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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Jurnal Pendidikan Matematika (Jupitek) Jurnal Magister Pendidikan Matematika (JUMADIKA) Science Map Journal Pakem : Jurnal Pengabdian Kepada Masyarakat Pattimura International Journal of Mathematics (PIJMath) ATOM : Jurnal Riset Mahasiswa BAKTI : Jurnal Pengabdian Kepada Masyarakat
Taufan Talib
Universitas Pattimura
Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health 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
VARIATIONS IN THE USE OF MAKE A MATCH LEARNING MODELS, SCRAMBLE LEARNING MODELS, AND CONVENTIONAL LEARNING MODELS TO IMPROVE STUDENT LEARNING OUTCOMES Carolina Selfisina Ayal; Binti Rohmawati; 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/jmsvol4issue2pp74-81

Abstract

Variations in the use of various mathematical learning models are expected to provide an overview of the ability of students to understand mathematical concepts. This study aimed to determine the variation of students' mathematics learning outcomes by using the make a match learning model, the scramble learning model, and the Conventional learning model. Using the quasi-experimental method, the make a match and scramble learning model was applied as the independent variable and the conventional learning model as the control variable. Statistically, the F test was used to show that there was a difference in the mean with the value of Fcount = 4.22 > Ftable = 3.18, and Tukey's HSD analysis showed a value of 14.18 and compared to the group mean, it was concluded that the use of the make a match learning model gave the better learning result value between scramble and conventional learning models
KEMAMPUAN PEMECAHAN MASALAH DAN SELF EFFICACY MAHASISWA DALAM MENYELESAIKAN WORKSHEET PERSAMAAN DIFERENSIAL TINGKAT SATU DERAJAT N Rofiroh Rofiroh; Isnaini Mahuda; Taufan Talib; Faqihuddin Faqihuddin
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/jmsvol4issue2pp93-107

Abstract

This study aims to describe the problem solving ability of UMT students in solving the first degree differential equations worksheet with the factorization method. This research is included in the category of qualitative research with a descriptive category. The research subjects were 20 fourth semester students for the 2021/2022 academic year. Data collection methods used are test techniques, filling out structured student worksheets and filling out questionnaires. The test is carried out by filling out the initial test. Filling out structured student worksheets consisting of material, examples and practice questions. Based on the initial test data, filling in the worksheets and questionnaires, the criteria for the three types of students were obtained. Type 1 students fill out 1-2 initial test questions, fill in the material incompletely, the sample questions are only done one question out of the two questions provided with unsystematic problem solving analysis and the last part of the practice questions is not filled in. Type 2 students fill out 2-3 questions for the initial test, complete the material, two examples of questions are done, the practice questions are filled with one question. Type 3 students work on 4 pre-test questions, complete structured student worksheets for each material, sample questions and practice questions. The student fills out a worksheet with a systematic problem-solving analysis
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
PENINGKATAN KEMAMPUAN MENGENAL LAMBANG BILANGAN MELALUI BERMAIN KARTU ANGKA BERGAMBAR PADA ANAK Ucu, Murni; Salamor, Reinhard; Talib, Taufan
Science Map Journal Vol 6 No 1 (2024): Science Map Journal
Publisher : Jurusan Pendidikan MIPA FKIP Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/jmsvol6issue1pp14-20

Abstract

Meningkatkan kemampuan mengenal lambang bilangan 1-10 melalui bermain kartu angka bergambar anak Kelompok A RA Al Hikmah Ambon. Penelitian ini dilakukan karena terdapat permasalahan dalam kemampuan mengenal lambang bilangan 1-10 pada anak Kelompok A RA Al Hikmah Ambon. Penelitian ini merupakan Penelitian Tindakan Kelas. Subjek penelitian ini adalah anak Kelompok A RA Al Hikmah Ambon yang berjumlah 12 anak. Objek penelitian adalah kemampuan mengenal lambang bilangan 1-10. Teknik pengumpulan data dilakukan dengan menggunakan observasi. Teknik analisis data dilakukan secara deskriptif kuantitatif dan kualitatif. Penelitian ini dilaksanakan dalam 2 siklus, setiap siklus berlangsung selama 4 kali pertemuan. Hasil penelitian menunjukkan bahwa kemampuan anak mengenal lambang bilangan 1-10 meningkat setelah adanya tindakan. Hasil observasi sebelum tindakan menunjukkan bahwa anak yang memiliki kemampuan mengenal lambang bilangan 1-10 adalah 17%. Pada Siklus I meningkat menjadi 50% dan pada Siklus II telah mencapai indikator keberhasilan, yaitu 83%. Berdasarkan hasil tersebut dapat disimpulkan bahwa bermain kartu angka bergambar dapat meningkatkan kemampuan mengenal lambang bilangan 1-10 pada anak Kelompok A RA Al Hikmah Ambon
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 Achmad Arsil Azim Kairoti Albertina Narahubun Amelia Amelia Anderson Leonardo Palinussa Aprilia Day Ariestha W Bustan Binti Rohmawati Bustan, Ariestha W Bustan, Ariestha Widyastuty Bustan, Ariestha Widyastuty Carolina Selfisina Ayal Carolina Selfisina Ayal Christi Matitaputty Christina Martha Laamena Diah Faradila Samsuri Emiliana Robiwala Fakhran Makatita Fakhrun Nisa Faqihuddin Faqihuddin Filda Koedoeboen Gita Febriani Pakay Hanisa Tamalene Indah Lestari Masry Kezia Ramona Lattan Khadijah Azzahra Alhamid Laamena, Novita Serly Latupeirissa, Indri Kezia M Samad Rumalean Mahuda, Isnaini Maimuna Keliangin Mayawi Mayawi Mayawi Mayawi Megawati Putri Wulandari Munazat Salmin Musri Rumbaru Nia Jurniasih Novalin C Huwaa Nurhayati Nurhayati Nurhayati Nurviana, Nurviana Reinhard Salamor Riezky Purnama Sari, Riezky Purnama Sari Rofiroh Rofiroh Salamor, Reinhard Salmin, Munazat Saputra, Lamanisa Rasid Ucu, Murni Ulya Nabilla, Ulya Nabilla Welmi Solissa Welmintje Mataheru Zaenab Boinauw Zeidun Attamimi