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All Journal Jurnal Gaussian BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Kreativitas PKM METIK JURNAL Variance : Journal of Statistics and Its Applications Jurnal Varian Jurnal Riset Pembangunan : Media Hasil Penelitian dan Kajian Pembangunan Daerah Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Multica Science and Technology VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Research Applications in Community Services Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Jurnal Statistika dan Komputasi (STATKOM) Eksponensial STATISTIKA
Surya Prangga
Universitas Mulawarman
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Pendampingan Desain Infografis dengan Statistika dan Sains Data Bagi Siswa/Siswi MAN 1 Kota Samarinda Muhammad Fathurahman; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Darnah; Goenjatoro, Rito; Hayati, Memi Nor; Prangga, Surya; Siringoringo, Meiliyani; Oroh, Chiko Zet
Journal of Research Applications in Community Service Vol. 4 No. 3 (2025): Journal of Research Applications in Community Service
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/jarcoms.v4i3.5158

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan pendampingan desain infografis yang mengintegrasikan ilmu statistika dan sains data serta meingkatkan literasi data bagi siswa dan siswi MAN 1 Kota Samarinda. Dalam era digital yang ditandai dengan kemudahan akses informasi, masih terdapat kekurangan pemahaman di kalangan siswa mengenai pemanfaatan teknologi, khususnya dalam desain infografis berbasis statistika dan sains data. Infografis merupakan alat yang efektif untuk menyajikan informasi secara visual yang membantu mempercepat pemahaman data kompleks menjadi lebih mudah dipahami. Aplikasi Canva dipilih sebagai platform dalam pendampingan ini karena kemudahan penggunaannya, yang memungkinkan siswa untuk berkreasi secara mandiri. Berdasarkan hasil tes awal, siswa belum memanfaatkan dengan optimal pengembangan ilmu data sains dalam pembuatan desain infografis. Oleh karena itu, kegiatan ini dirancang untuk memberikan pemahaman dan keterampilan praktis kepada peserta agar mereka dapat menggunakan teknologi visual dalam mengelola dan menyampaikan informasi berbasis data dengan lebih efektif dan inovatif. Melalui metode pengabdian ini, diharapkan terjadi peningkatan pemahaman dan keterampilan dalam penggunaan desain infografis serta pemanfaatan sains data literasi siswa yang dapat diterapkan dalam kegiatan belajar mengajar, terutama dalam pengolahan dan penyajian data statistik.
Geographically Weighted Panel Regression Modelling of Dengue Hemorrhagic Fever Data Using Exponential Kernel Function Raihani, Risti; Sifriyani, Sifriyani; Prangga, Surya
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 4 (2023): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i4.16235

Abstract

Geographically Weighted Panel Regression (GWPR) model is a panel regression model applied to spatial data. This research takes the Fixed Effect Model (FEM) panel regression as the global model and GWPR as the local model for dengue hemorrhagic fever (DHF) in East Kalimantan Province data over the years 2018-2020. DHF is a disease that has the potential to become an extraordinary event which is accompanied by death. In comparison to Indonesia, East Kalimantan Province's DHF Incident Rate (IR) was high in 2020. East Kalimantan's IR is 60.6 per 100,000 population, compared to Indonesia's IR of 40.0 per 100,000 population. This research aims to obtain the GWPR model, as well as to acquire factors that affect DHF in East Kalimantan Province over the years 2018-2020 based GWPR model. The parameter of the GWPR model was estimated on each observation location using the Weighted Least Square (WLS) method, which is an Ordinary Least Square (OLS) with the addition of spatial weighting. The spatial weighting on the GWPR model was determined by the best weighting function between fixed exponential and adaptive exponential. The optimum weighting function with a minimum cross-validation (CV) value of 1.7317×106 is adaptive exponential. Based on GWPR parameter testing, factors that affect DHF are local and diverse in each 10 regencies/municipalities in East Kalimantan Province. These factors are population density, number of health facilities, percentage of proper sanitation use in the household, percentage of household with qualified drinking water sources, and percentage of health services. The coefficient of determination of the GWPR model obtains a higher value than the FEM, which is 95.33%. Based on the measurement of goodness using the coefficient of determination value, it can be concluded that GWPR is the best method to model the DHF data rather than the FEM.
IMPLEMENTASI METODE NEIGHBOR WEIGHTED K-NEAREST NEIGHBOR PADA PENGKLASIFIKASIAN STATUS GIZI BALITA DI WILAYAH KERJA PUSKESMAS WONOREJO KOTA SAMARINDA Aisha, Putri; Fathurahman, M.; Prangga, Surya
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 1 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss1page11-20

Abstract

Neighbor Weighted K-Nearest Neighbor (NWKNN) merupakan salah satu metode klasifikasi dalam machine learning yang dikembangkan dari metode K-Nearest Neighbor (KNN). Metode NWKNN memiliki kelebihan dibanding KNN, terutama untuk menangani masalah jumlah kelas yang tidak seimbang dalam pengklasifikasian data mining. Konsep dari metode NWKNN adalah pemberian bobot yang besar untuk kelas minoritas dan bobot yang kecil untuk kelas mayoritas. Metode NWKNN dalam penelitian ini diterapkan pada pengklasifikasian status gizi balita di Kota Samarinda. Menurut World Health Organization (WHO), Indonesia merupakan salah satu negara dengan prevalensi stunting pada balita tertinggi di regional Asia Tenggara pada Tahun 2005 sampai dengan 2017, dengan rata-rata prevalensi stunting pada balita sebesar 36,4%. Status gizi adalah salah satu faktor penyebab terjadinya stunting pada balita. Penelitian ini bertujuan mendapatkan hasil pengklasifikasian status gizi balita menggunakan metode NWKNN dan nilai akurasinya. Data yang digunakan adalah data balita di wilayah kerja Puskesmas Wonorejo Kota Samarinda Tahun 2022. Berdasarkan hasil klasifikasi status gizi balita menggunakan metode NWKNN, terdapat 93 balita yang diklasifikasikan secara tepat dari 128 balita dengan nilai akurasi sebesar 72,65%. Nilai akurasi ini termasuk cukup baik dan menunjukkan bahwa metode NWKNN layak digunakan untuk memprediksi ketepatan klasifikasi status gizi balita di wilayah kerja Puskesmas Wonorejo, Kota Samarinda. .
An Implementation of K-Medoids Method in Provincial ClusteringBased on Education Indicator Data Apridayanti, Annisa Zuhri; Fathurahman, M; Prangga, Surya
Jurnal Varian Vol. 7 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.3205

Abstract

Data mining is searching for interesting patterns or information by selecting data using specific techniques or methods. One method that can be used in data mining is K-Medoids. K-Medoids is a method used to group objects into a cluster. This research aimed to obtain the optimal number of clusters using the K-Medoids method based on Davies-Bouldin Index (DBI) validity on education indicators data by province in Indonesia in 2021. The results showed that the optimal number of clusters using the K-Medoids method based on DBI validity is 5 clusters. Cluster 1 consists of 1 province with a higher average dropout rate, average length of schooling, and well-owned classrooms compared to other clusters. Cluster 2 consists of 15 provinces with an average proportion of school libraries lower than Clusters 3 and 4 and higher than Clusters 1 and 5. Cluster 3 consists of 9 provinces with an average proportion of school libraries, proportions of school laboratories, net enrollment rates, and higher school enrollment rates than other clusters. Cluster 4 consists of 8 provinces with a higher average enrollment rate than the other clusters. Cluster 5 consists of 1 province with a higher average repetition rate and student-per-teacher ratio than other clusters.
Prediksi Curah Hujan di Kabupaten Berau Menggunakan Support Vector Regression Patiallo, Monalisa Randang; Fathurahman, M.; Prangga, Surya; Nadhilah Widyaningrum, Erlyne
EKSPONENSIAL Vol. 16 No. 2 (2025): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/v16i2.1508

Abstract

Machine learning is an analytical approach that is able to predict the output of a system based on patterns that have been formed from previous data. One of the machine learning methods used in this research is Support Vector Regression (SVR). SVR is the application of the support vector machine method in the case of regression. The concept of the SVR algorithm is to obtain a function with the minimum error rate so as to produce a good predictive value. The advantage of SVR lies in its ability to handle nonlinear data using the kernel functions. This study aims to determine the results of rainfall prediction in Berau Regency using the SVR method. The data used is rainfall data in Berau Regency from January 2014 to December 2023 as much as 120 data, and uses five predictor variables namely temperature, humidity, air pressure, wind speed, and solar irradiation. The kernel function used is a polynomial kernel with parameter values  and . The results showed that the best SVR model to predict rainfall in Berau Regency is the SVR model with parameter values  and . This model provides good prediction performance, with an RMSE value of 0,1786.
Pelatihan Penggunaan Software Q-GIS Pemetaan Spasial dan Pengenalan Program Regresi Nonparametrik di BPS Provinsi Kalimantan Timur Sifriyani, Sifriyani; Fauziyah, Meirinda; Dani, Andrea Tri Rian; Wahyuningsih, Sri; Prangga, Surya; Istiqomah, Nurul; Solikhah, Arifatus
Journal of Research Applications in Community Service Vol. 2 No. 4 (2023): Journal of Research Applications in Community Service
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/jarcoms.v2i4.2326

Abstract

Perkembangan teknologi saat ini harus didukung dengan kemahiran seorang ahli untuk adaptasi melalui visualisasi data dan penyajian hasil analisis kesimpulan yang tepat. Untuk mendukung kemahiran tersebut dilaksanakan sharing knowledge antar stakeholder dengan akademisi guna mendukung pembuatan kebijakan. Hal ini menjadi salah satu alasan pelaksanaan kegiatan pengabdian masyarakat. Beberapa software open sourceyang dapat digunakan untuk visualisasi data pemetaan yaitu Q-GIS dan analisisnya menggunakan I-Regs. Tujuan pelaksanaan kegiatan adalah memberikan kesempatan untuk sharing knowledge penggunaan Q-GIS dan I-Regs yang dapat digunakan untuk proses pengolahan data dan visualisasi bagi instansi terkait, memberikan pengenalan penggunaan software I-Regs, dan meningkatkan pengetahuan isu terkini bagi kedua belah pihak. Subjek (mitra) dari kegiatan ini 100 peserta yang terdiri dari staff BPS, mahasiswa dan dosen Jurusan Matematika FMIPA UNMUL. Berdasarkan hasil analisis diperoleh kesimpulan bahwa terdapat perbedaan rata-rata nilai ujian sebelum dan sesudah mengikuti pelatihan artinya kegiatan pelatihan memiliki pengaruh yang signifikan dalam meningkatkan kinerja para staff.
Co-Authors Aisha, Putri Anjani Anjani Annisa Hayatunnufus Annisa Zuhri Apridayanti Apridayanti, Annisa Zuhri Aprilianti, Rina Binda Aprilia Suryani Casuarina, Indah Putri Dani, Andrea Tri Rian Darnah Darnah Darnah, Darnah Dini Elizabeth Dwi Husnul Mubiin Erlyne Nadhilah Widyaningrum Fauziyah, Meirinda Febriana Rinda Sihotang Febriyanti, Nur Afifah Goenjatoro, Rito Hillidatul Ilmi Ika Purnamasari Ika Purnamasari Ilmi, Hillidatul Irfan Fadil Juliarto, Handy Kurniawan Khairun Nida Khoiril Anwar M. Fathurahman Mangalik, Gerald Meiliyani Siringoringo Memi Nor Hayati Memi Nor Hayati Memi Nor Hayati Memi Nor Hayati Muhammad Rais Muhammad Wahdeni Pramana Muhammad Wahdeni Pramana Nariza Wanti Wulan Sari Ni Luh Ari Yusasrini Nur Azizah, Noviani Nurul Istiqomah Oroh, Chiko Zet Padatuan, Aprianti Boma Patiallo, Monalisa Randang Permana, Jordan Nata Pratiwi, Reni Primantoro, Sudhan Purnaraga, Tirta Raihani, Risti Rito Goejantoro, Rito Sekar Nur Utami Selsa Amelia Sifriyani, Sifriyani Siringoringo, Meiliyani Siti Mahmuda Solikhah, Arifatus Sukamto, Ika Sumiyarsi Suyitno Suyitno Suyono, Ari Krisna Syamsiar, Syamsiar Wiwit Pura Nurmayanti Zarkasi, Rifka Nurfaiza