zulhipni reno saputra elsi
@um-palembang.ac.id
Teknologi Informasi Fakultas Teknik
Universitas Muahmmadiyah PAlembang
Scopus Publications
Scholar Citations
Scholar h-index
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Scopus Publications
Zulhipni Reno Saputra Elsi, Deris Stiawan, Ahmad Fali Oklilas, Susanto, Kurniabudi, Yesi Novaria Kunang, Mohd. Yazid Idris, and Rahmat Budiarto
IEEE
To maintain network security, Intrusion Detection System (IDS) is needed to detect anomaly and attack. Designing proper IDS requires accurate model. This paper proposes a model, which consists of statistical extraction, feature selection, dataset clustering, classification, and performance measurement. Experiments on MQTT-IOT-IDS2020 dataset which contains Normal, scan_A, scan_sU, Sparta and mqtt_bruteforce are conducted. The dataset is statistically extracted using Bidirectional-based features packet header feature with 37 features. Chi square algorithm is selected for performing feature extraction process. 10 relevant and best features are selected and ranked into 5-subsets and 10-subset feature. Three dataset splitting into testing data and training data of 90%:10%, 70%:30% and 50%:50% are created. Binary classification using k-Nearest Neighbor (KNN) and Adaboost algorithms are performed. The experimental results show accuracy level above 99% for all scenarios, with Adaboost algorithm outperforms k-Nearest Neighbor algorithm.
Zulhipni Reno Saputra Elsi, Heny Pratiwi, Yoyon Efendi, R Rusdina, Rina Alfah, Agus Perdana Windarto, and Fana Wiza
IOP Publishing
The aim of the research is to map clusters on Indonesia's national food security during the Covid-19 Pandemic Where food security is a condition for the fulfillment of food for the state up to individuals, which is reflected in the availability of sufficient food, both in quantity and quality, safe, diverse, nutritious, equitable, and affordable and does not conflict with the religion, beliefs and culture of the community, to be able to live a healthy, active, and productive life in a sustainable manner The data source used is secondary data from the Central Statistics Agency (abbreviated BPS) The data consists of monthly per capita expenditure in urban and rural areas by province and group of goods (rupiah) consisting of 33 data records (2011-2018) The group of goods used is expenditures used for food costs The data mining method used is k-medoids which are part of the clustering Cluster mapping uses 2 labels namely C1: labels with high food security and C2: labels with low food security The results of the k-medoids method calculation concluded that 19 provinces were in C1 cluster and 14 provinces were in C2 cluster From these results it is stated that 42% of Indonesia still has low food security as evidenced by the fulfillment of higher food needs than non-food These regions are West Sumatra, Riau, Bangka Belitung Islands, Riau islands, DKI Jakarta, West Java, Banten, Bali, Central Kalimantan, South Borneo, East Kalimantan, North Sulawesi, West Papua and Papua © Published under licence by IOP Publishing Ltd