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<![CDATA[Analisis Regresi Logistik pada Karakteristik Perempuan Berumur 15-49 Tahun yang Tidak Pernah Menggunakan Alat Kontrasepsi (KB) di Kabupaten Bintan ]]>
<![CDATA[Dio Dwi Saputra]]>
<![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.v2022i1.1570
<![CDATA[The Family Planning Program (KB) held by the Indonesian government has different levels of achievement between regions. Bintan Regency is the regency with the highest percentage of ever-married women aged 15-49 years who have never used contraception in the Riau Islands Province. So, this study aims to determine the characteristics of women aged 15-49 years and their effects. The inferential analysis method used is binary logistik regression analysis. The findings of this study are women aged 15-49 years in Bintan Regency whose age at first marriage is 21 years and over, have a senior high school/equivalent education and college education, does not work, does not use the internet and does not have health insurance, has a tendency not to use contraception. Meanwhile, women who live in rural areas, have a junior high school/equivalent education and are in non-poor households tend to use contraception. The government must optimize the socialization of the family planning program and make policies, which have a direct or indirect impact on women’s decisions to participate in the family planning program.]]>
<![CDATA[Determinan Pengangguran Lulusan SMK di Wilayah dengan Potensi Ekonomi Sektor Petanian (Pulau Sulawesi) Tahun 2021 ]]>
<![CDATA[Ayu Setianingsih]]>;
<![CDATA[Febri Wicaksono]]>
<![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.v2022i1.1571
<![CDATA[Tujuan dibangunnya pendidikan kejuruan adalah membentuk tenaga kerja yang berkompetensi dan terampil. Akan tetapi dalam kenyataannya lulusan SMK memberikan kontribusi tertinggi untuk pengangguran di Indonesia dibandingkan tingkat pendidikaan lainnya. Disisi lain sektor pertanian merupakan salah satu sektor potensial di Indonesia. Kondisi serupa juga terjadi di Pulau Sulawesi dimana lulusan SMK di Pulau Sulawesi secara keseluruhan memiliki TPT yang tertinggi dibandingkan tingkat pendidikan lainnya. Begitu juga dengan sektor potensialnya yang secara keseluruhan juga menunjukkan potensi ekonominya berada pada sektor pertanian. Tingginya peran sektor pertanian dalam perekonomian dapat memberikan peluang kerja yang besar karena adanya potensi kegiatan ekonomi dari sektor tersebut. Akan tetapi sektor pertanian adalah sektor yang kurang diminati oleh generasi muda. Oleh karena itu penelitian ini bertujuan untuk mengetahui variabel-variabel apa saja yang mempengaruhi pengangguran lulusan SMK di wilayah dengan potensi ekonomi sektor pertanian (Pulau Sulawesi). Data yang digunakan ada data Sakrernas Agustus 2021. Metode yang digunakan yaitu regersi logistik biner. Hasil penelitian menunjukkan bahwa variabel umur, status perkawinan, status dalam rumah tangga, klasifikasi wilayah, dan bidang keahlian berpengaruh signifikan terhadap pengangguran lulusan SMK di Pulau Sulawesi tahun 2021. Sedangkan variabel jenis kelamin dan pelatihan tidak berpengaruh signifikan.]]>
<![CDATA[Variabel yang Memengaruhi Risiko Perceraian di Kabupaten Cilacap Tahun 202 ]]>
<![CDATA[Adima Lu'lu'atun Nabila Munawardani]]>;
<![CDATA[Suryanto Aloysius]]>
<![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.v2022i1.1573
<![CDATA[A family from legal marriage is an important foundation in the development of human resources. However, this sometimes cannot be achieved when marriage ends in divorce. This because divorce causes various negative impacts and mainly affects children as the next generation of the nation. Cilacap Regency is the largest contributor to divorce in Central Java with the number of divorces in 2021 reaching 7234 cases. This study aims to determine the general characteristics and variables that affect the risk of divorce in Cilacap Regency in 2021. The data used are secondary data from divorce cases that have been decided by the Cilacap Religion Court in 2021. The analytical method used is survival analysis with parametric method using weibull distribution. The results showed that wife's occupation, husband's education level, wife's education level, place of residence and children had a significant effect on the risk of divorce in Cilacap Regency in 2021.]]>
<![CDATA[Perancangan Smart Predictive Maintenance untuk Mesin Produksi ]]>
<![CDATA[Krisman Yusuf Nazara]]>
<![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.v2022i1.1575
<![CDATA[Indonesia's economic growth rate gets a large contribution from the manufacturing industry. In the industrial era 4.0, optimizing the use of information technology supports the effectiveness of an industry's employee performance to be more productive. To optimize maintenance costs and monitor production equipment and machines, Internet of Things (IoT) technology is needed that is equipped with machine learning to produce smart predictive maintenance. This study aims to obtain the best predictive model for the classification of production machine conditions by comparing various machine learning models. This predictive maintenance model is expected to be able to predict machine maintenance schedules so as to increase the life of production machines, helping to estimate maintenance costs. The analytical method used refers to classification analysis by comparing 6 (six) classification models, namely: XGBoost, k-nearest neighbors, logistic regression, gradient boosting, decision tree regression and random forest. Comparison of these algorithms to obtain the best classification model in the case of production machines. Of the six algorithms, the best model is obtained from XG-boost with an accuracy of 99.07.]]>
<![CDATA[Pengaruh Karakteristik Sosiodemografi Kepala Rumah Tangga dan Anak Terhadap Kecenderungan Anak Terlibat dalam Pekerjaan Berbahaya di Sektor Pertanian: Analisis Data SAKERNAS ]]>
<![CDATA[Sukma, Weni Lidya]]>;
<![CDATA[Kadir, Kadir]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2023i1.1586
<![CDATA[In the agricultural sector, children may be involved in hazardous work that requires physical labor and long hours. Our study used SAKERNAS’s data conducted in August 2022 to examine the effect of both household heads’ and children’s sociodemographic characteristics on the child probability working in agricultural hazardous jobs. Our study confirms the importance of household heads' level in preventing children from working in agriculture and/engaging in hazardous job activities. The results of multinomial logistic regression using marginal effects pointed out that the education level of household heads have a positive impact on reducing the likelihood of child labor in agriculture and engagement of children in hazardous agricultural jobs. We also found the probability of children being child labour in agriculture and get involved in hazardous jobs is larger in female-head household compared to male-head household. In addition, increasing educational participation among children can also reduce the likelihood of child labor.]]>
<![CDATA[Determinan Status Kerawanan Pangan Rumah Tangga di Nusa Tenggara Timur 2021 ]]>
<![CDATA[Br Lumban Gaol, Marta Desna Fitria]]>;
<![CDATA[Sukim, Sukim]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2023i1.1591
<![CDATA[Households food insecurity in the Province of East Nusa Tenggara (NTT) has an urgency to address. Although regionally the province of NTT has a food secure status in 2021, the prevalence of people experiencing food insecurity in that province is the highest nationally. This study aims to analyze the determinants of households food insecurity status in NTT Province in 2021. This study uses two levels of analysis units, namely the households level and the districts/cities level by applying the multilevel binary logistic regression method. The data used are raw data and publications from the Central Bureau of Statistics (BPS). Most households in NTT Province are food insecure. Determinants of households food insecurity status in NTT Province in 2021 are area of residence, gender of head of household (HH), age of HH, field of business of HH, number of household members, household poverty status, status of food aid recipients, sources of proper drinking water, and the number of shops and markets.]]>
<![CDATA[Implementasi Support Vector Machine (SVM) dalam Penentuan Klasifikasi Indeks Khusus Penanganan Stunting di Indonesia ]]>
<![CDATA[Syafika, Vicky Alfina Nur]]>;
<![CDATA[Karisma, Ria Dhea Layla Nur]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2023i1.1595
<![CDATA[Stunting is a health problem that poses a challenge in various countries, including Indonesia. Several government stunting intervention programs can be evaluated based on the stunting-specific intervention index. Accurate evaluation results of stunting intervention programs will facilitate the government in determining the next policy. This study aims to obtain the classification and accuracy level of the stunting-specific intervention index in Indonesia using the Support Vector Machine (SVM) method. The results of the study showed that the best model for stunting-specific intervention index classification using the SVM method was the polynomial kernel with parameters h= 1 and C=100. The resulting classification showed that there were 4 Provinces with low stunting-specific intervention index categories, 21 Provinces with moderate stunting-specific intervention index categories, and 9 Provinces with high stunting-specific intervention index categories. The 100% accuracy level of the stunting-specific intervention index classification in Indonesia using the SVM method indicates that the SVM methods is highly effective in classifying the stunting-specific intervention index in Indonesia.]]>
<![CDATA[Faktor-Faktor yang Memengaruhi Pekerja Anak di Provinsi Nusa Tenggara Timur Tahun 2021 ]]>
<![CDATA[Alwi, Rahmi Maulina]]>;
<![CDATA[Sirait, Timbang]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2023i1.1601
<![CDATA[Child labor is a global issue contained in SDG's goal 8.7 which envisions the end of child labor in all its forms by 2025. In 2021 it is known that the province of NTT has a high number of child workers and ranks eighth out of 34 provinces in the world. Indonesia, and is above the national average. Much research has been done on child labor, but not much has considered the imbalance between success and failure in this child labor phenomenon. This research was conducted to determine the characteristics of child labor in the province of NTT in 2021 and the factors that influence it by using the firth logistic regression method which takes into account estimation bias in unbalanced data conditions. The research was conducted using data from the national socio-economic survey core module for March 2021. From the research it was found that the factors that influence child labor are the child's education level, child's age, child's gender, and marital status of the head of household.]]>
<![CDATA[Analisis Spasial Variabel-Variabel yang Memengaruhi Jumlah Kasus Baru HIV/AIDS di Provinsi Jawa Timur Tahun 2021 ]]>
<![CDATA[Thahar, Safira Fauziana]]>;
<![CDATA[Sirait, Timbang]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2023i1.1602
<![CDATA[HIV/AIDS remains a global health emergency. In the last five years, East Java Province has always occupied the first position in the increase in the number of HIV/AIDS cases in Indonesia. The purpose of this study is to determine the variables that significantly affect the increase in the number of new HIV/AIDS cases in East Java Province in 2021 using the Geographically Weighted Negative Binomial Regression analysis method to overcome overdispersion and spatial effects on data. The independent variables studied were the percentage of condom users, population density, percentage of poor people, average years of schooling, percentage of villages with crimes of drug distribution and abuse, ratio of the number of health facilities per 10.000 population, and ratio of the number of health workers per 10.000 population. The data came from the publications of the Health Office and the Central Bureau of Statistics of East Java Province. The results showed that the distribution of the number of new HIV/AIDS cases in East Java in 2021 tended to cluster. In addition, four groups of districts/cities were formed based on the similarity of independent variables that had a significant effect.]]>
<![CDATA[Pengaruh Trade Creation dan Trade Diversion pada ACFTA terhadap Ekspor Karet (HS 40) Indonesia ]]>
<![CDATA[Qur'ani, Nissa Shahadah]]>;
<![CDATA[Utami, Efri Diah]]>
<![CDATA[ Seminar Nasional Official Statistics Vol 2023 No 1 (2023): Seminar Nasional Official Statistics 2023 ]]>
Publisher : <![CDATA[Politeknik Statistika STIS ]]>
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DOI: 10.34123/semnasoffstat.v2023i1.1610
<![CDATA[Indonesia is one of the highest exporters of rubber and articles thereof. In utilizing natural resources, Indonesia joined ASEAN China Free Trade Area (ACFTA), the agreement ASEAN and China to create a free trade area. There are effects of trade union, trade creation and diversion. This study aims to find out the general description of rubber and articles thereof exports, trade patterns before and after implementation of ACFTA, and variables that can affect Indonesia's exports of rubber and articles thereof. This study uses the SUR model gravity fixed effects panel with data 2000-2021. The trading pattern showed indications of changes before and after ACFTA; variables of real GDP per capita, economic distance, population, REER, measures of economic similarity, trade creation and diversion affect Indonesia's exports rubber and articles thereof; and no trade creation or diversion effects were found. So, it is better for Indonesia expand exports to non-ACFTA members countries.]]>
