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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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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.
THE INFLUENCE OF GENDER ON SPEAKING ANXIETY IN ENGLISH CLASSES AT POLITEKNIK NEGERI CILACAP: A MIXED-METHODS STUDY AND PEDAGOGICAL IMPLICATIONS Romadloni, Annisa; Sari, Laura; Wati, Linda Perdana
EGALITA Vol 20, No 2 (2025): December (In Press)
Publisher : Pusat Studi Gender UIN Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/egalita.v20i2.35966

Abstract

Abstract Speaking anxiety serves as a significant barrier to oral proficiency in English for Specific Purposes (ESP) courses. Yet, the influence of gender on this affective factor within Indonesian vocational education remains underexplored. This mixed-methods study investigated speaking anxiety patterns at Politeknik Negeri Cilacap. Data were collected from 90 students (45 male, 45 female) using a modified FLCAS questionnaire,written reflections, and classroom observations, complemented by in-depth interviews with twelve selected participants. Although aggregate anxiety scores did not differ significantly between genders, item-level analysis revealed distinct differences. Female students reported significantly higher anxiety when called upon without preparation (cold calls), when fearing negative evaluation, and when speaking before the whole class. At the same time, both genders experienced comparable anxiety levels during formal presentations. Qualitative data confirmed that the fear of making mistakes, sensitivity to lecturer and peer judgment, and a lack of preparation time were the primary drivers of these patterns. Based on these findings, the research advocates for the implementation of gender-responsive scaffolding. Suggested pedagogical strategies include providing structured "think time" before spontaneous questions, utilizing tiered speaking activities that progress from pair discussions to plenary reporting, and cultivating an error-friendly classroom culture. This approach aims to mitigate specific anxiety triggers for female students while building an inclusive environment that prepares all ESP learners for authentic professional communication.  Keywords: Gender; Speaking Anxiety; English for Spesific Purposes; Vocational Education.Abstrak Kecemasan berbicara merupakan hambatan signifikan bagi kemahiran lisan dalam mata kuliah English for Specific Purposes (ESP), namun pengaruh gender terhadap faktor afektif ini dalam pendidikan vokasi di Indonesia masih jarang diteliti. Studi mixed-methods ini menginvestigasi pola kecemasan berbicara di Politeknik Negeri Cilacap. Data dikumpulkan dari 90 mahasiswa (45 laki-laki, 45 perempuan) menggunakan kuesioner FLCAS yang dimodifikasi, refleksi tertulis, dan observasi kelas, dilengkapi dengan wawancara mendalam terhadap dua belas mahasiswa terpilih. Meskipun skor kecemasan agregat tidak berbeda signifikan antar-gender, analisis tingkat butir mengungkapkan perbedaan nyata. Mahasiswa perempuan melaporkan kecemasan yang jauh lebih tinggi saat dipanggil tanpa persiapan (cold calls), saat takut akan evaluasi negatif, dan ketika berbicara di depan seluruh kelas, sementara kedua gender memiliki tingkat kecemasan yang setara dalam presentasi formal. Data kualitatif mengonfirmasi bahwa ketakutan membuat kesalahan, sensitivitas terhadap penilaian dosen dan teman sebaya, serta kurangnya waktu persiapan merupakan pemicu utama pola tersebut. Berdasarkan temuan ini, penelitian merekomendasikan penerapan scaffolding responsif gender. Strategi pedagogis yang disarankan meliputi pemberian "waktu berpikir" terstruktur sebelum pertanyaan spontan, aktivitas berbicara berjenjang dari diskusi pasangan ke pelaporan pleno, serta penciptaan budaya kelas yang ramah terhadap kesalahan. Pendekatan ini bertujuan untuk memitigasi pemicu kecemasan spesifik pada mahasiswa perempuan sekaligus membangun lingkungan inklusif yang mempersiapkan seluruh pembelajar ESP untuk komunikasi profesional yang autentik.  Kata Kunci: Gender; Kecemasa Berbicara; English For Spesific Purposes; Pendidikan Vokasi
Eksplorasi Teknik Pre-Processing Berbasis eXtreme Gradient Boosting (XGBoost) pada Serangan DDoS Nur Faiz, Muhammad; Sari, Laura; Imam Riadi; Arif Wirawan Muhammad; Sukma Aji
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 6 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i6.9380

Abstract

Distributed Denial of Service (DDoS) attacks represent a critical threat to modern network security, particularly within Internet of Things (IoT) environments characterized by large-scale and heterogeneous traffic patterns. The primary challenges in detecting such attacks involve class imbalance, irrelevant features, and noise within the data, all of which can degrade the performance of machine learning-based detection models. This study evaluates the impact of a pre-processing pipeline—comprising the Synthetic Minority Over-sampling Technique (SMOTE), correlation-based feature selection, and advanced feature selection methods—on the performance of the XGBoost algorithm in detecting DDoS attacks using the CIC-IoT2023 dataset. Experimental results indicate that the XGBoost model trained on RAW data achieves exceptionally high performance, with an accuracy of 0.999983, precision of 0.985531, recall of 0.961390, and an F1-score of 0.999983. However, after applying the pre-processing techniques, all metrics experienced a decline, with accuracy decreasing to 0.958899, precision to 0.865729, recall to 0.748332, and the F1-score to 0.959158. The reduction in recall suggests a higher number of undetected attacks, whereas the drop in precision indicates an increase in false alarms. Nevertheless, the F1-score remaining above 0.95 demonstrates that the model continues to perform effectively overall. These findings reveal that pre-processing does not always lead to performance improvements, especially when the raw dataset is already relatively clean and balanced. This study provides deeper insights into how SMOTE, feature selection, and noise injection influence the generalization of XGBoost on IoT traffic, and emphasizes that the effectiveness of pre-processing is highly dependent on dataset characteristics and the intended application context of intrusion detection systems.
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