Article Per Year (5 Year)
p-Index From 2020 - 2025
1.325
P-Index
This Author published in this journals
All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Bioeksperimen: Jurnal Penelitian Biologi BAREKENG: Jurnal Ilmu Matematika dan Terapan Komatika: Jurnal Pengabdian Kepada Masyarakat Urecol Journal. Part D: Applied Sciences Proceeding of International Conference on Humanity Education and Society Radiant : Journal of Applied, Social, and Education Studies
Nirwana, Muhammad Bayu
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
Optimalisasi Produksi Triterpenoid Dari Sangketan (Achyranthes aspera) Dengan Budidaya Organik Fanani, Zaenal; Farida, Umi; Nirwana, Muhammad Bayu
Bioeksperimen: Jurnal Penelitian Biologi Vol 7, No 1: Maret 2021
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/bioeksperimen.v7i1.9482

Abstract

Kebutuhan akan bahan baku obat semakin meningkat sejalan dengan pemanfaatan obat tradisional yang semakin meningkat. Sangketan (Achyranthes aspera) adalah salah satu tanaman obat potensial, mengingat tanaman ini memiliki kandungan senyawa aktif yang bermanfaat untuk kesehatan. Triterpenoid merupakan salah satu kandungan metabolit sekunder utama dari Sangketan. Tujuan penelitian ini adalah untuk mengetahui kombinasi dari komposisi media tanam dan aplikasi fertigasi dengan pupuk organik, yang dapat mendukung produksi senyawa triterpenoid dari Sangketan secara optimal. Pada budidaya Sangketan diberikan perlakuan perbandingan komposisi media tanah + arang sekam padi 1:1; 1:2 dan 2:1. Sedangkan aplikasi fertigasi menggunakan pupuk organik kotoran kambing, dengan konsentrasi 1kg pupuk organik per 5 liter air, dosis 60 ml per tanaman dan diaplikasikan setiap dua minggu. Sangketan di panen setelah 4-5 bulan, kemudian dilakukan analisis kualitatif kandungan triterpenoid menggunakan metode kromatografi lapis tipis. Data yang diperoleh diaplikasikan menggunakan metode simplex lattice design (SLD), untuk memperoleh kombinasi yang optimal. Data kualitatif ekstrak Sangketan yang mengandungan senyawa triterpenoid, telah dianalisis dengan pereaksi kloroform dan H2SO4 pekat, ditandai dengan adanya lapisan warna coklat kemerahan. Data kuantitatif rendemen ekstrak Sangketan diaplikasikan menggunakan metode simplex lattice design, diperoleh persamaan Y = 8,94(Arang) + 11,585(Tanah) + 14,26(Arang.Tanah). Kandungan triterpenoid pada ekstrak Sangketan dibuktikan menggunakan kromatografi lapis tipis, berupa bercak warna abu-abu di bawah sinar UV 254 nm dengan nilai Rf 0,65.
Waiting Time to Get a Job: Comparison of Survival Analysis of Semi-Parametric & Parametric Models Harmajati, Firdaus; Nirwana, Muhammad Bayu; Sugiyanto
Urecol Journal. Part D: Applied Sciences Vol. 3 No. 1 (2023)
Publisher : Konsorsium LPPM Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53017/ujas.248

Abstract

Education is very important along with the advancements in technology that required people to have in-depth and quality knowledge. A person who can get a job usually has a good educational background. How long it takes a person to get a job is affected by many factors. In statistical sciences, factors affecting how long a person gets a job after graduating from college can be studied using survival analysis. Survival analysis is a regression method used to examine the factors that influence the occurrence of one or more events. Several survival models can be used to estimate the impact of survival factors on how long a person gets a job, including the cox proportional hazard model and the accelerated failure time model. The cox proportional hazard model belongs to the semi-parametric approach where the hazard function essentially follows the non-parametric model while the independent variables follow the parametric model. The accelerated failure time model is a parametric model based on data distribution that can predict the time of the event in observed data. This study was conducted by comparing the cox proportional hazard model and the accelerated failure time model with the logistics distribution to determine if the conditions or data types are better identified with the cox proportional hazard model or the failure time model. time. The results obtained by considering the minimum AIC value, the accelerated failure time model has a better logistics distribution than the cox proportional hazard model.
Pemodelan Produksi Padi di Provinsi Jawa Timur dengan Regresi Non Parametrik B-Spline Handajani, Sri Sulistijowati; Pratiwi, Hasih; Susanti, Yuliana; Respatiwulan, Respatiwulan; Nirwana, Muhammad Bayu; Mahmudah, Arik
PYTHAGORAS Jurnal Pendidikan Matematika Vol 18, No 2: December 2023
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v18i2.67475

Abstract

Kebutuhan pangan merupakan kebutuhan primer masyarakat yang harus terpenuhi. Makanan pokok yang banyak dikonsumsi masyarakat Indonesia salah satunya beras. Beras yang berasal dari padi selalu diusahakan memenuhi untuk kebutuhan konsumsi masyarakat terutama di sekitarnya. Jawa Timur adalah salah satu provinsi penyumbang terbesar produksi padi di Indonesia.  Oleh sebab itu perlunya melihat pengaruh faktor-faktor iklim di beberapa wilayah produksi padi terbesar di provinsi Jawa Timur yaitu kabupaten Tuban, Nganjuk dan Gresik terhadap besarnya produksi padi di wilayah tersebut. Tujuan penelitian ini adalah menganalisis faktor-faktor meliputi suhu, kelembaban, curah hujan dan luas panen padi terhadap jumlah prodiksi padi. Data diambil dari website BMKG dan BPS tahun 2020-2022 di Kabupaten Tuban, Nganjuk dan Gresik. Metode analisis yang digunakan dengan memodelkan regresi non parametrik B-spline dengan beberapa kombinasi titik knot dari beberapa variable prediktor yang menghasilkan GCV terkecil dari kemungkinan banyaknya titik knot yang dicobakan. Hasil pemodelan mendapatkan knot optimum pada variabel X1 (suhu) berorde 2 dengan tiga titik knot bernilai 23,45584; 24,32467; 26,93116. Knot optimum pada variabel X2 (kelembaban) berorde 2 dengan satu titik knot bernilai 83,3828. Knot optimum pada variabel X3 (curah hujan) berorde 2 dengan dua titik knot bernilai 5,177247 dan 15,51238. Knot optimum pada variabel X4 (luas panen padi) berorde 2 dengan satu titik knot bernilai 16939,25. Nilai GCV minimum yang diperoleh adalah 18462458. Hasil analisis menunjukkan semua variable berpengaruh signifikan walaupun untuk variable iklim terdapat beberapa segmen yang kurang signifikan, dengan nilai adjusted R-Square sebesar 0,987. The need for food is a primary requirement of society that must be fulfilled. One of the staple foods widely consumed by the Indonesian society is rice. Rice, which comes from paddy fields, is always cultivated to fufill  the consumption needs of the community, especially in the surrounding areas. East Java is one of the largest contributors to rice production in Indonesia. Therefore, it is necessary to examine the influence of climate factors in several rice-producing regions in East Java, namely Tuban, Nganjuk, and Gresik regencies, on the level of rice production in those areas. The aim of this research is to analyze factors such as rainfall, humidity, temperature, and rice cultivation area on rice production quantity.  The data was collected from BMKG (Meteorology, Climatology, and Geophysics Agency) and BPS (Central Statistics Agency) websites for the years 2020-2022 in Tuban, Nganjuk, and Gresik regencies. The analysis method used involves modeling non-parametric B-splines with various combinations of knot points from multiple predictor variables, resulting in the smallest Generalized Cross-Validation (GCV) among the possible knot points tested. The modeling results obtained the optimal knots for variable X1 (temperature) of order 2 with three knot points at values 23.45584, 24.32467, and 26.93116. The optimal knot for variable X2 (humidity) of order 2 was at one knot point with a value of 83.3828. The optimal knots for variable X3 (rainfall) of order 2 were two knot points with values of 5.177247 and 15.51238. The optimal knot for variable X4 (rice cultivation area) of order 2 was at one knot point with a value of 16,939.25. The minimum GCV value obtained was 18,462,458. The analysis results indicate that all variables have a significant influence, although for climate variables, there were some segments that were less significant, with an value adjusted R-Square of 0.987.
COMPARISON OF ROBUST REGRESSION RESULTS OF SCALE (S) ESTIMATION AND METHOD OF MOMENT (MM) ESTIMATION ON THE CLOSING PRICE OF ENERGY SECTOR STOCKS IN 2022 Hilyatul Hilwy, Sarah; Susanti, Yuliana; Nirwana, Muhammad Bayu
International Conference on Humanity Education and Society (ICHES) Vol. 3 No. 1 (2024): Third International Conference on Humanity Education and Society (ICHES)
Publisher : FORPIM PTKIS ZONA TAPAL KUDA

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The development of the company is undoubtedly inseparable from financial factors. The company will issue shares that investors will purchase. Investors will consider the state of the company they invest in investment activities. Fundamental analysis can assess the company's condition by calculating company ratios. The existence of fundamental analysis can help investors make decisions. Capital market movements often experience fluctuations or extreme events in the stock market that cause outliers in stock price data. Outliers in the data can be overcome by using robust regression to reduce the impact of outliers on the data. This analysis uses S and MM estimations with Tukey Bisquare weights to estimate the model. Energy sector stock closing price data will be tested for classical assumptions, including normality, homoscedasticity, autocorrelation, and multicollinearity tests. If the energy sector stock closing price data does not meet normality, detect outliers and continue estimating data using S and MM estimations. The best model to estimate the data is the MM estimation with an adjusted R-Square value of 99.86%, fulfilling the parameter significance test, namely the t-test and F-test.
Pelatihan Manajemen dan Visualisasi Data Menggunakan Excel untuk Guru Matematika SMP di Kabupaten Karanganyar: Data Management and Visualization Training using Excel for Junior High School Mathematics Teacher in Karanganyar Regency Nirwana, Muhammad Bayu; Pratiwi, Hasih; Susanti, Yuliana; Respatiwulan, Respatiwulan; Handayani, Sri Sulistijowati; Wijaya, Andreas Rony; Pratama, Alfito Putra Fajar; Ferawati, Kiki
Komatika: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2024): November 2024
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.v4i2.1023

Abstract

Literasi statistik merupakan kemampuan untuk memahami beragam informasi statistik yang dimunculkan di berbagai media. Kemampuan ini meliputi keterampilan dalam menginterpretasikan grafik dan tabel, serta mampu membaca dan memahami statistik dalam berita, media, jajak pendapat, dan lain-lain. Kabupaten Karanganyar merupakan salah satu kabupaten di Provinsi Jawa Tengah yang berbatasan dengan Kota Surakarta dan termasuk sebagai wilayah Karesidenan Surakarta. Pengetahuan mengenai literasi statistik dan implementasinya di wilayah Kabupaten Karanganyar merupakan hal yang penting untuk disampaikan kepada masyarakat, karena berkaitan langsung dengan pemahaman mengenai informasi data statistika dan bagaimana merepresentasikannya. Sebagai ilmu yang mempelajari tentang cara pengumpulan, analisis, dan pengambilan keputusan dari data, pengetahuan tentang statistika merupakan ilmu penunjang yang penting untuk dimiliki oleh masyarakat. Sebagai sasaran peningkatan literasi statistika kali ini Grup Riset Statistika dan Sains Data Bidang Lingkungan dan Kesehatan Program Studi Statistika FMIPA UNS akan melaksanakan pengabdian masyarakat dengan bentuk pelatihan untuk guru dan siswa SMP di Kabupaten Karanganyar melalui forum Musyawarah Guru Mata Pelajaran (MGMP) Matematika. Literasi statistik memerlukan pengetahuan tentang analisis dan visualisasi data yang diberikan untuk meningkatkan pemahaman terkait penerapan metode statistika dengan menggunakan Excel yang sudah banyak dikenal oleh masyarakat.
Cox Proportional Hazard Regression Analysis to Identify Factors Influencing Student Study Period: Analisis Regresi Cox Proportional Hazard untuk Mengidentifikasi Faktor-Faktor yang Memengaruhi Lama Studi Mahasiswa Anggraira, Attilah Suci; Nirwana, Muhammad Bayu; Subanti, Sri
RADIANT: Journal of Applied, Social, and Education Studies Vol. 4 No. 2 (2023): RADIANT: Journal of Applied, Social, and Education Studies
Publisher : Politeknik Harapan Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52187/rdt.v4i2.169

Abstract

The length of study is the time needed by students to complete their education, which is calculated from the time they enter school until they graduate. In general, a student is considered to graduate on time if he has studied for no more than four years. This study aims to identify the factors that influence the length of study of students using survival analysis with the Cox Proportional Hazard regression model. This study used data from 146 students who were randomly selected enrolled at Sebelas Maret University, Faculty of Mathematics and Natural Sciences, batch 2017 and 2018. The research variables consisted of nine predictor variables that were thought to influence student length of study. The nine factors are gender, major, GPA, university entrance, scholarship, part-time work, region of origin, organization, and committee. The results show that the following factors that significantly influence the length of study of students are majors and GPA. The results of this study have important benefits for higher education administrators and policy makers to develop strategies that can help students complete study programs on time.
TRUNCATED SPLINE SEMIPARAMETRIC REGRESSION TO HANDLE MIXED PATTERN DATA IN MODELING THE RICE PRODUCTION IN EAST JAVA PROVINCE Handajani, Sri Sulistijowati; Pratiwi, Hasih; Respatiwulan, Respatiwulan; Susanti, Yuliana; Nirwana, Muhammad Bayu; Nareswari, Lintang Pramesti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2597-2608

Abstract

Climate change can affect rice production through changes in temperature, precipitation patterns, extreme weather events, and atmospheric carbon dioxide levels. A statistical model can be used to understand the correlation between rice production and factors that affect it. The existence of some patterns that are formed from independent variables and others that do not show data patterns due to volatility in weather element data makes semiparametric regression modeling more appropriate. In forming a parametric model, the data pattern needs to be regular to make the model more precise. Irregular data patterns are more appropriately modeled with nonparametric regression models. The existence of several patterns formed from independent variables to their dependent variables, and several others, does not show a particular pattern due to the volatility in climate data, making truncated spline semiparametric regression modeling more appropriate to use. This research aims to model rice production in several regions in East Java Province in 2022 using a semiparametric regression model. The data used were from the Meteorology, Climatology, and Geophysics Agency and the Central Statistics Agency for East Java Province in 2022. The response variable is the rice production (tons) in 2022 in Tuban, Gresik, Nganjuk, Malang, Banyuwangi, and Pasuruan Regency (Y). The predictor variables are paddy harvested area (hectares), average temperature (℃), humidity (percent), and rainfall (mm). The semi-parametric spline truncated regression model is obtained by combining the parametric and non-parametric models based on truncated splines. The analysis showed a spline truncated semiparametric regression model with a combination of knot points (3,3,1) with a minimum GCV value of 12,642,272. The variables significantly affecting rice production were rice harvest area, temperature, air humidity, and rainfall, with an adjusted value of 98.522%.
Co-Authors Andreas Rony Wijaya Anggraira, Attilah Suci Handajani, Sri Sulistijowati Handayani, Sri Sulistijowati Harmajati, Firdaus Hilyatul Hilwy, Sarah Jamhari Jamhari Kiki Ferawati Mahmudah, Arik Nareswari, Lintang Pramesti Pratama, Alfito Putra Fajar pratiwi, hasih Respatiwulan, Respatiwulan Sri Subanti SUGIYANTO Umi Farida Yuliana Susanti, Yuliana