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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Dasar SAINSMAT IPTEK Journal of Proceedings Series KONSELI: Jurnal Bimbingan dan Konseling (E-Journal) Journal of Regional and City Planning Jurnal Informatika dan Teknik Elektro Terapan Sistemasi: Jurnal Sistem Informasi Journal of Applied Geospatial Information Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Unisda Journal of Mathematics and Computer Science (UJMC) Jurnal Penelitian dan Pengembangan Pelayanan Kesehatan International Journal of Pedagogy and Teacher Education J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika METIK JURNAL Building of Informatics, Technology and Science Jurnal Perencanaan Pembangunan Journal of Education and Learning Mathematics Research (JELMaR) International Journal of Advances in Data and Information Systems Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Layanan Masyarakat (Journal of Public Service) TheJournalish: Social and Government The Journal of Indonesia Sustainable Development Planning (JISDeP) JoMMiT : Jurnal Multi Media dan IT Jurnal Riset Ilmu Ekonomi Jurnal Algoritma East Java Economic Journal SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Jurnal Mahasiswa Ilmu Komputer PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Journal of Multiscale Materials Informatics Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial

Harun Al Azies

Universitas Dian Nuswantoro

Author-ID : 6466980

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Transportation Other

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Pemodelan Pengaruh Imunisasi DPT Terhadap Angka Kematian Bayi di Jawa Timur Tahun 2016 Menggunakan Pendekatan Regresi Nonparametrik Spline Al Azies, Harun; Trishnanti, Dea
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 12 No 1 (2019): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Fakultas Sains dan Teknologi Univ. PGRI Adi Buana Surabaya

East Java is one of the provinces with a high IMR level. Based on the District / City report in East Java, in 2006 it was 0.035 live births and became 0.0032 live births in 2008. Identification of factors that influence both indicators correctly can be done by modeling, namely by nonparametric regression analysis. The nonparametric regression approach used is Spline, with its strengths the model tends to look for estimates wherever the data moves. This is because there is a knot point which is a joint fusion point which indicates a change in data behavior patterns. Based on the results of analysis and discussion using Spline analysis, it is known that the factors that influence the incidence of IMR in East Java are toddlers receiving type 3 DPT immunization. The best Spline nonparametric regression model is a linear Spline model with three point knots. The GCV value produced was 51.34. Factors of children under five obtained immunizations affecting infant mortality rates in districts / cities in East Java in 2016. This research still uses linear spline regression program with a combination of one, two, and three knots with R square of 65.92%. The need to develop programs into quadratic and cubic orders using a combination of knots. Jawa Timur merupakan salah satu provinsi dengan tingkat AKB yang tinggi. Berdasarkan laporan Kabupaten/Kota di Jawa Timur, pada tahun 2006 sebesar 0,035 kelahiran hidup dan menjadi 0,0032 kelahiran hidup pada tahun 2008. Jika suatu daerah dengan AKB yang tinggi, maka terdapat kemungkinan bahwa daerah sekitarnya akan memiliki beban AKB yang sama pula. Identifikasi faktor-faktor yang mempengaruhi kedua indikator secara tepat dapat dilakukan dengan pemodelan, yaitu dengan analisis regresi nonparametrik. Pendekatan regresi nonparametric yang digunakan adalah Spline, dengan kelebihannya model cenderung mencari estimasinya kemanapun data tersebut bergerak. Hal ini dikarenakan terdapat titik knot yang merupakan titik perpaduan bersama yang menunjukkan terjadinya perubahan pola perilaku data. Berdasarkan hasil analisis dan pembahasan dengan menggunakan analisis Spline diketahui bahwa faktor yang berpengaruh terhadap kejadian AKB di Jawa Timur adalah balita memperoleh imunisasi DPT tipe 3. Model regresi nonparametrik Spline terbaik adalah model Spline linear dengan tiga titik knot. Nilai GCV yang dihasilkan adalah 51,34. Faktor balita memperoleh imunisasi mempengaruhi angka kematian bayi di kabupaten/kota di Jawa Timur pada tahun 2016. Penelitian ini masih menggunakan program regresi spline linier dengan kombinasi satu, dua, dan tiga knot dengan R square sebesar 65,92%. Perlu adanya pengembangan program menjadi orde kuadratik dan kubik dengan menggunakan kombinasi knot.

Comparison of Kernel Support Vector Machine (SVM) in Classification of Human Development Index (HDI) Harun Al Azies; Dea Trishnanti; Elvira Mustikawati P.H
IPTEK Journal of Proceedings Series No 6 (2019): The 1st International Conference on Global Development (ICODEV)
Publisher : Institut Teknologi Sepuluh Nopember

Human Development Index (HDI) is one of measuring instrument of achieving quality of life of one region even country. There are three basic components of the Human Development Index compilers: health dimension, knowledge dimension, and decent living dimension. Classification is a method for compiling data systematically according to the rules that have been set previously. In recent years, classification method has been proven to help many people’s work, such as image classification, medical biology, traffic light, text classification etc. There are many methods to solve classification problem. This variation method makes the researchers find it difficult to determine which method is best for a problem this framework is aimed to compare the ability of classification methods, such as Support Vector Machine (SVM) Linear Kernel, Radial Basis Function (RBF) Kernel and Polynomial kernel methods. The result of classification of HDI by using RBF kernel is the best kernel to solve HDI problem, with parameter combination cost= 1 and gamma=1 obtained classification accuracy of 98.1% which is the best classification accuracy.

Analisis Pengaruh Fasilitas Kesehatan terhadap Kematian Bayi di Jawa Timur Menggunakan Pendekatan Geographically Weighted Regression Harun Al Azies
Jurnal Penelitian dan Pengembangan Pelayanan Kesehatan Vol. 3 No. 2 (2019)
Publisher : Jurnal Penelitian dan Pengembangan Pelayanan Kesehatan (Journal of Research and Development in Health Services)

Abstrak Jawa Timur merupakan salah satu provinsi dengan tingkat kematian bayi yang tinggi. Analisis pengaruh fasilitas kesehatan terhadap kejadian kematian bayi di Jawa Timur dapat membantu merumuskan kebijakan dan program kesehatan ibu dan anak. Tujuan analisis ini adalah untuk mengetahui hubungan antara ketersediaan posyandu, klinik Keluarga Berencana (KB), Pos Pelayanan Keluarga Berencana Desa (PPKBD), rumah sakit bersalin, puskesmas pembantu, dan apotek dengan kejadian kematian bayi. Terdapat kemungkinan bahwa wilayah sekitar daerah dengan kematian bayi yang tinggi akan memiliki beban kematian bayi yang tinggi pula. Oleh karena itu diperlukan suatu metode pemodelan statistik dengan memperhitungkan aspek lokasi yaitu metode Geographically Weighted Regression (GWR). Analisis dan pembahasan menggunakan metode GWR mendapatkan bahwa faktor ketersediaan Posyandu Strata Pratama dan Madya serta Puskesmas Pembantu memengaruhi kejadian kematian bayi di wilayah Pacitan, Ponorogo, Pasuruan, Kediri (kota), Malang (kota), Pasuruan (kota), Banyuwangi, dan Probolinggo. Sementara itu, di wilayah Kabupaten Bondowoso, Bangkalan, Batu (Kota), Blitar, Sidoarjo, dan Sumenep kejadian kematian bayi dipengaruhi oleh faktor ketersediaan Posyandu Strata Pratama dan Madya. Faktor ketersediaan Posyandu Strata Purnama dan Mandiri memengaruhi kejadian kematian bayi di wilayah Lamongan, Madiun (Kota), Kediri, dan Malang sedangkan di wilayah Kabupaten Lumajang, Jombang, Magetan, Bojonegoro, dan Jember dipengaruhi oleh ketersediaan Posyandu Strata Purnama, dan Kabupaten Gresik oleh ketersediaan Posyandu Strata Pratama. Ketersediaan fasilitas kesehatan penunjang yang terjamin, adanya kesadaran ibu untuk menjaga kesehatan diri dan asupan nutrisi untuk bayi, serta rutin mengecek kesehatan merupakan upaya untuk menekan tingkat kematian bayi di Jawa Timur. Kata kunci: fasilitas kesehatan, Geographically Weighted Regression, kematian bayi, spasial analisis Abstract East Java is one of the provinces with high infant mortality rates. Analysis of the influence of health facilities on infant mortality in East Java can help to formulate maternal and child health policies and programs. The purpose of this analysis is to determine the relationship between the availability of Integrated Healthcare Center (Posyandu), family planning clinics, village family planning services (PPKBD), maternity hospitals, supporting health centers, and pharmacies with the incidence of infant mortality. There is a possibility that the surrounding area of an area with high infant mortality will have the same burden. Therefore we need a statistical modeling method that takes into account the location aspects, such as the Geographically Weighted Regression (GWR) method. Analysis and discussion using GWR analysis showed that the availability of Posyandu Strata Pratama and Madya, as well as the supporting health centers, affected infant mortality incidence in Pacitan, Ponorogo, Pasuruan, Kediri (city), Malang (city), Pasuruan (city), Banyuwangi, and Probolinggo. While in Bondowoso Regency, Bangkalan, Batu (city), Blitar, Sidoarjo, and Sumenep, it was affected by the availability of Posyandu Strata Pratama and Madya. The availability of Posyandu Strata Purnama and Mandiri affected the incidence of infant mortality in Lamongan, Madiun (City), Kediri, and Malang areas. The availability of Posyandu Strata Purnama influenced the incidence of infant mortality in Lumajang, Jombang, Magetan, Bojonegoro, and Jember districts while Gresik Regency is affected by the availability of Posyandu Strata Pratama. The availability of supporting health facilities, the awareness of mothers to maintain personal health and nutritional intake for infants, and routine health check-up are efforts to reduce infant mortality in East Java. Keywords: health facility, Geographically Weighted Regression, infant mortality, spatial analysis

Faktor-Faktor yang Mempengaruhi Angka Harapan Hidup di Jawa Timur: Prediksi dengan Pendekatan Bayesian Model Averaging Harun Al Azies; Vivi Mentari Dewi
Jurnal Perencanaan Pembangunan: The Indonesian Journal of Development Planning Vol. 5 No. 2 (2021): October 2021
Publisher : Ministry of National Development Planning Republic of Indonesia/Bappenas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36574/jpp.v5i2.214

This study predicts the factors that influence life expectancy in East Java, Indonesia. In particular, this study compares the prediction results between the linear regression model and the Bayesian Model Averaging (BMA). The study used a 2015 data set from the Central Bureau of Statistics (BPS) of the province of East Java.The results of data exploration show that the life expectancy in East Java is 70.68 years, the Bondowoso regency is the region with the lowest life expectancy at 65.73 years and the city of Surabaya is the area with the highest life expectancy value in East Java, which is 73.85 years.The results of the inference study indicate that the factors that are expected to affect life expectancy in East Java are the infant mortality rate and the illiteracy rate of the population aged 10 and over.The results of the comparison between the BMA and the regression show that the BMA is a better model for predicting the factors that affect life expectancy in East Java than the regression model because the BMA model can estimate the parameters more efficiently by estimating the model parameters based on the standard error value.

Pemodelan Pengaruh Imunisasi DPT Terhadap Angka Kematian Bayi di Jawa Timur Tahun 2016 Menggunakan Pendekatan Regresi Nonparametrik Spline Harun Al Azies; Dea Trishnanti
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 12 No 1 (2019): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya

Identification of Mean Years of Schooling as a Control for RPJMD: A Spatial Autocorrelation Approach Harun Al Azies; Anwar Efendi Nasution
Journal of Education and Learning Mathematics Research (JELMaR) Vol 2 No 2 (2021): November 2021
Publisher : Department of Mathematics Education, Faculty of Teacher Training and Education, Wisnuwardhana University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37303/jelmar.v2i2.60

This article will identify the mean years of schooling in East Java as a control for achieving RPJMD. Inequality in the development of education leads to inequalities between the regions of East Java. This is due to the different regional characteristics, it is, therefore, necessary to respond to it by carrying out a regional mapping based on the education indicators listed in the RPJMD of each region using a statistical analysis approach, namely spatial autocorrelation. The variable that becomes the indicator in this study is the Mean Years of Schooling (MYS), the unit of observation being the regencies/cities of East Java. The results of the research that has been conducted can be concluded that the mean years of schooling for the population of East Java Province is seven years where urban areas have a better average length of schooling than in districts, and there are only nine areas in East Java that have MYS exceeding the RPJMD target. In the Global Moran's I test, there is a positive autocorrelation or cluster pattern that exhibits similar characteristics in adjacent locations, and the results of the local Morans’ show that there are nine regions that have spatial relationships with their most significant areas relatives based on the MYS indicator. These areas are Bondowoso Regency, Bangkalan Regency, Pamekasan Regency, Gresik Regency, Jember Regency, Probolinggo Regency, Sampang Regency, Sidoarjo Regency and Surabaya City

Analysis of Poverty Convergence at The District/City Level in East Java Province Harun Al Azies; Wahyu Wisnu Wardana
East Java Economic Journal Vol. 4 No. 2 (2020)
Publisher : Kantor Perwakilan Bank Indonesia Provinsi Jawa Timur

This paper aims to investigate the presence of poverty convergence across regions in East Java over the period of 2008-2018. By employing σ-convergence dan β-convergence, we find that in general there is no strong evidence of poverty convergence across regions. Furthermore, disaggregating the analysis into urban (city) and rural (municipality) areas reveals that there is a tendency of poverty convergence across cities in East Java. In contrast, the finding suggests that municipalities in East Java tended to experience poverty divergence. Other conclusions based on the results of absolute and conditional convergence show that there is a process of convergence of poverty in urban (city) and rural (municipality) during the period 2011-2014.

Partitional Clustering of Underdeveloped Area Infrastructure with Unsupervised Learning Approach: A Case Study in the Island of Java, Indonesia Bambang Widjanarko Otok; Agus Suharsono; Purhadi Purhadi; Rahmawati Erma Standsyah; Harun Al Azies
Journal of Regional and City Planning Vol. 33 No. 2 (2022)
Publisher : The Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/jpwk.2022.33.2.3

This study attempted to identify underdeveloped areas in regencies/cities on the island of Java, Indonesia, based on a number of infrastructure indicators. An unsupervised learning approach was used to perform partition clustering with the K-Means, K-Medoids, and CLARA methods. In addition to technically obtaining clustering results and conducting a performance comparison of the three unsupervised learning methods, another objective of this research was to map the clustering results to make it easier to recognize the characteristics of the regions indicated as underdeveloped areas, which should be absolute priorities for infrastructure development. It was found that the best clustering method was the CLARA method, with a connectivity coefficient of 7.4794 and a Dunn’s index value of 0.1042. The partition clustering of regencies/cities on Java Island using the CLARA method based on infrastructure indicators resulted in 99 regencies/cities included in the cluster of areas with underdeveloped infrastructure, while 12 regencies/cities were included in the cluster of areas with developing infrastructure, and 8 regencies/cities were included in the cluster of areas with developed infrastructure.

Artificial Intelligence Berbasis QSPR Dalam Kajian Inhibitor Korosi Muhamad Akrom; Usman Sudibyo; Achmad Wahid Kurniawan; Noor Ageng Setiyanto; Ayu Pertiwi; Aprilyani Nur Safitri; Novianto Hidayat; Harun Al Azies; Wise Herawati
JoMMiT Vol 7, No 1 (2023)
Publisher : Politeknik Negeri Media Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46961/jommit.v7i1.721

Baja termasuk material yang memiliki ketahanan rendah terhadap serangan korosi Ketika berada pada lingkungan korosif. Inhibitor organik mampu menghambat korosi dengan efisiensi inhibisi yang tinggi. Tinjauan komparatif penting bagi pengembangan metode evaluasi kinerja inhibitor disajikan dalam karya ini. Kami mereview perkembangan artificial intelligence berbasis mesin learning dengan model QSPR dalam kajian penghambatan korosi. Makalah ini menjelaskan bagaimana metode pembelajaran mesin berbasis data dapat menghasilkan model yang menghubungkan sifat-aktivitas molekuler dengan penghambatan korosi oleh inhibitor berbasis bahan alam (green inhibitor). Teknik ini dapat digunakan untuk memprediksi kinerja senyawa yang belum disintesis atau diuji. Keberhasilan model ini memberikan paradigma untuk penemuan senyawa baru yang cepat, penghambat korosi yang efektif untuk berbagai logam dan paduan.

Mapping of the Reading Literacy Activity Index in East Java Province, Indonesia: an Unsupervised Learning Approach Harun Al Azies; Ayu Febriana Dwi Rositawati
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2021 No. 1 (2021): Proceedings of 2021 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2021i1.128

One of the educational problems that must be faced by East Java Province is the low reading culture of the community. The level of reading culture can be indicated by the Reading Literacy Activity Index (Alibaca Index). Alibaca Index of East Java is only 33.19 which value is included in the low category. So, this research uses the indicators that compose the Alibaca Index to classify regencies/cities in East Java Province. The analysis process carried out in this research uses one of the unsupervised learning algorithms, namely the K-Means algorithm. Analysis using the K-Means algorithm for grouping regencies/cities in East Java Province based on the indicators that compose the Alibaca index gives the results that the regencies/cities of East Java Province are divided into 3 clusters based on the optimal number of clusters according to the result of the elbow and silhouette method. Cluster 1 consists of 20 regencies and cities, cluster 2 consists of 10 regencies, and cluster 3 consists of 8 cities. Each cluster has different characteristics, cluster 1 is the cluster with the lowest skill dimension, while the cluster 2 area is an area that dominates the access dimension, alternative dimension, and cultural dimension, meanwhile, the third cluster does not have dominance in these 3 dimensions, which means that cluster 3 is the government's priority for improving reading activities, so the result of the analysis can help the government to develop strategic policies to achieve educational equity, especially concerning literacy levels based on the characteristics of each regency/city in East Java Province.

Co-Authors Achmad Wahid Kurniawan Achmad Wahid Kurniawan Adhitya Nugraha Agus Suharsono Akrom, Muhamad Alfa Trisnapradika, Gustina Alzami, Farrikh Ananda, Imanuel Khrisna Andrean, Muhammad Niko Anwar Efendi Nasution Aprilyani Nur Safitri Ardytha Luthfiarta Ariyanto, Noval Ayu Febriana Dwi Rositawati Ayu Pertiwi Ayu Pertiwi Bambang Widjanarko Otok Brilianti Rochmanto, Hani Brilianto, Rivaldo Mersis Budi, Setyo Dea Trishnanti Dea Trishnanti Devi Putri Isnarwaty Dikaputra, Ishak Bintang Elvira Mustikawati P.H Fahmi Amiq Fawwaz Atha Rohmatullah Firmansyah, Gustian Angga Fitriani, Fenny Gangga Anuraga Ganiswari, Syuhra Putri Guruh Fajar Shidik Gustina Alfa Trisnapradika Hani Brilianti Rochmanto Herawati, Wise Herowati, Wise Hidayat, Novianto Hidayat, Novianto Nur Irnanda, Muhammad Diva Ishak Bintang Dikaputra Isnarwaty, Devi Putri ISWAHYUDI ISWAHYUDI Junta Zeniarja Kharisma, Ni Made Kirei Megantara, Rama Aria Moch Anjas Aprihartha Muhamad Akrom Muhammad Naufal Muhammad Naufal, Muhammad Muljono Muljono Noor Ageng Setiyanto, Noor Ageng Noval Ariyanto Novianto Hidayat Nugroho, Dandy Prasetyo Nur Safitri, Aprilyani Prabowo, Wahyu Aji Eko Pratama, Ananta Surya Pravesti, Cindy Asli Pulung Nurtantio Andono Purhadi Purhadi Putra, Permana Langgeng Wicaksono Ellwid Rahman, Irfan Fauzia Rahmawati Erma Standsyah Ramadhan Rakhmat Sani Rohmatullah, Fawwaz Atha Safitri, Aprilyani Nur Sari Ayu Wulandari Setyo Budi Sri Winarno Sri Winarno Sudibyo, Usman Supriadi Rustad Trishnanti, Dea Trisnapradika, Gustina Alfa Umam, Taufiqul Usman Sudibyo Vivi Mentari Dewi Wahyu Wisnu Wardana Wise Herawati Wise Herowati Zahro, Azzula Cerliana Zain, Affa Fahmi Zami, Farrikh Al

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