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Gangga Anuraga
Universitas PGRI Adi Buana Surabaya
Religion Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Pemodelan Faktor yang Mempengaruhi Angka Kematian Bayi di Jawa Timur dengan Menggunakan Geographically Weighted Regression Antonito Hornay Cabral; Mariana Yonasti Udus; Silfia Febriani Jamlean; Wara Pramesti; Gangga Anuraga
SNHRP Vol. 2 (2019): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 2 Tahun 2019
Publisher : LPPM Universitas PGRI Adi Buana

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Abstract

Angka Kematian Bayi (AKB) didefinisikan sebagai resiko untuk anak yang lahir hidup mati sebelum ulang tahun pertama yang dikenal sebagai salah satu indikator yang sensitif dan umum digunakan untuk pembangunan sosial dan ekonomi penduduk. Angka Kematian bayi merupakan salah satu indikator penting dalam menentukan tingkat kesehatan masyarakat. Berdasarkan laporan Badan Pusat Statistik Jawa Timur tahun 2016, angka kematian bayi sebesar 23.60 per 1000 kelahiran. Angka tersebut diatas tingkat nasional tetapi masih dianggap tinggi dan belum memenuhi target pemerintah. Upaya yang dapat dilakukan oleh pemerintah untuk menurunkan angka kematian bayi adalah dengan mengetahui faktor-faktor yang memengaruhi AKB tersebut. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi angka kematian bayi di Jawa Timur tahun 2016. Salah satu metode yang digunakan untuk megetahui faktor-faktor yang mempengaruhi AKB adalah Geographically Weighted Regression (GWR). Keunggulan model GWR dibandingkan dengan model regresi klasik adalah GWR mampu memberikan model secara lokal. Hasil penelitian menunjukkan bahwa faktor-faktor yang mempengaruhi AKB Jawa Timur adalah Jumlah Puskesmas, Presentase Penduduk Miskin, Berat bayi Lahir Rendah dan Presentase Penolong Persalinan.Model GWR mampu menjelaskan keragaman sebesar 83.06 persen. Kata kunci : Angka Kematian Bayi, Geographically Weighted Regression, Fix Gaussian
Pelatihan Pengujian Hipotesis Dengan Ms Excel Untuk Meningkatkan Kompetensi Guru Matematika Di SMA Kabupaten Gresik Gangga Anuraga; Wara Pramesti; Fenny Fitriani
Kanigara Vol 1 No 2 (2021): Kanigara
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/kanigara.v1i2.3963

Abstract

Pelaksanaan pengembangan diri secara berkelanjutan merupakan kewajiban yang harus dilajalankan oleh guru. Hal tersebut didasarkan pada UU No 14 Tahun 2005 tentang Guru dan Dosen. Satu kegiatan yang dapat dilakukan oleh guru adalah menghasilkan suatu publikasi ilmiah. Dalam hal tersebut, guru harus memahami cara pengolahan data. Akan tetapi, pemahaman guru mengenai pengolahan data tersebut masih sangat kurang. Hal tersebut didukung dengan kurangnya pelatihan yang didapatkan guru mengenai bagaimana cara pengolahan data yang sesuai dengan kebutuhan permasalahan karya ilmiah. Berdasarkan hal tersebut, dilaksanakan suatu program pelatihan peningkatan kemampuan penulisan karya ilmiah bagi guru. Kegiatan pelatihan ini bertujuan untuk meningkatkan pemahaman statistika khususnya pengujian hipotesis bagi guru. Metode yang digunakan pada pelatihan adalah dengan menggunakan metode diskusi dan praktek langsung mengenai pengujian hipotesis dengan menggunakan Ms Excel. Berdasarkan hasil preteset dan posttest peserta pelatihan, didapatkan bahwa pelatihan yang dilaksanakan mampu meningkatkan pemahaman pengujian hipotesis. Sehingga hasil kegiatan pengabdian ini mampu meningkatkan motivasi guru serta para guru mulai dapat merumuskan permasalahan yang dapat diselesaikan dengan pendekatan pengujian hipotesis statistik.
Pengenalan Statistika dan Aplikasinya pada Data Kesehatan bagi Siswa SMA Kristen Anak Panah Nabire Gangga Anuraga; Alfisyahrina Hapsery; Achmad Chikham Nouriel Rosyadi; Dwi Cahya Julia Kartikasari
Seminar Nasional Hasil Riset dan Pengabdian Vol. 6 (2024): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 6 Tahun 2024
Publisher : LPPM Universitas PGRI Adi Buana

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Abstract

Program pengabdian kepada masyarakat yang bertajuk "Pengenalan Statistika dan Aplikasinya pada Data Kesehatan bagi Siswa SMA Kristen Anak Panah Nabire" bertujuan untuk meningkatkan pemahaman siswa mengenai pentingnya statistika dalam analisis data kesehatan. Kegiatan ini dilakukan secara daring dan dirancang untuk memberikan wawasan dasar mengenai penggunaan statistika dalam konteks kesehatan melalui sosialisasi beberapa kasus nyata. Observasi awal dilakukan untuk mengidentifikasi tingkat pemahaman siswa serta kebutuhan teknologi untuk pelaksanaan program. Pelaksanaan pengabdian meliputi sosialisasi daring, presentasi studi kasus, diskusi interaktif, dan sesi tanya jawab yang difasilitasi oleh dosen dan mahasiswa Program Studi Statistika. Hasil kegiatan menunjukkan peningkatan pemahaman siswa terhadap konsep dasar statistika dan aplikasinya dalam bidang kesehatan, yang diindikasikan oleh respons positif dan peningkatan nilai post-test. Program ini diharapkan dapat memotivasi siswa untuk melanjutkan studi di bidang statistika atau bidang terkait lainnya, serta memperluas pengetahuan dan keterampilan mereka dalam analisis data kesehatan. Kata kunci: Statistika, Kesehatan, Pengabdian kepada Masyarakat, Analisis Data.
PEMODELAN ANGKA HARAPAN HIDUP DI INDONESIA MENGGUNAKAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) Izequela De Jesus Madeira; Pretesya Septiliani Syukur; Risa Mudji Istiawati; Gangga Anuraga
Seminar Nasional Hasil Riset dan Pengabdian Vol. 6 (2024): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 6 Tahun 2024
Publisher : LPPM Universitas PGRI Adi Buana

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Abstract

Abstrak Penelitian ini menganalisis hubungan antara angka harapan hidup dan faktor-faktor di seluruh provinsi Indonesia menggunakan metode Geographically Weighted Regression (GWR). Hasil menunjukkan estimasi yang berbeda-beda untuk setiap provinsi, menandakan variasi hubungan antara angka harapan hidup dan faktor-faktor yang memengaruhi. Variabel signifikan secara statistik terhadap angka harapan hidup di Indonesia adalah sanitasi layak (X₂), rata-rata lama sekolah (X₃), berat badan bayi rendah (X₄), imunisasi dasar lengkap (X₅), pengetahuan tentang stunting (X₆), dan jumlah perawat (X₇). Penelitian ini diharapkan memberikan informasi bermanfaat terkait faktor-faktor yang memengaruhi angka harapan hidup di Indonesia dengan menggunakan metode Geographically Weighted Regression (GWR). Kata kunci: Angka Harapan Hidup; Geographically Weighted Regression (GWR); Indonesia.
PEMODELAN FAKTOR – FAKTOR YANG MEMPENGARUHI ANGKA HARAPAN HIDUP (AHH) DI JAWA TIMUR TAHUN 2022 Erika Zahra Fitriananta; Pingky Febriyanti; Gangga Anuraga
Seminar Nasional Hasil Riset dan Pengabdian Vol. 6 (2024): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 6 Tahun 2024
Publisher : LPPM Universitas PGRI Adi Buana

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Abstract

AbstractThe Life Expectancy in East Java in 2022 reached 71.74, showing an increase from the previousyear. Several key factors influence the high or low life expectancy, including health indicators,environmental conditions, and socio-economic factors. To address issues related to life expectancy,one step taken is to identify the factors that significantly affect life expectancy. This study aims toidentify the factors that have a significant impact on life expectancy in East Java Province using aspatial regression approach. The analysis reveals that the Spatial Autoregressive (SAR) model isthe best with an AIC of 123.26. Significant factors in life expectancy include the proportion of thepopulation with national health insurance for the poor (????1) and the average years of schooling(X3).Keywords: Life Expectancy, East Java, Spatial Autoregressive (SAR).
PEMODELAN KUALITAS PENDIDIKAN TERHADAP TINGKAT PENGANGGURAN TERBUKA DI JAWA BARAT MENGGUNAKAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) Intan Amelia Haryanto; Saputri Dyah Pratiwi; Putri Amelia Divaio; Gangga Anuraga
Seminar Nasional Hasil Riset dan Pengabdian Vol. 6 (2024): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 6 Tahun 2024
Publisher : LPPM Universitas PGRI Adi Buana

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Abstract

The open unemployment rate in Indonesia ranked the second highest in Southeast Asia in 2022,with a rate of 5.86 percent, or approximately 8.47 million people. This study aims to analyze theimpact of education quality on the open unemployment rate in West Java Province using theGeographically Weighted Regression (GWR) method. The dependent variable in this study is theopen unemployment rate (TPT), while the independent variables include expected years ofschooling, labor force participation rate, number of poor people, literacy rate of the populationaged 15 and over, net enrollment rate, mobile phone usage by students aged 5-24 years over thepast three months, and average years of schooling. The data used are secondary data from theCentral Bureau of Statistics (BPS) and the West Java Provincial Education Statistics for 2022,covering 27 regencies/cities. The analysis results show that the GWR model provides betterestimates compared to the OLS model, with a higher R-Square value and a lower AIC. The factorsthat significantly affect the TPT in each regency/city in West Java Province are the average yearsof schooling and the net enrollment rate. This research is expected to contribute to theformulation of effective education policies to reduce the open unemployment rate in West JavaProvince.Keywords: Quality of Education, Open Unemployment Rate (TPT), Geographically WeightedRegression (GWR), Average Years of Schooling, Net Enrollment Rate (NER).
Topic Modeling for Twitter Users Regarding the "Ruanggguru" Application Arianto, Bagus Wicaksono; Anuraga, Gangga
Jurnal ILMU DASAR Vol 21 No 2 (2020)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v21i2.17112

Abstract

PT Ruang Raya Indonesia ("Ruangguru") is the largest and most comprehensive technology company in Indonesia that focuses on education-based services. In 2019 there were 15 million Ruangguru users and 300.00 teachers who had joined and were present in 32 provinces in Indonesia. It prepared a number of expansion strategies to become a company valued at more than US $ 1 billion in the next year or two. The purpose of this research is to classify the opinions of Ruangguru users about the services provided so that it can be an evaluation material in improving their services using the latent direchlet allocation method. The data used comes from a collection of tweets of Twitter users in Indonesia using the Twitter API. The Twitter account used in this study is @ruangguru. The results of the analysis showed that the public perception of Twitter users by using latent dirichlet allocation was formed into 28 topics.Keywords: latent dirichlet allocation, ruangguru, twitter.
Classification of Underdeveloped Areas in Indonesia Using the SVM and k-NN Algorithms Al Azies, Harun; Anuraga, Gangga
Jurnal ILMU DASAR Vol 22 No 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jid.v22i1.16928

Abstract

The determination or classification of underdeveloped areas essentially consists of classifying several observations taking into account existing indicators. The classification method used is K-Nearest Neighbor (k-NN) and Support Vector Machines (SVM). This study aims to analyze the accuracy of the classification between SVM and k-NN algorithms in the classification of underdeveloped areas in Indonesia. The data source used in this study is secondary data obtained from the Central Bureau of Statistics (BPS). The data used are 514 districs and municipalities of Indonesia. After analysis, the conclusion is that there are 122 districs and municipalities that are left behind out of a total of 514 districs and municipalities in Indonesia. The most underdeveloped areas are on the island of Papua, followed by the areas of the islands of Bali and Nusa Tenggara, and Sulawesi. Based on the results of the classification of underdeveloped areas using the method SVM with the kernel RBF has the best results with the parameters C = 1 and γ = 0.05 while the results of the classification of underdeveloped areas using the method k-NN obtains the best results with k = 15 Based on the results of classification of underdeveloped areas using the SVM and the k-NN method, including the level of classification is very good. The two methods compared have the same precision value of 92.2% and can be used to determine the classification of underdeveloped areas. Keywords: classification, machine learning, supervised learning, underdeveloped areas.
Pengukuran Kualitas Pendidikan Kabupaten Sidoarjo pada Jenjang SMP dengan Structural Equation Modeling Fitriani, Fenny; Pramesti, Wara; Anuraga, Gangga
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 10 No 1 (2024): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v10i1.6624

Abstract

The better the quality of education in a country, it can be considered that the quality of human resources in the country is qualified and can be a good development support for the country. However, there is a gap in education in Indonesia. This gap also occurs at a more regional scope such as districts/cities. One of the districts/cities experiencing education gaps is Sidoarjo district. This gap is thought to be influenced by differences in the factors that shape the quality of education in each school. Therefore, it is necessary to study how much influence each factor has on the quality of education. This article explores the quality of education in Sidoarjo district using structural equation modeling (SEM) at the junior high school level. The use of SEM is based on its ability to analyze two or more variables that cannot be measured directly. From the results of the analysis, it was found that infrastructure and socioeconomic factors have a significant effect on education quality. Infrastructure factors have a greater effect on the quality of education when compared to socioeconomic factors
GenAI Acceptance Modeling in Islamic Higher Education: An Integration of TAM and EVT Using PLS-SEM Fernanda, Jerhi Wahyu; Donasari, Renita; Anuraga, Gangga; Rahman, Fathur
Southeast Asian Journal of Islamic Education Vol 7 No 2 (2024): Southeast Asian Journal of Islamic Education, December 2024
Publisher : Faculty of Education and Teacher Training of UINSI Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21093/sajie.v7i2.9815

Abstract

Generative artificial intelligence (GenAI) technology is currently receiving special attention and has numerous benefits. In the education field, this technology can help obtain information quickly to complete a thesis. This research aims to conduct GenAI Modeling based on the Technology Accepted Model (TAM) and Expected Value Theory (EVT) framework using the Partial Least Square Structural Equation Model (PLS-SEM). The research used primary data obtained from surveys. The population was all Tarbiyah faculty students who took a thesis in the Even Semester of the 2023/2024 academic year with a total of 1266. The sample in this research was 191 students who were completing their thesis and had used Gen AI technology to help complete their thesis. The sampling technique used cluster random sampling with a procedure of dividing students into 8 clusters based on the study program. The research instrument used a questionnaire consisting of 5 latent variables: Perceived Usefulness, Perceived Ease of Use, Intrinsic Motivation, Perceived Value, and Behavioral Intention to Use. The results of the analysis using the PLS-SEM method showed that Intrinsic Motivation has a significant relationship with Perceived Ease of Use, and Intrinsic Perceived Usefulness and Perceived Value have a significant relationship with Behavioral Intention to Use. These results show that students choose GenAI Technology to help complete their thesis based on its benefits, such as making it easier to prepare backgrounds, research instruments, and data analysis steps, as well as providing insight into knowledge related to the topic being researched. The research results imply the need for policies regarding the use of GenAI technology for theses so that students are wiser in using GenAI technology.
Co-Authors Achmad Chikham Nouriel Rosyadi Agus Sulistiono Alfisyahrina Hapsery Anggi Emeliani Anggraeny, Zahro Dewi Antonito Hornay Cabral Anwardi Anwardi Arianto, Bagus Wicaksono Bambang Widjanarko Otok Betty Roosihermiatie Dito Anurogo, Dito Dwi Cahya Julia Kartikasari Edy Sulistiyawan, Edy Erika Zahra Fitriananta Faramaysty, Laura Sekar Fathur Rahman Fitriani, Fenny Hani Brilianti Rochmanto Hardani Prisma Rizky Harun Al Azies Indrasetianingsih , Artanti Indrasetianingsih, Artanti Intan Amelia Haryanto Izequela De Jesus Madeira Jerhi Wahyu Fernanda, Jerhi Wahyu Leonida, Katarina Rosa Lusia, Dwi Ayu M. A. Mauludin Madeira, Izequela De Jesus Mariana Yonasti Udus Muhammad Athoillah, Muhammad Permadina K. Arieska Pingky Febriyanti Pomalingo, Suwito pramesti, wara Pratiwi, Sekar Rini Pretesya Septiliani Syukur Putri Amelia Divaio Rabiatul Adawiyah Ratu Bunga Prawesti Arie Salim Renita Donasari, Renita Rezzy Eko Caraka Risa Mudji Istiawati Rizky, Hardani Prisma Sadewa, Arief Triatmaja Permana Sakhinah Abu Bakar Saputri Dyah Pratiwi Silfia Febriani Jamlean Silviana Maya Purwasih Tety Rachmawati Utami, Diva Aprilia Trisha Vidila Rosalina Wara Pramesti Wara Pramesti Wara Pramesti Zulhan Widya Baskara