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All Journal PROSIDING SEMINAR NASIONAL CENDEKIAWAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Variance : Journal of Statistics and Its Applications Science Map Journal Tensor: Pure and Applied Mathematics Journal Jurnal Satya Informatika Sinergi: Jurnal Pengabdian Kepada Masyarakat Seminar Nasional Inovasi Teknologi Kocenin Jurnal Pengabdian Kepada Masyarakat Parameter: Jurnal Matematika, Statistika dan Terapannya BAKTI : Jurnal Pengabdian Kepada Masyarakat PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya
Laamena, Novita Serly
Program Studi Statistika, Universitas Pattimura
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Journal : Science Map Journal

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PERBANDINGAN MODEL REGRESI WEIBULL DAN REGRESI COX PROPOSIONAL HAZARD Mayawi Mayawi; Nurhayati Nurhayati; Novita Serly Laamena; Ariestha Widyastuty Bustan; Munazat Salmin; Taufan Talib
Science Map Journal Vol 4 No 2 (2022): Science Map Journal
Publisher : Jurusan Pendidikan MIPA FKIP Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jmsvol4issue2pp49-60

Abstract

This study aims to determine the model of Acute Myocardial Infarction using the Weibull Regression and Cox Proportional Hazard Regression methods to determine the factors that significantly influence the length of time for recovery of acute myocardial infarction patients. The results of this study indicate that the factors that significantly influence the recovery time of acute myocardial infarction patients are age, onset, number of secondary diagnoses and duration of pain. Based on the AIC value, the Weibull regression model is the best regression model because the AIC value is smaller, namely 292.883 compared to the Cox Proportional Hazard regression model with an AIC value of 493.3971
PENERAPAN ANALISIS KLASTER HIERARKI UNTUK PENGELOMPOKAN KABUPATEN/ KOTA DI PROVINSI MALUKU BERDASARKAN STATUS PENDIDIKAN Novita Serly Laamena; Taufan Talib
Science Map Journal Vol 5 No 1 (2023): Science Map Journal
Publisher : Jurusan Pendidikan MIPA FKIP Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jmsvol5issue1pp10-18

Abstract

One of the main goals of education is to develop potential and to educate individuals. Education is an effort to help the souls of students both physically and mentally towards a better human civilization. This research was conducted to group districts/cities in Maluku province based on educational status using hierarchical cluster analysis with the single linkage, average linkage and ward's methods. The results showed that clustering using the single linkage and average linkage methods was almost the same, while clustering using the ward's method had quite different results. Clustering using the single linkage and average linkage methods shows that Ambon city is the only city that always has its own cluster and does not join other districts/cities. This shows that the city of Ambon has an education status that is quite different from other districts/cities in Maluku Province. Regencies/cities that are always in the same cluster, namely cluster 1, both in the single linkage method, average linkage and the ward's method are Tanimbar Islands Regency, Southeast Maluku Regency, Central Maluku Regency and Tual City
PERAMALAN VOLUME IMPOR MIGAS DI INDONESIA MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE Latupeirissa, Indri Kezia; Laamena, Novita Serly; Bustan, Ariestha W; Talib, Taufan
Science Map Journal Vol 6 No 2 (2024): Science Map Journal
Publisher : Jurusan Pendidikan MIPA FKIP Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jmsvol6issue2pp44-55

Abstract

Indonesia is one of the countries with abundant natural resources. Mining is one of the most important factors that need to be maintained to improve the welfare of its people and also contributes to the majority of state revenues in the non-tax sector, such as oil and gas. The development of Indonesia's oil and gas sector is very dynamic. Indonesia and countries in the world must adjust production, consumption, domestic and foreign policies from time to time due to changes in world oil prices in order to achieve people's welfare. In addition, our oil and gas production and reserves will continue to decline over time, so we have to import oil and gas. The increase in oil and gas imports also has an impact on the strengthening of the Rupiah exchange rate, so that demand for domestic currency also increases. Therefore, it is necessary to have a forecast to determine the volume of oil and gas imports in Indonesia for the next year. This study aims to predict the volume of oil and gas imports in Indonesia using one of the time series forecasting methods, namely the ARIMA method. The data used is oil and gas import data from January 2019 to December 2023 sourced from the Central Statistics Agency. The results of the study show that the right method for oil and gas import data is the ARIMA Model (0,1,1). The forecast results from January to June 2024 are 4557.45 tons, 4582.71 tons, 4608.04 tons, 4633.44 tons, 4658.91 tons and 4684.45 tons. The MAPE value of 9.31% indicates that the forecast results are very accurate
Co-Authors Bosar Panjaitan Bosar Panjaitan Bustan, Ariestha W Bustan, Ariestha Widyastuty Bustan, Ariestha Widyastuty Faisal Zuli Henry Junus Wattimanela Hiariey, Arlene H. Istiqomah Sumadikarta Latupeirissa, Indri Kezia Lusye Bakarbessy Mayawi Mayawi Munazat Salmin Noya Van Delsen, M.S. Noya Van Delsen, Marlon Stivo Nurhayati Nurhayati Nurhayati Nurhayati Ronald John Djami Ronald John Djami Rosalina Salhuteru Rumanama, Siti Adnan Salhuteru, R. Sanlly Joanne Latupeirissa Saputra, Lamanisa Rasid Sedubun, Debora Ribka Taufan Talib Teguh Budi Santoso Wattimanela, H. J. Yonlib Weldri Arnold Nanlohy Yudistira Yudistira Yusriani Sapta Dewi