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<![CDATA[Analysis of NSL-KDD Dataset for Classification of Attacks Based on Intrusion Detection System Using Binary Logistics and Multinomial Logistics ]]>
<![CDATA[Novia Amilatus Solekha]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1138
<![CDATA[At present, the intrusion detection system is the most developed trend in society. The intrusion detection system acts as a defense tool to detect security attacks which has been increasing steadily in recent years. Therefore, global information security is a very serious problem. As the types of attacks that emerge are constantly changing, there is a need to develop adaptive and flexible security features. Selection feature is one of the focuses of research on data mining for datasets that have relatively many attributes. In this study, the author tries to analyze the NSL-KDD data set with the selected attributes classified in two ways, namely binary classification (attack or not attack) and five classification classes using multinomial logistics, namely Dos, R2L, U2R, Probe and Normal. The results showed that the NSL-KDD dataset for the classification of attacks on the Intrusion Detection System (IDS) using binary logistics can increase the classification accuracy to 92.3% and 91.7% for datasets with multinomial logistics.]]>
<![CDATA[Determinan Kemiskinan Multidimensi Perempuan Berusia Produktif di Pulau Papua Tahun 2020 ]]>
<![CDATA[Faricha Zahara AlChasanah]]>;
<![CDATA[Ekaria Ekaria]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1141
<![CDATA[Poverty is problem for many countries, including Indonesia. In Indonesia, women experience poverty more severely than men. Papua Island was chosen as the research locus because it is consistent with the highest poverty rate. Measuring poverty with a monetary approach is not considered ideal, so the research focuses on measuring multidimensional poverty. This study aims to find out the general description and variables that are thought to influence the multidimensional poverty women of productive age in Papua Island 2020 based on social, demographic and economic aspects by taking into account inter-regional linkages. The data used are Susenas KOR and KP in 2020 and the method of spatial regression analysis with the Spatial Error Model. The results showed that 70.3532 percent women of productive age in Papua Island 2020 experienced multidimensional poverty, with a higher percentage experienced by Papua Province in the districts, especially Deiyai, Nduga and Intan Jaya. The variables that affect the multidimensional poverty women of productive age in Papua Island 2020 are the percentage of villages/kelurahan with rural status and women's economic and technological conditions.]]>
<![CDATA[Penambangan Opini Pada Data Multidomain Memanfaatkan Stream Big Data Twitter ]]>
<![CDATA[Herlambang Permadi]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1144
<![CDATA[The SDGs (Sustainable Development Goals) success era was marked by the openness of the government and other stakeholders to implement open and aspirational governance. Through opinion mining, the government, business actors, and other stakeholders can find out the current state of their output achievements to the public. Public opinion on social media is a tool for measuring, evaluating, and planning the success of a product, program and policy on a particular subject. However, quite a lot of opinion domains are shared by the public on social media. The existing opinion mining system only analyzes opinions on one particular opinion domain. This study builds a system that can help users to find out public perceptions about products, figures, and current topics in many analysis domains. Research uses big data on Twitter as a very popular source of opinion data to monitor public opinion. A review of previous related research concludes that the Naive Bayes algorithm has advantages in its simple computation, optimal for clustering few classes, and effective in classifying noisy features. The researcher found that the Naive Bayes algorithm in the Supervised Learning method was quite good in classifying multi-domain data. The implementation of the research resulted in a multi-domain sentiment analysis system. From the results of testing and evaluation, it is concluded that the system is able to identify opinion sentiments and provide a framework to accommodate analysis of the diversity of opinion domains from Twitter social media]]>
<![CDATA[Analisis Big Data dan Official Statistics dalam Melakukan Nowcasting Pertumbuhan Ekonomi Indonesia Sebelum dan Selama Pandemi COVID-19 ]]>
<![CDATA[Muhammad Alfaris Kurniawan]]>;
<![CDATA[Anna Triana Falentina]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1146
<![CDATA[Economic growth data is very important and eagerly awaited by many people. However, the release of economic growth data has been delayed by up to five weeks so it is not able to provide actual data. Nowcasting method can be an alternative to support the actual data availability. Mixed Data Sampling (MIDAS) is one of the nowcasting methods that accommodates differences in the time-frame of the data. This study aims to form a nowcasting model of Indonesia's economic growth before and during the COVID-19 pandemic using official statistics and Big Data. The method used is MIDAS regression analysis which is applied to groups of variables and periods. Nowcasting results show that both official statistics and Big Data are able to predict economic growth well. For the pre-pandemic period, models that use Google Trends data have the best accuracy and models that use macroeconomics variables is the best estimator. Meanwhile, if the pandemic period is included, the model with combined variables is able to provide the best accuracy.]]>
<![CDATA[Pengembangan Search Engine Konten Statistik pada Website Badan Pusat Statistik untuk Mendukung Diseminasi Statistik Resmi ]]>
<![CDATA[Yohanes Wahyu Trio Pramono]]>;
<![CDATA[Dhoni Eko Wahyu Nugroho]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1147
<![CDATA[BPS as a government-owned public agency, has the duties and authorities as an official body that disseminates statistical data. With the increasing penetration of internet usage, the website channel is one of the electronic media that is fast and easy to answer the challenges of data dissemination strategies. The development and implementation of a search engine on the BPS website have now succeeded in providing a search function for diverse statistical content, across website domain areas, and capable of performing image searches using image-to-text techniques and in-depth searches of all PDF texts for PDF publications and Official News Statistics PDF format. With this search engine development strategy, it is hoped that the data dissemination business process at the BPS Dissemination Directorate can run more optimally, being able to provide the data desired by data users more easily, quickly, and precisely.]]>
<![CDATA[Angka Harapan Hidup dan Makroekonomi Berkaitan? ]]>
<![CDATA[Rifki Chandra Utama]]>;
<![CDATA[Endah Setyowati]]>;
<![CDATA[Bayun Matsaany]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1148
<![CDATA[One of the dimensions of the Sustainable Development Goals (SDGs) is the economy. The performance of the economy can be seen from macroeconomic indicators, namely Gross Domestic Product (GDP), inflation, labor force index, and interest rates. The SDGs are also very closely related to demographic conditions, especially the level of health and welfare which is reflected in life expectancy. In this study, it is proposed to model life expectancy with macroeconomic variables using the Neural Network (NN) method. The selection of the NN method is based on the existence of a non-linear relationship between the life expectancy variable and several macroeconomic variables. The data used is Indonesia's annual data for the period 1990-2020. NN modeling uses several combinations, namely a combination of inputs, number of neurons, and activation functions. Based on these combinations, the best model is obtained, namely the NN(4,4,1) model with the activation function of tanh. The model explains that the four macroeconomic variables have an effect on life expectancy. This is in accordance with the argument in the book Macroeconomics that life expectancy modeling can be influenced by macroeconomic variables.]]>
<![CDATA[Determinan Pengangguran Usia Muda Terdidik di Provinsi Banten Tahun 2020 ]]>
<![CDATA[Faiz Alwan Alharis]]>;
<![CDATA[Aisyah Fitri Yuniasih]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1153
<![CDATA[Banten Province is the province with the highest open unemployment rate in Indonesia. In 2020, the open unemployment rate in Banten Province reached 10.64 percent. The high unemployment rate is dominated by the workforce aged 16 to 30 years. The high unemployment at a young age, especially unemployment at an educated youth can be the emergence of economic problems in Banten Province. This problem can be caused by the characteristics of the individual or the characteristics of the region. To be able to determine the effect of these characteristics, multilevel binary logistic regression analysis was used. The results obtained indicate that all variables significantly affect youth educated unemployment in Banten Province. The educated young age workforce that tends to become unemployed is the workforce that has the characteristics of living in rural areas, not married, not the head of the household, has never attended certified training, has work experience, lives in a district/city with a large population, and lives in districts/cities with low GRDP.]]>
<![CDATA[Determinan Pengangguran Lulusan SMK Provinsi Sulawesi Utara Sebelum dan Saat Pandemi Covid-19 ]]>
<![CDATA[Tengku Mashitah Crisanty]]>;
<![CDATA[Ernawati Pasaribu]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1155
<![CDATA[Indonesia is facing a demographic bonus phenomenon and the Covid-19 pandemic. As a result of the Covid-19 Pandemic, to reduce the spread of the Covid-19 virus, the government imposed PSBB which had an impact on reducing employees (PHK). One way to overcome unemployment is the implementation of vocational revitalization. However, the impact of the revitalization of SMK has not been seen as evidenced by the TPT of SMK graduates who are still the largest contributor to Indonesian unemployment in 2018 to 2021. North Sulawesi is one of the provinces that has a high TPT of SMK graduates. This study uses data from the August 2019 and 2021 National Labor Force Survey (Sakernas). The analytical method used is binary logistic regression. The results showed that in 2019 the independent variables that had a significant effect on unemployment status were marital status, field of expertise and year of graduation. Meanwhile, in 2021, the independent variables that have a significant effect on unemployment status are job training, marital status, year of graduation and area of residence.]]>
<![CDATA[Penyusunan Derajat Urbanisasi untuk Perhitungan Indikator Suistainable Development Goals ]]>
<![CDATA[Wida Widiastuti]]>;
<![CDATA[Achmad Fauzi Bagus Firmansyah]]>;
<![CDATA[Novia Permatasari]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1156
<![CDATA[Global methodology for delineating urban-rural areas is needed for monitoring the indicator of Sustainable Development Goals. The degree of urbanization, proposed method by United Nations, can classify cluster area into three-level categories; urban centers, urban clusters, and rural. The classification is calculated considering three aspects; population density, proportion of settlement areas, and neighborhood contiguity. This method can be implemented for calculating the indicator 9.1.1, namely Rural Access Index (RAI). This index reflects the accessibility of rural populations within 2 km radius of all-season roads. The results show significant inequality between two provinces, Nusa Tenggara Barat (NTB) and Nusa Tenggara Timur (NTT). The distribution of NTB’s population is dominated by urban centers (55.6%) and urban clusters (36.39%), whereas the majority of NTT’s population lives in rural areas (44.74%). The RAI results, 23.22% of NTT’s rural population has inadequate access to the all-season roads which is higher than NTB’s rural population (6.46%).]]>
<![CDATA[Perlukah Alternatif Penghitungan Nilai Tukar Petani? Simulasi Perbandingan Indeks Harga Laspeyres Index dan Rothwell Index pada Komoditas Ikan Segar di Indonesia ]]>
<![CDATA[Masarina Flukeria]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2022i1.1160
<![CDATA[Tulisan ini bertujuan untuk memperbaiki penghitugan Nilai Tukar Petani (NTP) yang telah lama dihitung oleh Badan Pusat Statistik sejak tahun 1976. NTP digunakan untuk mengukur daya beli keseluruhan komoditas pertanian secara keseluruhan yang dihitung dari rasio 2 (dua) jenis indeks harga yaitu Indeks Harga yang Diterima oleh Petani dan Indeks Harga yang Dibayar oleh Petani. Penggunaan Modified Laspeyres Index untuk Indeks Harga yang Diterima oleh Petani dianggap belum mampu menangkap dinamika kuantitas produksi pertanian dan perikanan yang umumnya bersifat volatile dan dipengaruhi oleh faktor musim. Penggunaan Modified Laspeyres Index pada Indeks Harga yang Diterima oleh petani dinilai kurang tepat karena mengasumsikan volume produksi yang konstan sepanjang waktu. Pada kenyataannya, baik harga maupun kuantitas produk pertanian dan perikanan mempunyai sifat yang volatile atau bahkan dipengaruhi oleh faktor musim dimana pada masa panen mengalami lonjakan volume produksi yang sangat tinggi dan masa paceklik mengalami penurunan volume produksi yang tajam. Oleh karena itu, penggunaan Modified Laspeyres Index pada komponen Indeks Harga yang Diterima oleh Petani perlu dipertimbangkan kembali. Dengan kata lain, perlu dibangun alternatif indeks harga lain yang mampu menangkap volatilitas pada produk pertanian sehingga penilaian kinerja pertanian dan perikanan yang lebih baik dapat dicapai. Penulis mengimplementasikan Rothwell Index pada Indeks Harga yang Diterima oleh Petani dengan menggunakan komoditas ikan segar sebagai objek penelitian ini karena atributnya sebagai komoditas yang relatif dominan dipengaruhi oleh faktor cuaca sehingga baik harga dan kuantitas produksinya pun mempunyai volatilitas tinggi. Hasil penelitian menunjukkan adanya perbedaan nyata antara indeks harga komoditas ikan segar dengan menggunakan Laspeyres Index dan Rothwell Index. Rothwell Index lebih rasional daripada Laspeyres Index karena mampu menangkap volatilitas harga dan kuantitas produksi komoditas ikan segar tersebut. Dari sisi kebijakan, NTP yang dihitung saat ini penting untuk diperbaiki karena digunakan untuk merumuskan dan mengevaluasi kebijakan pertanian dan perikanan di Indonesia.]]>
