grater machine. The use of solar panels in this study is highly dependent on sunlight exposure. In addition, the tilt position of the solar panel can also determine the power generated by the solar panel. The tilt position of the solar panel can be manually adjusted according to the direction of sunlight at certain times. Around midday, sunlight can be captured optimally. At that time, the accumulator/battery will quickly charge, and the coconut grater machine can be used at low or high speeds. The purpose of this study is to implement a PWM (Pulse Width Modulation) system-based control as a motor speed regulator on a coconut grater machine. PWM technology is installed to obtain optimal rotation results and has the potential to save electrical energy. The research results showed that the installed solar panels could produce an average of 4.86 watts of electrical power at 8:00 a.m. WIB and a maximum of 5 watts of electrical power at 12:00 p.m. WIB. Under no-load operating conditions, the current was 0.38 A and the motor speed was 3,724 Rpm. When the engine was tested under load, the speed was 2,926 Rpm.
Co-Authors Annisa Romadloni Arif Wirawan Muhammad Arif Wirawan Muhammad Davito Rasendriya Rizqullah Putra Fadhillah Hazrina Fadlil , Abdul Faiz , Muhammad Nur Hazrina, Fadhilla Imam Riadi Johanna, Anne Listyaningrum, Rostika Maharrani, Ratih Hafsarah Muhammad Nur Faiz, Muhammad Nur Nur Faiz, Muhammad Nur Wachid Adi Prasetya Oman Somantri Perdana Wanti, Linda Prima Dewi, Riyani Purwaningrum, Santi Puspitasari, Lina Rahadi, Nur Wahyu Sukma Aji Supriyono, Abdul Rohman Wanti, Linda Perdana Wati, Linda Perdana Widianingsih, Betti Zulfahmi Muassar, Mifta