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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Mahasiswa Statistik Journal of Innovation and Applied Technology International Journal of Advances in Intelligent Informatics BAREKENG: Jurnal Ilmu Matematika dan Terapan Proceeding Simposium Nasional Kelautan dan Perikanan Wave: Jurnal Ilmiah Teknologi Maritim Jurnal Abdi: Media Pengabdian Kepada Masyarakat Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Bima Abdi: Jurnal Pengabdian Masyarakat Komatika: Jurnal Pengabdian Kepada Masyarakat MATHunesa: Jurnal Ilmiah Matematika Pattimura Proceeding : Conference of Science and Technology Bakti Sekawan : Jurnal Pengabdian Masyarakat Jurnal Umum Pengabdian Masyarakat (JUPEMAS) Kenduri: Jurnal Pengabdian Dan Pemberdayaan Masyarakat Journal of Community Empowerment Journal of World Future Medicine, Health and Nursing
Danang Ariyanto
Universitas Negeri Surabaya
Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy 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 Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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INTRODUKSI TEKNOLOGI PASCAPANEN SIMPLISIA KUNYIT HITAM DI DESA GETASANYAR, MAGETAN Purnomo, Aris Rudi; Purnama, Erlix Rakhmad; Ariyanto, Danang; Adiprahara, Mirwa Anggarani
Jurnal ABDI: Media Pengabdian Kepada Masyarakat Vol. 9 No. 2 (2024): JURNAL ABDI : Media Pengabdian Kepada masyarakat
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/abdi.v9i2.26860

Abstract

Introduksi Teknologi Pascapanen Simplisia Kunyit Hitam Di Desa Getasanyar, Magetan
COMPARISON OF RANDOM FOREST AND NAÏVE BAYES METHODS FOR CLASSIFYING AND FORECASTING SOIL TEXTURE IN THE AREA AROUND DAS KALIKONTO, EAST JAVA Pramoedyo, Henny; Ariyanto, Danang; Aini, Novi Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (591.915 KB) | DOI: 10.30598/barekengvol16iss4pp1411-1422

Abstract

Soil texture is used to determine airflow, heat, instability, water holding capacity, and the shape and structure of the soil structure. Soil texture as an important attribute that determines the direction of soil management must be modeled accurately. However, soil texture is a soil attribute that is quite difficult to model. It is a compositional data set that describes the particle size of the soil mineral fraction (sand, silt, and clay). The methods used to classification and predict soil texture with machine learning algorithms are Random Forest (RF) and Naïve Bayes (NB). The purpose of this study was to classify the distribution of soil texture using the Random Forest and Naïve Bayes methods to obtain the most accurate grouping results. This research was conducted in the area around Kalikonto River Basin, East Java Province. The performance-based tests show that the RF algorithm provides higher accuracy in predicting soil texture based on the Digital Elevation Model (DEM). The results of RF’s performance testing on training data and testing data gave an accuracy value of 92.55% and 87.5%. Classification using the Naïve Bayes method produces an accuracy value of 89.98% on testing data and 80.65% accuracy on training data.
LOGISTIC AND PROBIT REGRESSION MODELING TO PREDICT THE OPPORTUNITIES OF DIABETES IN PROSPECTIVE ATHLETES Ariyanto, Danang; Sofro, A'yunin; Hanifah, A’idah Nur; Prihanto, Junaidi Budi; Maulana, Dimas Avian; Romadhonia, Riska Wahyu
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1391-1402

Abstract

Diabetes is among the most prevalent chronic diseases globally, posing significant health risks to individuals. The identification of individuals at risk of developing these conditions is of paramount importance, particularly in high-stress and physically demanding activities such as athletic training. To find out the chances of a prospective athlete suffering from diabetes or not, models for binary data can be used, including logistic regression and probit models. The data used is primary data from prospective athletes in East Java, including prospective athletes from the State University of Surabaya and East Java Koni Athletes. This study aimed to develop an early prediction model for diabetes in prospective athletic candidates using a bivariate logistic and probit regression approach while considering the influence of socio-demographic and anthropometric factors. To selecting the best model between logistic regression and probit regression using Akaike’s Information Criterion (AIC) value, the smaller the AIC value gets means that the model is closer to the actual value or being the best model. Logistic regression has a smaller AIC value (129,85) than probit regression, this means that the logistic model is the best model. In this paper, an attempt is made to explore the use of logistic and probit regression to determine the factors which significantly influence the diabetes disease and we got that the logistic model as the best model because it has a smaller AIC value than the probit model. Based on the result of analysis and discussion, it can be concluded that there are two factors called mother’s job and finance which are influenced to the response variable, diabetes disease at significance level of 5%.
RAINFALL MODELING USING THE GEOGRAPHICALLY WEIGHTED POISSON REGRESSION METHOD Iriany, Atiek; Ngabu, Wigbertus; Ariyanto, Danang
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0627-0636

Abstract

Rainfall is an important parameter in understanding the climate and environment in the Malang Regency area. This research aims to model the distribution of rainfall in this region using the Geographically Weighted Poisson Regression (GWPR) method. GWPR is a spatial statistical approach that allows us to understand changes in inhomogeneous rainfall patterns throughout the Malang Regency area. Rainfall data collected from weather stations over several years was used in this study. We use GWR to study the relationship between various environmental factors, such as topography, vegetation, and land use, and rainfall distribution in Malang Regency. The results of the GWR analysis provide a deeper understanding of the spatial differences in the influence of these factors on rainfall. By applying GWR, we can find out how certain factors contribute to different rainfall patterns in certain regions. Rainfall modeling using the Geographically Weighted Poisson Regression (GWPR) method combines the power of Poisson regression in analyzing calculated data with the advantages of GWR in modeling spatial variability. GWPR allows us to identify and map rainfall distribution patterns that vary in geographic space. The main advantage of GWPR is its ability to provide local adjustments and capture the spatial variability associated with rainfall distribution. The results of the modeling analysis show that the GWPR is better, marked by the smallest AIC value, namely 336.84, compared to the generalized poisson regression model, namely 337.76.
ANALYSIS OF RAINFALL IN INDONESIA USING A TIME SERIES-BASED CLUSTERING APPROACH Sofro, A'yunin; Riani, Rosalina Agista; Khikmah, Khusnia Nurul; Romadhonia, Riska Wahyu; Ariyanto, Danang
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0837-0848

Abstract

Indonesia has a tropical climate and has two seasons: dry and rainy. Prolonged drought can cause drought disasters, and rain can cause floods and landslides. According to information from the Meteorology, Climatology, and Geophysics Agency (BMKG), natural disasters such as floods and landslides due to heavy rains have been a severe problem in Indonesia for the past five years. Different regional characteristics can affect the intensity of rain that falls in every province in Indonesia. It can be grouped to determine which provinces have similar characteristics to natural disasters due to rainfall. Later, it can provide information to the government and the public so that they are more aware of natural disasters. So, it is necessary to research and classify provinces in Indonesia for rainfall with cluster analysis. The data used is secondary rainfall data taken from the official BMKG website. Cluster analysis of rainfall in 34 provinces in Indonesia used hierarchical and non-hierarchical methods in this study. The approach that is used in this research limits our clustering of the data. Further research with a machine learning approach is recommended. For the clustering method, the agglomerative hierarchical method includes single, average, and complete linkage. The non-hierarchical method includes k-medoids and fuzzy c-means. The cluster analysis results show that the dynamic time warping (DTW) distance measurement method with the average linkage method has the most optimal cluster results with a silhouette coefficient value of 0.813.
STOCK PRICE PREDICTION AND SIMULATION USING GEOMETRIC BROWNIAN MOTION-KALMAN FILTER: A COMPARISON BETWEEN KALMAN FILTER ALGORITHMS Maulana, Dimas Avian; Sofro, A'yunin; Ariyanto, Danang; Romadhonia, Riska Wahyu; Oktaviarina, Affiati; Purnama, Mohammad Dian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp97-106

Abstract

Stocks have high-profit potential but also have high risk. Many people have ways to forecast stock prices. The Geometric Brownian Motion (GBM) method forecasts stock prices. The data used in this study are closing stock price data from July 1, 2021 to August 31, 2021 taken from Yahoo! Finance. The stocks used in this research are Bank Rakyat Indonesia (BBRI), Indofood Sukses Makmur (INDF), and Telkom Indonesia (TLKM). A strategy is carried out to improve prediction accuracy by utilising the Kalman Filter (KF). This research will compare the mean absolute percentage error (MAPE) value between GBM-KF, which was manually computed and computed using the Python library. As an example of this research, for BBRI stock, the high GBM MAPE value of 9.02% can be reduced to 3.52% with manually computed GBM-KF and 3.68% with Python library computed GBM-KF. Similarly, INDF and TLKM stocks are showing a significant reduction in MAPE values to deficient levels in some cases. The GBM-KF method employing manual computing may enhance the overall precision of stock price forecasting. Future research may enhance this study by using the GBM-KF model on alternative financial instruments, integrating supplementary market data, or evaluating its efficacy under extreme market conditions.
Peningkatan Kemampuan Analisis Statistik menggunakan Aplikasi R Studio Berbasis Open Source untuk Kebutuhan Penelitian Dosen di Fakultas Mipa Universitas Negeri Surabaya Ariyanto, Danang; Rachmadiarti, Fida
Jurnal Umum Pengabdian Masyarakat Vol 2 No 1 (2023): Jurnal Umum Pengabdian Masyarakat
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58290/jupemas.v2i1.73

Abstract

Bagi seorang ASN terutama dosen, analisis statistik sudah menjadi hal umum yang harus dikuasai untuk menyimpulkan hasil dari suatu penelitian. Selama ini, analisis statistik dipermudah prosesnya melalui aplikasi-aplikasi statistik yang digunakan untuk mengolahan data penelitian. Hal yang menjadi isu dari kegiatan analisis statistik ini yaitu selama ini masih banyak dosen di Fakultas MIPA Unesa menggunakan aplikasi statistik secara ilegal atau tidak berlisensi resmi. Jika hasil dari analisis dalam penelitian dibuat dalam jurnal nasional/internasional dan terdeteksi oleh pemilik paten maka dapat dituntut hukuman karena karena melakukan pelanggaran UU No 28 tahun 2014 terkait hak cipta dan penjiplakan mentah-mentah (Slavish Imitation). Hal ini sangat berbahaya bagi karir dosen khususnya dalam lingkup penelitian dan karya ilmiah. Apabila isu tersebut diabaikan, maka pelayanan publik yang maksimal tidak dapat tercapai dan juga menghambat terwujudnya core value ASN Ber-AKHLAK. Saat ini sedang berkembang aplikasi analisis statistik berbasis open source yaitu R Studio yang mana pengguna dapat berkontribusi dalam menambahkan atau memodifikasi menu yang ada melalui packages yang tersedia dan bersifat gratis. Berdasarkan hal tersebut, disusun rancangan kegiatan terkait pelatihan analisis statistik dengan menggunakan aplikasi berbasis open source yaitu R Studio. Internalisasi nilai dasar serta peran dan fungsi ASN tersebut diharapkan mampu membentuk seorang ASN yang profesional dan tentunya dapat meningkatkan hasil penelitian dosen dilingkungan FMIPA Unesa. Hasil dari kegiatan ini menunjukkan bahwa peserta pelatihan mampu mengusai Aplikasi R Studio untuk kebutuhan analisis data. Lebih dari 80% peserta puas dengan kegiatan pelatihan dan mampu melakukan analisis data dengan R Studio.
PELATIHAN DAN PRAKTIK PEMBUATAN PUPUK ORGANIK DARI KOTORAN HEWAN DI DESA BOCEK, KABUPATEN MALANG Iriany, Atiek; Ridlo, Mahmuddin; Setiawan, Adi; Waziiroh, Elok; Widodo, Agung Sugeng; Ariyanto, Danang
Journal of Community Empowerment Vol 4, No 3 (2025): Desember
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jce.v4i3.36738

Abstract

ABSTRAKPetani kopi di wilayah Gunung Arjuna, Desa Bocek, Kecamatan Karangploso, Kabupaten Malang menggunakan pupuk kimia untuk perawatan tanaman, karena faktor kemudahan mendapatkan pupuk kimia. Sementara, UD. Kopi Java Indonesia merupakan roaster kopi yang berperan sebagai buyer hasil panen kopi lereng Gunung Arjuna memiliki kebutuhan kualitas produk green bean tersertifikasi organik untuk pasar ekspor. Melalui Program Doktor Mengabdi Pengembangan Kemitraan (DM-PK), Direktorat Riset dan Pengabdian kepada Masyarakat Universitas Brawijaya (DRPM UB) menyelenggarakan pendampingan pertanian organik dan keberlanjutan (sutainability). Tujuan kegiatan adalah meningkatkan kesiapan petani kopi dalam sertifikasi organik dengan pelatihan dan praktik pembuatan pupuk organik dari kotoran hewan. Petani kopi sejumlah 20 orang dan 1 orang pemilik roster kopi menjadi mitra DM-PK. Metode kegiatan terdiri dari pelatihan sertifikasi organik, praktik pembuatan pupuk organik dari kotoran hewan dan evaluasi kesiapan implementasi kopi organik. Mitra kegiatan DM-PK UB terdiri dari 20 petani kopi lereng Arjuna dan 1 roaster kopi. Waktu pelaksanakan kegiatan DM-PK UB pada bulan Oktober dan November 2025 di CV Kopi Java Indonesia, Desa Bocek, Karangploso, Malang. Penjelasan materi diikuti praktik secara langsung oleh petani memerikan manfaat dan dapat meningkatkan kesiapan sertifikasi kopi organik. Hasil evaluasi dengan nilai overall 4.1 menunjukkan petani kopi lereng Gunung Arjuna “Siap” untuk implementasi kopi organik.Kata kunci: Kopi; Pupuk; Organik; Pelatihan.ABSTRACTCoffee farmers in the Mount Arjuna area, Bocek Village, Karangploso District, Malang Regency, use chemical fertilizers for plant care due to the ease of obtaining them. Meanwhile, UD. Kopi Java Indonesia, a coffee roaster that acts as a buyer for coffee harvests from the slopes of Mount Arjuna, needs quality organically certified green beans for the export market. Through the Doctoral Program for Partnership Development (DM-PK), the Directorate of Research and Community Service at Brawijaya University (DRPM UB) provides assistance in organic farming and sustainability. The objective of the activity is to improve the readiness of coffee farmers for organic certification through training and practice in making organic fertilizer from animal manure. Twenty coffee farmers and one coffee roster owner are DM-PK partners. The activity method consists of organic certification training, practice in making organic fertilizer from animal manure, and evaluation of readiness for implementing organic coffee. DM-PK UB's partners consist of 20 coffee farmers from the slopes of Arjuna and one coffee roaster. The DM-PK UB program will be implemented in October and November 2025 at CV Kopi Java Indonesia, Bocek Village, Karangploso, Malang. The material will be explained, followed by hands-on practice by farmers, highlighting the benefits and improving readiness for organic coffee certification. The evaluation results, with an overall score of 4.1, indicate that coffee farmers on the slopes of Mount Arjuna are "Ready" for organic coffee implementation. Keywords: Coffee; Fertilizer; Organic; Training.
Literasi Keuangan dan Profesi Aktuaris di Sekolah Kota/Kabupaten Mojokerto Zatadini, R. A. Diva; Permata, Reny Amalia; Oktaviarina, Affiati; Sofro, A’yunin; Maulana, Dimas Avian; Ariyanto, Danang; Khumairo, Nabilatul; Nofriyadi, Rizki
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2025): Desember
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v5i2.907

Abstract

The development of the financial industry requires human resources with adequate financial literacy and risk management understanding. However, teachers and students in Mojokerto still face challenges in the form of low financial literacy, particularly in personal financial management, long-term financial planning, and understanding risk concepts, as well as limited awareness of the actuarial profession as a strategic career path in the financial sector. This community service program aims to enhance the financial literacy of teachers and students through interactive and educational approaches, focusing on the introduction of basic financial literacy concepts and the actuarial profession as a strategic career opportunity in the financial industry. The activities include interactive seminars, case studies, simulations, and discussion sessions to strengthen participants’ comprehension. The program is expected to improve participants’ knowledge and skills in financial literacy, broaden their understanding of the actuarial profession. Based on the results of the pre-test and post-test, it can be concluded that the learning activities conducted had a positive impact on increasing participants’ knowledge, as evidenced by the rise in their average scores from 70.89 in the pre-test to 96.44 in the post-test. Overall, this program contributes to building financially literate school communities and preparing younger generations to face future economic challenges more effectively.
Analisis Pelaksanaan Pelatihan Infografis Data Dengan Microsoft Excel Bagi Guru Kabupaten/Kota Pasuruan A'yunin Sofro; Riska Wahyu Romadhonia; Affiati Oktaviarina; Danang Ariyanto; Mutia Eva Mustafidah
Komatika: Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2025): Mei 2025
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat, Institut Informatika Indonesia Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/komatika.v5i1.1078

Abstract

Dalam era teknologi yang berkembang pesat, pemanfaatan perangkat lunak seperti Microsoft Excel menjadi krusial, terutama di bidang pendidikan. Meski populer, sebagian besar guru di Kabupaten/ Kota Pasuruan belum sepenuhnya memaksimalkan Microsoft Excel untuk infografis data. Tim Pengabdian Kepada Masyarakat (PKM) mengusulkan kolaborasi dalam "Pelatihan Infografis data dengan Microsoft Excel Bagi Guru Kabupaten/Kota Pasuruan" tahun 2024, bertujuan meningkatkan pemahaman dan keterampilan guru sejalan dengan visi lembaga untuk meningkatkan mutu pendidikan. Pelatihan difokuskan pada pembuatan infografis data melalui fungsi Excel, meningkatkan keterampilan guru di Kabupaten/Kota Pasuruan dalam memanfaatkan perangkat lunak ini. Pelatihan ini telah dilaksanakan oleh tim secara luring pada hari Sabtu, 13 Juli 2024 bertempat di SMPN 1 Bangil. Pelatihan diikuti oleh 24 guru di beberapa SD di Pasuruan dan berjalan lancar. Pada saat pelatihan dilakukan penilaian dengan pretest dan posttest, berdasarkan hasil tes tersebut akan dilakukan pengujian menggunakan uji t, dengan hasil yang diperoleh adalah nilai thitung lebih besar dari ttabel dan terjadi kenaikan rata-rata nilai pretest (30,83) ke posttest (67,92) yang menunjukkan bahwa pelatihan yang dilakukan berhasil meningkatkan pemahaman dan kemampuan peserta, yang ditunjukkan oleh kenaikan nilai. Hasil survei evaluasi kegiatan menunjukkan bahwa secara keseluruhan, peserta memberikan penilaian yang sangat positif terhadap kegiatan PKM ini, dengan rata-rata poin keseluruhan sebesar 4.8. Hal tersebut menunjukkan bahwa materi dan penyampaian dalam kegiatan ini berhasil menarik minat dan memenuhi kebutuhan peserta, dengan mayoritas merasa antusias, termotivasi, dan mampu meningkatkan kemampuan mereka dalam membuat infografis data menggunakan Microsoft Excel.
Co-Authors A'yunin Sofro Achmad Efendi Adiprahara, Mirwa Anggarani Affi Oktaviarina AFFIATI OKTAVIARINA Agung Sugeng Widodo Annisa Nur Afifah Kusuma Sayekti Arditama Putra Rochmanullah Asri Maharani Atiek Iriany A’yunin Sofro Bambang Dwi Argo Chai, Napat Dhanny Septimawan Sutopo Dian Cahya Cahya Rini Dian Cahya Rini Dinda Galuh Guminta Elok Waziiroh Endah Budi Rahaju Fida Rachmadiarti Hanifah, A’idah Nur Henny Pramoedyo Henny Pramoedyo Ibnu Febry Kurniawan Ichsan Maulana Ismachul Diana Masruroh Junaidi Budi Prihanto Khikmah, Khusnia Nurul Khumairo, Nabilatul Khusnia Nurul Khikmah Krit, Pong Marhen Andan Prasetyo Maulana, Dimas Avian Mitakda, Maria Bernadetha Moh. Fadli Mona Triwulandari Muhamad Firdaus Muhammad Mahdy Al Akbar Mutia Eva Mustafidah Nabila Ayunda Sovia Napat Chai NI WAYAN SURYA WARDHANI Ni Wayan Surya Wardhani Ni Wayan Surya Wardhani Ninda Kartika Putri Nofriyadi, Rizki Nonik Indrawatingsih Novi Nur Aini Novi Nur Aini, Novi Nur Permata, Reny Amalia Pong Krit Prihanto, Junaidi Budi Purnama, Erlix Rakhmad Purnama, Mohammad Dian Purnomo, Aris Rudi Redi Bintarto Riani, Rosalina Agista Ridlo, Mahmuddin Riska Wahyu Romadhonia Riskyana Dewi Intan Puspitasari Romadhonia, Riska Wahyu Romi Setiawan Safinaz Berkhafi Jannah Jannah Sapto Wiratno Satoto sihabudin sihabudin Silvia Eka Sofro, A'yunin Sofro, A’yunin Solimun Solimun Sukamto, Ika Sumiyarsi Wigbertus Ngabu Yana Shanti Yuliani Puji Astuti Yuni Rosita Dewi Yurizka Melia Sari Zatadini, R. A. Diva