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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 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) Journal of World Future Medicine, Health and Nursing Journal of Community Empowerment
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 Health Professions Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Enhanced diabetes and hypertension prediction using bat-optimized k-means and comparative machine learning models Sofro, A'yunin; Ariyanto, Danang; Prihanto, Junaidi Budi; Maulana, Dimas Avian; Romadhonia, Riska Wahyu; Maharani, Asri; Oktaviarina, Affi; Kurniawan, Ibnu Febry; Khikmah, Khusnia Nurul; Al Akbar, Muhammad Mahdy
International Journal of Advances in Intelligent Informatics Vol 11, No 4 (2025): November 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i4.1816

Abstract

This research aims to develop an analytical approach to classification statistics. The proposed approach combines machine learning with optimization. Considering the urgency of research related to exploring the best methods to apply to sports data. This study proposes a novel framework that combines the k-means clustering results with the bat algorithm to optimize performance prediction for athletes in Indonesia. The proposed method aims to explore the data by comparing the classification performance of random forests, extremely randomized trees, and support vector machines. We conducted a case study using primary data from 200 respondents at Surabaya State University and the East Java National Sports Committee. The accuracy results in this study indicate that, based on the performance evaluation metric, the best approach is random forest clustering using k-means with bat algorithm optimization, achieving 81.25% accuracy, compared with other machine learning approaches. This research contributes to the field of classification statistics by introducing a novel hybrid framework that integrates machine learning, clustering, and optimization techniques to improve predictive accuracy, particularly in sports analytics. Beyond sports science, the proposed approach can be adapted to other domains that require robust performance prediction and decision support, such as health analytics, educational assessment, and human resource selection.
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.
TRADITIONAL LOGISTIC REGRESSION AND MACHINE LEARNING APPROACHES OF SOCIODEMOGRAPHIC AND ANTHROPOMETRIC FACTORS INFLUENCING HYPERTENSION IN ATHLETES Sofro, A'yunin; Maharani, Asri; Mustafidah, Mutia Eva; Khikmah, Khusnia Nurul; Oktaviarina, Affiati; Ariyanto, Danang
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1125-1138

Abstract

The type and intensity of exercise performed by athletes play an important role in affecting blood pressure stability, putting them at risk of developing hypertension. Hypertension, or high blood pressure, is a medical condition in which the blood pressure in the arteries rises above normal limits. Hypertension in athletes becomes an essential factor in real cases if not detected early. Therefore, this study aims to model and analyse the sociodemographic and anthropometric factors that influence the incidence of hypertension. The data used in this study are primary data from 200 athlete selection participants at the University of Surabaya and the Indonesian National Sports Committee (INSC) of East Java. This research method proposes to compare the traditional approach with machine learning to prove the accuracy comparison of the model's goodness, where both approaches are proposed by considering the novelty proposed through the machine learning approach but still maximizing the traditional approach. The proposed methods are binary logistic regression, binary logistic regression with the addition of random effects, highly randomized tree, and support vector classification. The binary logistic regression model is better than the binary logistic regression model with random effects, random trees, and support vector classification because the accuracy, sensitivity, specificity, and F1-score value (68.5%, 69%, 68%, and 68.8%) is highest than the others. Other results showed that the waist circumference variable, the father's occupation variable, and the salary variable significantly affected hypertension at the 5% significance level.
SPATIAL INTERPOLATION OF RAINFALL DATA USING COKRIGING AND RECURRENT NEURAL NETWORKS FOR HYDROLOGICAL APPLICATIONS IN SURABAYA, INDONESIA Ariyanto, Danang; Sofro, A'yunin; Puspitasari, Riskyana Dewi I; Romadhonia, Riska Wahyu; Ombao, Hernando
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1185-1198

Abstract

Urban hydrological challenges, such as flooding and water resource management, require accurate rainfall data to support sustainable development. This study investigates the use of Recurrent Neural Networks (RNN) for spatial interpolation of monthly rainfall data across 31 districts in Surabaya, Indonesia, and compares its performance with the geostatistical method Cokriging. Elevation data were incorporated as an additional variable to account for geographical variability. The dataset was divided into training (26 locations) and testing (5 locations) subsets, with testing locations treated as missing data points to simulate real-world conditions. The results show that the RNN-based interpolation method achieved progressively lower Root Mean Square Error (RMSE) values from January (48.65) to April (13.78), indicating higher accuracy compared to the Cokriging method. These findings underscore the potential of RNN in addressing data gaps and spatial variability, offering robust solutions for hydrological applications in urban environments. This approach not only supports flood risk mitigation strategies but also contributes to optimizing drainage systems and water resource planning. Further research is recommended to incorporate additional environmental variables and extend the application to broader spatial and temporal contexts.
ANALISIS SPASIAL TEMPORAL INDEKS KETAHANAN PANGAN MENGGUNAKAN GEOGRAPHICALLY TEMPORALLY WEIGHTED REGRESSION DAN KLASTER FUZZY DI NUSA TENGGARA TIMUR Iriany, Atiek; Ayunda Sovia, Nabila; Ngabu, Wigbertus; Ariyanto, Danang
MATHunesa: Jurnal Ilmiah Matematika Vol. 13 No. 3 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v13n3.p9-17

Abstract

Ketahanan pangan di Indonesia masih menghadapi tantangan serius akibat ketimpangan sosial-ekonomi dan infrastruktur antarwilayah yang berfluktuasi antarperiode. Provinsi Nusa Tenggara Timur (NTT) menjadi contoh nyata, dengan capaian Indeks Ketahanan Pangan (IKP) antar kabupaten/kota menunjukkan variasi signifikan pada periode 2018–2022. Penelitian ini bertujuan menganalisis pengaruh faktor sosial-ekonomi dan infrastruktur terhadap IKP dengan mempertimbangkan heterogenitas spasial-temporal. Metode yang digunakan adalah Geographically and Temporally Weighted Regression (GTWR) untuk menangkap dinamika pengaruh variabel pada dimensi ruang dan waktu, serta Fuzzy C-Means untuk mengelompokkan wilayah berdasarkan pola pembangunan. Hasil penelitian menunjukkan bahwa Angka Partisipasi Sekolah (APS) berpengaruh negatif signifikan terhadap IKP, PDRB per kapita berpengaruh positif meskipun terbatas, akses air minum layak berfluktuasi, sedangkan rasio elektrifikasi konsisten berpengaruh positif signifikan. Analisis Fuzzy C-Means menghasilkan tiga klaster utama: (1) wilayah dengan APS sedang dan IKP relatif tinggi, (2) wilayah dengan APS tinggi namun IKP menengah hingga rendah, dan (3) wilayah dengan APS rendah dan IKP rendah yang merepresentasikan daerah tertinggal. Temuan ini menegaskan bahwa pembangunan di NTT masih menghadapi ketimpangan spasial-temporal, sehingga kebijakan tidak dapat bersifat seragam melainkan harus disesuaikan dengan karakteristik lokal.
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 AFFIATI OKTAVIARINA Agung Sugeng Widodo Al Akbar, Muhammad Mahdy Annisa Nur Afifah Kusuma Sayekti Arditama Putra Rochmanullah Asri Maharani Atiek Iriany Ayunda Sovia, Nabila A’yunin Sofro Bambang Dwi Argo Chai, Napat Dhanny Septimawan Sutopo Dian Cahya Cahya Rini Dian Cahya Rini Elok Waziiroh Fernandes, Adji Achmad Rinaldo Fida Rachmadiarti Hanifah, A’idah Nur Henny Pramoedyo Henny Pramoedyo Ibnu Febry Kurniawan Khikmah, Khusnia Nurul Khumairo, Nabilatul Krit, Pong Marhen Andan Prasetyo Maulana, Dimas Avian Mitakda, Maria Bernadetha Moh. Fadli Muhamad Firdaus Mustafidah, Mutia Eva Mutia Eva Mustafidah Ni Wayan Surya Wardhani NI WAYAN SURYA WARDHANI Ni Wayan Surya Wardhani Nofriyadi, Rizki Novi Nur Aini Novi Nur Aini, Novi Nur Oktaviarina, Affi Ombao, Hernando Permata, Reny Amalia Prihanto, Junaidi Budi Purnama, Erlix Rakhmad Purnama, Mohammad Dian Purnomo, Aris Rudi Puspitasari, Riskyana Dewi I Putri, Henida Ratna Ayu Redi Bintarto Riani, Rosalina Agista Ridlo, Mahmuddin Riska Wahyu Romadhonia Romadhonia, Riska Wahyu Romi Setiawan Sapto Wiratno Satoto sihabudin sihabudin Sofro, A'yunin Sofro, A’yunin Solimun Solimun Sukamto, Ika Sumiyarsi Wigbertus Ngabu Yana Shanti Yunita Prameswari, Yunita Zatadini, R. A. Diva