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All Journal E-Jurnal Matematika Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI SAINSMAT Chemica: Jurnal Ilmiah Kimia dan Pendidikan Kimia LaGeografiA Journal of Marine Research Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Jurnal Environmental Science Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang PENGABDI: Jurnal Hasil Pengabdian Masyarakat Jurnal Dedikasi ARRUS Journal of Mathematics and Applied Science Journal of Mathematics: Theory and Applications Pedagogy : Jurnal Pendidikan Matematika Chemistry Education Review Seminar Nasional Pengabdian Kepada Masyarakat SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam INOVASI: Jurnal Hasil Pengabdian Masyarakat Indonesian Journal of Fundamental Sciences Venn: Journal of Sustainable Innovation on Education, Mathematics and Natural Sciences Seminar Nasional Hasil Penelitian LP2M UNM Ininnawa: Jurnal Pengabdian Masyarakat Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) SMART: Jurnal Pengabdian Kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS)
Wahidah Sanusi
Jurusan Matematika FMIPA Universitas Negeri Makassar, 90224
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Analisis Survival terhadap Kekambuhan Pasien Penderita Asma menggunakan Pendekatan Counting Process: (Studi Kasus: Balai Besar Kesehatan Paru Masyarakat Makassar) Abdy, Muhammad; Sanusi, Wahidah; Aulia, Hikma
Journal of Mathematics, Computations and Statistics Vol. 5 No. 2 (2022): Volume 05 Nomor 02 (Oktober 2022)
Publisher : Jurusan Matematika FMIPA UNM

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Survival analysis or survival analysis is a set of statistical procedures to analyze data with the time until a particular event occurs as a response variable. Observe events such as death and recurrence of the disease. Survival analysis used for recurring data is the counting process approach for identic and stratified cox recursion events for non-identical recursion events. An example of identic recursion data is patient recurrence data of non-communicable diseases such as asthma. The type of research carried out is applied research with a quantitative approach, namely by taking or collecting the necessary data and analyzing it using the counting process approach method. The counting process approach method is a specific method used for identical reccuring event, each recurring event will be counted as a new and independent event. The variables used in the study were Time, Status, Gender, Age, Smoker, Allergies, Obesity, and Atopic History. Based on the results of this study, it was found that the factors of gender, age, and atopic history had an effect on the recurrence of asthmatic patients with a significance level of less than 10%.
Pengelompokan Daerah Rawan Kriminalitas di Sulawesi Selatan Menggunakan Metode K-means Clustering Irwan, Irwan; Sanusi, Wahidah; Saman, Febriyanto
Journal of Mathematics, Computations and Statistics Vol. 5 No. 1 (2022): Volume 05 Nomor 01 (April 2022)
Publisher : Jurusan Matematika FMIPA UNM

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This research is an applied research that emphasizes how to carry out cluster analysis mathematically, knowing how to apply k-means clustering, and the characteristics of each group of crime-prone areas. The simulation data used in this study is data obtained from the Central Statistics Agency (BPS) of South Sulawesi Province. The data was then analyzed by the K-means clustering method. The results of the study show that there are four characteristics of each group of crime-prone areas in South Sulawesi. Group 1 is categorized as a crime-safe area, Group 2 is categorized as a crime-prone area, group 3 is categorized as a crime-safe area, and group 4 is categorized as an area that is quite prone to crime.
Model Generalized Poisson Regression (GPR) dan Penerapannya pada Angka Pengangguran bagi Penduduk Usia Kerja di Provinsi Sulawesi Selatan Ihsan, Hisyam; Sanusi, Wahidah; Ulfadwiyanti, Risna
Journal of Mathematics, Computations and Statistics Vol. 3 No. 2 (2020): Volume 03 Nomor 02 (Oktober 2020)
Publisher : Jurusan Matematika FMIPA UNM

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This study discusses the formation of the Generalized Poisson Regression (GPR) model and its application to the unemployment rate for the working age population in South Sulawesi Province. This type of research is applied research that uses the Poisson regression model, namely Poisson regression and GPR models. The response variabel used is the total unemployment rate at working age which includes the workforce in South Sulawesi Province in 2017. The predictor variables used are the percentage of the workforce on the working age population, the Human Development Index, the percentage of work on the labor force, population density, and economic growth. This research uses the Maximum Likelihood Estimation (MLE) method to estimate parameters and produce a GPR model. The predictor variables which have a significant influence are the Human Development Index and the percentage of work on the labor force.
Suatu Kajian Tentang B-Aljabar Sanusi, Wahidah; Abdy, Muhammad; Sidjara, Sahlan; Asni, Asriani Arsita
Journal of Mathematics, Computations and Statistics Vol. 3 No. 2 (2020): Volume 03 Nomor 02 (Oktober 2020)
Publisher : Jurusan Matematika FMIPA UNM

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This research is a literature studies that aims at reviewing the concepts and properties of B-Algebras. The concept of B-Algebras in this article is based on research that has been done by Neggers and Kim and Allen. All discussions in this article use the firm sets, both finite sets and infinite sets. As a result, more complete evidence of the properties of B-Algebras can be given and its relationship with the group. A group with a specific operation and has as an identity element is a B-Algebras. Moreover, a number of group theorems can be derived into B-Algebra such as natural mapping and the First Isomorphism Theorems which in their proof have similarities to the proofs of groups while still using the properties of B-Algebra itself.
Model Matematika SIR Sebagai Solusi Kecanduan Penggunaan Media Sosial Side, Syafruddin; Sanusi, Wahidah; Rustan, Nur Khaerati
Journal of Mathematics, Computations and Statistics Vol. 3 No. 2 (2020): Volume 03 Nomor 02 (Oktober 2020)
Publisher : Jurusan Matematika FMIPA UNM

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This study aims to build the SIR (Susceptible - Infected - Recovered) model as a solution of social media addiction with the assumption that students who recover from addiction of social media because they have high selfcontrol. This model is divided into three classes: namely class of students who have potential to use social media, class of students who are addicted to social media, and class of students who have high selfcontrol. The data used are primary data that was obtained by distributing questionnaires to 145 students of mathematics departement FMIPA UNM class of 2017, 2018, and 2019. The simulation results of the SIR type model produce a basic reproduction number (R0) of 1.451136 which means that the number of students who are addicted to the use of social media will increase in a certain period of time.
Model Vector Autoregressive Exogenous dan Aplikasinya pada Curah Hujan Kota Makassar Sukarna; Wahidah Sanusi; Serly Diliyanti Restu Ningsih
Journal of Mathematics, Computations and Statistics Vol. 2 No. 02 (2019): Volume 02 Nomor 02 (Oktober 2019)
Publisher : Jurusan Matematika FMIPA UNM

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This type of research is applied research that aims to predict rainfall in Makassar city VARX model using. The model was developed from the VARX model VAR by adding exogenous factors that influence the precipitation like Sea Surface Temperature (SST) Nino 3.4, the Southern Oscillation Index (SOI), and Dipole Mode Index (DMI). Rainfall data used in this researrchis the monthly rainfall data in Makassar city from 1987-2016 year on three stations, namely Panaikang, Paotere, and Biring Romang as endogenous factors. This data is retrieved from the Great Hall the Meteorology, Climatology, and Geophysics Region IV Makassar. VARX model formation through several stages, namely : test stasioneritas, the determination of the optimal lag length, test causality, diagnostic models, the establishment of the model of forecasting and VARX. The result showed that the average peak rainfall in Makassar city occurred in March and then come down exponentially. In May the chance of occurrence of very little rain.The model obtained in this study deserves to be used to predict rainfall in the next period.Keywords: , , ,
Pemodelan Matematika SEIR Penyebaran Penyakit Pneumonia pada Balita dengan Pengaruh Vaksinasi di Kota Makassar Syafruddin Side; Wahidah Sanusi; Nurul Aulia Bohari
Journal of Mathematics, Computations and Statistics Vol. 4 No. 1 (2021): Volume 04 Nomor 01 (April 2021)
Publisher : Jurusan Matematika FMIPA UNM

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This study aims to build a model of the spread of pneumonia in SEIR (Susceptible-Exposed-Infected-Recovered) toddlers, analyze the model, and determine the minimum proportion of vaccinations. The data used are data on the number of pneumonia sufferers in toddlers in Makassar City in 2019.The results obtained by the SEIR mathematical model of pneumonia in the form of ordinary differential equation systems; addiction free balance points and addiction balance points which are both stable; basic reproduction numbers for simulations without vaccination greater than 1, which means that the disease still exists in the population, while basic reproduction numbers for simulations with vasksination less than 1, which means the disease will disappear and not spread from the population.
Pemodelan Pencemaran Udara sebagai Solusi Penurunan Kualitas Udara Menggunakan Generalized Space-Time Autoregressive di Kota Makassar Farhan, Muhammad; sanusi, wahidah; Ihsan, Hisyam
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4304

Abstract

This study discusses the application of the Generalized Space-Time Autoregressive (GSTAR) model to analyze air pollution in Makassar City, focusing on NO2 and SO2 pollutants from 2017 to 2023. Data were collected from four different sampling locations: transportation, industry, residential, and office areas. This study uses inverse distance weighting and cross-correlation normalization to develop the forecasting model. The analysis results show that the GSTAR (1;0;2) model for NO2 pollutants and GSTAR (1;0;1) for SO2 pollutants are the best models, with residuals meeting the assumptions of white noise and normal distribution. Therefore, this model can be used to predict future air pollution levels.
Deteksi informasi hoaks vaksin covid-19 Di media sosial twitter menggunakan jaringan syaraf tiruan backpropagation Syam, Rahmat; Sanusi, Wahidah; SYahnur, Andi Aulia
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4433

Abstract

Hoaks di bidang kesehatan adalah hal yang berbahaya terutama pada suatu pandemi Covid-19 di mana keadaan masih belum pasti. Hoaks terkait vaksin Covid-19 banyak tersebar di media sosial salah satunya di media sosial Twitter. Pembaca umumnya dapat melakukan pendeteksian terhadap suatu pesan Twitter yang termasuk hoaks secara manual seperti dengan membaca berita di media massa resmi. Namun dengan kecepatan dan banyaknya informasi yang tersebar di Twitter membuat cara manual sulit dilakukan. Karena itu, deteksi informasi hoaks secara otomatis dapat menjadi solusi untuk kesulitan tersebut. Penelitian ini mendeteksi informasi hoaks vaksin Covid-19 menggunakan metode jaringan syaraf tiruan backpropagation dengan mengklasifikasi teks pesan Twitter ke dalam dua kelas yaitu hoaks dan bukan hoaks. Tujuan dari penelitian ini yaitu untuk mengetahui model arsitektur jaringan syaraf tiruan backpropagation dalam mendeteksi hoaks vaksin Covid-19 di media sosial Twitter dan tingkat akurasi yang didapatkan dari model tersebut menggunakan 7,130 data tweet yang dikumpulkan dengan data scraping dengan bahasa pemrograman Python dan dilabeli secara manual kemudian diterapkan preprocessing data dan pembobotan TF-IDF sebelum teks tweet diproses ke dalam model. Hasil penelitian ini menunjukkan bahwa model dengan performa paling baik dimiliki oleh metode backpropagation model pembagian 20% data latih dan 80% data uji yang menggunakan dua hidden layer (3, 5) yaitu mencapai tingkat akurasi sebesar 77.12% dengan tingkat error sebesar 22.88%, di sisi lain nilai AUC dari kurva ROC yang dihasilkan sebesar 0.7414 yaitu masuk pada kategori klasifikasi cukup. Kata Kunci: Hoaks, Twitter, Vaksin Covid-19, Jaringan Syaraf Tiruan, Backpropagation Hoaxes in the health field are dangerous, especially in a Covid-19 pandemic where the situation is still uncertain. Hoaxes related to the Covid-19 vaccine are widely spread on social media, one of which is Twitter. Readers can generally detect a Twitter message that is a hoax manually, such as by reading news in the official mass media. However, the speed and amount of information spread on Twitter makes manual methods difficult to do. Therefore, automatic detection of hoax information can be a solution to this difficulty. This research detects hoax information about the Covid-19 vaccine using the backpropagation artificial neural network method by classifying Twitter message text into two classes, namely hoaxes and non-hoaxes. This study aims to determine the backpropagation artificial neural network architecture model in detecting Covid-19 vaccine hoaxes on Twitter social media and the level of accuracy obtained from the model used 7,130 tweet data collected by data scraping using Python programming language and manually labeled then applied data preprocessing and TF-IDF weighting before the tweet text is processed into the model. The results of this study show that the model with the best performance is owned by a backpropagation model method of a division of 20% training data and 80% test data using two hidden layer (3, 5), which achieves an accuracy rate of 77.12% with an error rate of 22.88%, on the other hand, the AUC value of the resulting ROC curve is 0.74 that is included in the fair classification category. Keywords: Hoax, Twitter, Covid Vaccine, Artificial Neural Network, Backpropagation
Struktur Komposisi Vegetasi Hutan Mangrove di Teluk Laikang Kabupaten Takalar Arfan, Amal; Rakib, Muhammad; Sanusi, Wahidah
LaGeografia Vol 23, No 1 (2024): Oktober
Publisher : UNIVERSITAS NEGERI MAKASSAR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/lageografia.v23i1.66701

Abstract

This study aims to examine the structure of mangrove forest vegetation composition in Laikang Bay, Takalar Regency. The sampling technique used purposive sampling. The sampling technique used purposive sampling. Data collection techniques were carried out by means of observation, survey, and documentation. The data analysis technique performed is the analysis of the structure and composition of mangrove forests which include Density, Relative Density, Frequency, Relative Frequency, Dominance, Relative Dominance, Important Value Index, and Diversity Index. The results showed that the types of mangroves at the research site were Sonneratia alba, Rhizopora apiculata, Rhizopora mucronata, Bruguiera gymnorrhiza, Avicennia alba, Avicennia marina. The measurement results show that the condition of tree-level mangrove density at point 1 amounted to 1333 ind/ha, point 2 amounted to 2050 ind/ha, and point 3 amounted to 2950 ind/ha in good condition with very tight criteria. The frequency of mangrove species classified as almost can be found at each point of the plot and dominance with the lowest basal area of 603.19 cm2 of Bruguiera gymnorrhiza and the largest is 7655.27 cm2 of Rhizopora mucronata. The highest Index of Importance at all points is found in the type of Rhizopora mucronata.  The Diversity Index of the entire research location shows a medium-to-low level of uniformity.AbstrakPenelitian ini bertujuan untuk mengkaji tentang struktur komposisi vegetasi hutan mangrove di Teluk Laikang Kabupaten Takalar. Teknik pengambilan sampel menggunakan purposive sample. Teknik pengambilan sampel menggunakan purposive sampling. Teknik pengambilan data dilakukan dengan cara observasi, survei dan dokumentasi. Teknik analisis data yang dilakukan adalah analisis struktur dan komposisi hutan mangrove yang diantaranya  Kerapatan, Kerapatan Relatif, Frekuensi, Frekuensi Relatif, Dominansi, Dominansi Relatif, Indeks Nilai Penting dan Indeks Keanekaragaman. Hasil penelitian menunjukan bahwa  Jenis Mangrove pada lokasi penelitian  Sonneratia alba, Rhizopora apiculata, Rhizopora mucronata, Bruguiera gymnorrhiza, Avicennia alba, Avicennia marina. Hasil pengukuran menunjukan bahwa kondisi kerapatan mangrove tingkat pohon pada titik 1 sebesar 1333 ind/ha, titik 2 sebesar 2050 ind/ha dan titik 3 sebesar 2950 ind/ha dalam kondisi baik dengan kriteria sangat rapat. Frekuensi jenis mangrove yang tergolong hampir dapat ditemukan di setiap titik plot dan dominansi dengan basal area terendah sebesar 603.19 cm2 dari jenis Bruguiera gymnorrhiza dan yang terbesar adalah 7655.27 cm2 dari Rhizopora mucronata. Indeksi Nilai Penting tertinggi di seluruh titik terdapat pada jenis Rhizopora mucronata.  Indeks Keseragaman keseluruhan lokasi penelitian menunjukan tingkat keseragaman sedang-hingga rendah.
Co-Authors A. Armansyah AHMAD FAUZAN RIDHA SUJIONO ahmad yani Ahmad Zaki Ahmad Zaki AHMAD ZAKI Ahmad Zaky Alimuddin Alimuddin Tampa Amal Amal Amal Amal Amal Arfan, Amal Amni Rasyidah Andi Abidah Andi Diki Nurbaldatun Islam Andini, Reski Anggi Ananda Putri Annas, Suwardi Arkas, Amaliah Nurul Asdar Asdar Asdar Asmi, Nurul Asni, Asriani Arsita Asriani Arsita Asni Astuti - Aswi, Aswi Aswi, Aswi Aulia, Hikma Awi Dassa, Awi Beby Fitriani Besse Nur Afni Besse Nur Afni Bohari, Nurul Aulia Diki Nurbaldatun Islam Elma Selviana Darwis Febriyanto Saman Fitriyani Fitriyani Fitriyani Folorunso, Serifat Adedamola H. Hasriani Hafilah Hardiono Hafilah. H Harisahani, Nur Hasan Basri Hasanah, Afifatun Hasnawiyah, Hasnawiyah Hasriani Hikma Aulia Hisyam Ihsan Ihsan U, Wa Irma Al Ika Pratiwi Ilham Minggi Irham Aryandi Basir Irham Aryandi Basir Irma Aswani Ahmad, Irma Aswani Irwan Irwan Irwan Irwan Irwan Irwan Irwan Janide, Anugrah Kahvi Nurani Kaito, Nurlaila Katrina Pareallo Lisca Palerina Mudinillah, Adam Muh. Idris Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Abdy Muhammad Arif Tiro, Muhammad Arif Muhammad Danial Muhammad Danial Muhammad Danial Muhammad Farhan Muhammad Isbar Pratama Muhammad Rakib Muhammad Rakib Muhammad Rakib Muhammad Syahrir Muhjria, Muhjria Mukarram, Trys Musliati Musliati Mustati'atul Waidah Maksum N Nurfadillah N Nurwakia Nasrullah Nasrullah Nirwana, St. Risma Ayu Nur Anny S. Taufieq Nur Anny S. Taufieq Nur Anny S. Taufieq Nur Anny Suryaningsih Taufieq Nur Fajri Setiawan Nur Hikmayanti Syam Nur Khaerati Rustan Nur Ridiawati Nur Ridiawati Nurani, Kahvi Nurazizah Nurdin, Nur Izzah Nurfadillah Nurhilaliyah, Nurhilaliyah Nurul Aulia Bohari Nurul Aulia Bohari Nurul Fadilah Syahrul Oktaviana Oktaviana Padjalangi, Andi Muhammad Ridho Yusuf Sainon Andi Patasik, Ghadytha Marie Lucia Pertiwi, Ika Pince Salempa R. Rusli Rabiatul Adawiyah Rabiatul Adawiyah Rahman, Muhammad Fatur Rahmat Setiawan Rahmat Syam Rahmawati, Rahmawati Reski Andini Risna Ulfadwiyanti Rosidah Rosidah Ruliana Rustan, Nur Khaerati S Sukmawati Sahlan Sidjara Saiful Bahri Saiful Bahri Saman, Febriyanto Sari, Yulfiana Serly Diliyanti Restu Ningsih Serly Diliyanti Restu Ningsih Setiawan, Nur Fajri Sidjara, Sahlan Siti Helmyati Sudarmin Sudarmin Sukarna Sukarna Sukarna Sukarna Sukarna Sulaiman Sulaiman Suwardi Annas Syafruddin Side SYahnur, Andi Aulia Syuhri, Ajrian Takdir, Nurfajri Hamdani Talib, Dr. Ahmad Tampa, Alimuddin Taty Sulastri Taty Sulastri Taty Sulastri Thaha, Irwan Trys Mukarram Ulfadwiyanti, Risna Usman Mulbar Utami Priono Wahyuliani, Dwi Wahyuni, Maya Sari Wulandari, Natalia Puspita Yusuf S.A.P., Andi Muh. Ridho