Claim Missing Document
Check
Articles

Found 5 Documents
Search
Journal : Edumatsains

Pengaruh Performance Mahasiswa PPL terhadap Peningkatan Hasil Belajar Fisika Siswa di SMA Faradiba, Faradiba
EduMatSains Vol 1, No 1 (2016): Juli 2016
Publisher : Fakultas Keguruan dan Ilmu Pendidikan Universitas Kristen Indonesia

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

Abstract

Research has conducted student teachers’s performance influence to improving student’s learning outcomes in high school in August 2015 - January 2016. The study was conducted with 4 phases: (1).Providing pretest, posttest and questionnaires. (2). Data collection pretest, posttest and questionnaires. (3). Data processing such as coding and simple regression model . (4). Simple regression analysis and variable presentation supporting student’s learning. The correlation coefficient 0.712 (71.2%) for the relation between the two variables categorized strong. Determasi coefficient value of 0, 507 (50.7%) which describe student  teacher’s performance (X) has the effect of a contribution of 50.7% to the student’s learning outcomes (Y) and 49.30% influenced by other factors. Regression model Y = -43.507 + 2,887X.T test obtained Thitung 10,69 greater than  Ttable  1.98  which mean that there is influence student teacher’s performance toward improving student learning outcomes. F test obtained Fhitung 115.23 value greater than Ftable which mean the model is expressed well.
Pengaruh Performance Mahasiswa PPL terhadap Peningkatan Hasil Belajar Fisika Siswa di SMA Faradiba Faradiba
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 1 No 1 (2016): Juli
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v1i1.67

Abstract

Research has conducted student teachers’s performance influence to improving student’s learning outcomes in high school in August 2015 - January 2016. The study was conducted with 4 phases: (1).Providing pretest, posttest and questionnaires. (2). Data collection pretest, posttest and questionnaires. (3). Data processing such as coding and simple regression model . (4). Simple regression analysis and variable presentation supporting student’s learning. The correlation coefficient 0.712 (71.2%) for the relation between the two variables categorized strong. Determasi coefficient value of 0, 507 (50.7%) which describe student teacher’s performance (X) has the effect of a contribution of 50.7% to the student’s learning outcomes (Y) and 49.30% influenced by other factors. Regression model Y = -43.507 + 2,887X.T test obtained Thitung 10,69 greater than Ttable 1.98 which mean that there is influence student teacher’s performance toward improving student learning outcomes. F test obtained Fhitung 115.23 value greater than Ftable which mean the model is expressed well.
Pengenalan Pola Sinyal Suara Manusia Menggunakan Metode Back Propagation Neural Network Faradiba Faradiba
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 2 No 1 (2017): Juli
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v2i1.372

Abstract

This research have been designed a structure of artificial neural network (ANN) with using backpropagation to recognize signal pattern of human voice. The signal should first be processed with Linear Predictive Coding (LPC). Linear Predictive Coding (LPC) used for extraction characteristic. Producing matrix with 24 x50 orde which is then becoming input data for Artificial Neural Network Backpropagation (ANN-BP). There nets consist of 4 layers. Those 4 layers are : 1 input layers with 24 neuron, 2 hidden layers which are devided as 15 neuron at the first hidden layer and 10 neuron at the second, The last output with 5 neuron.For 5 training data, parameter characteristic value of net such us: Learning rate value (alpha) = 0,05 and mu value (μ) = 10-3with using by sigmoid bipolar activation function. The result of the research shows that the nets can recognize as 100 % of 25 trainning data, 74 % of 25 testing data.Keywords : Artificial Neural Network, Back propagation, voice recognation
Tingkat Kebisingan Suara di Lingkungan MTS Negeri 34 Jakarta terhadap Kualitas Proses Belajar Mengajar Septina Severina Lumbantobing; Faradiba Faradiba; Fransiskus Assisi B
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 4 No 1 (2019): Juli
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v4i1.1044

Abstract

Schools are places where the teaching and learning process is carried out should provide a conducive atmosphere so that educational goals are expected to be achieved. One of the main factor that is quite disturbing when the learning process takes place is the noise. The school where this research is located is one of the schools that is close to the noise source. The location of this research is 34 MTs in Jakarta which is located at a radius of 0.34 km from the runway of Halim Perdanakusuma airport. This research uses descriptive analysis method. Sound noise level data collection is done by using a sound level meter. Data is measured by a momentary sound pressure level of 5 minutes, or Leq (5 minutes) for each measurement point. The noise level at 34 MTs Jakarta in five measurement points respectively were 84.87 dB, 79.60 dB, 81.73 dB, 81.00 dB and 85.20 dB. The highest noise level is at point 5 which is the side facing the runway at Halim Perdanakusuma airport. The average noise level is 83.85 dB. This value is in the very noisy category according to Kep-48 MNLH / 11/1996. From the results of questionnaire analysis, 46.1% of respondents stated that the school was noisy, then 36.2% of students stated that the noisy conditions disrupted communication while carrying out the learning process in the classroom and 36.9% of respondents stated that noise from Halim Perdanakusuma airport activities disturbed their concentration in the teaching and learning process in the classroom Keywords: noise level, school, sound level meter, learning process
EFEKTIVITAS PENGGUNAAN VIRTUAL LABORATORY TERHADAP PENINGKATAN HASIL BELAJAR SISWA SMA DI ERA NEW NORMAL Chyntia Clarinda; Novalina; Mariana Gu; Faradiba Faradiba
EduMatSains : Jurnal Pendidikan, Matematika dan Sains Vol 6 No 2 (2022): Januari
Publisher : Fakultas Keguruan dan Ilmu Pendidikan, Universitas Kristen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33541/edumatsains.v6i2.3339

Abstract

Technological developments present many choices of learning media. The learning media that is the prima donna during the pandemic is a virtual laboratory. Virtual laboratories are used by teachers as a substitute for face-to-face practicum activities. There are many kinds of virtual laboratory applications that have been spread, one of which is the "PhET" simulation application. The purpose of this study was to determine the impact of using the PhET simulation application on improving student learning outcomes. This research was conducted at SMAN 54 Jakarta. The method used in this research is descriptive quantitative with the type of pre-experimental research. Data collection techniques used in this study were questionnaires and tests. Questionnaires and tests were used to obtain data on student learning outcomes. Data analysis used t test and N-gain test. The t-test was used to see if there was an effect of using a virtual laboratory on student learning outcomes. While the N-Gain test is to see how effective the use of virtual laboratories is to improve learning outcomes. The results of this study indicate an increase in student learning outcomes after using a virtual laboratory application.
Co-Authors Abdullah, Magfirah Achmad, Cindy Artikasari Alyanti, Tifani Kursya Ananda, Ratu Hilda Andreas Rian Nugroho Asep Edi Sukmayadi Asni Amin Aswar, Jumalia Audia Triani Olii, Audia Triani Bintang R. Simbolon Chyntia Clarinda Dedi Juliasman Sakatsila Dewi Yuliana Diaz Jubairy Prabowo Dicka Saputri Erni Murniarti Erni Murniarti Fadliyah, Hilyatul Ferina Septiani Damanik Fortwengel, Gerhard Fransiskus Assisi B Hadi Saputra Handayani, Ida Sri Hasanudin, Nurlaila Hasfikasari, Prity intan permata sari Ivanawati, Anselma Jean Rassyifa, Aloina Jei Tipoani Sinaga Kase, Alfa Graciani Khaira, A Tenri Mifta Khaira, A. Tenri Mifta Laia, Setiana Larasinta, Nadia Lase, Fan Damai Sejahtera Lumbantobing, Septina Severina Lutfan Lazuardi Manogari Sianturi Manogari Sianturi Manogari Sianturi Manullang, Nathasya Grisella Mariana Gu Minawati Minawati Muammar Fawwaz Muhammad Thesa Ghozali Napitupulu, Revaldo Ngia Masta Nirwana, Nirwana Nomleni, Marteda Veronika Novalina Nur Adnin Nurmala, Andi Arifah Nurwahyuni, Atik Nya Daniaty Nya Daniaty Malau Olla, Yufran Meliando Philipus Philipus Piter Honirius Naitaunus Pratita, Rasta Naya Rais Razak, Rais Rassyifa, Aloina Jean Ratna Santi Rezki Amriati Syarif Rezki Amriati Syarif, Rezki Amriati Ririn Aquarina Ririn Ririn Sakatsila, Dedi Juliasman Samuel Gideon Satibi Satibi Savitri, Triana Aulia Sekri Ambu, Reggen Seprianus Seprianus Septiani Damanik, Ferina Septina Severina Lumbantobing Septina Severina Lumbantobing Septina Severina Lumbantobing Septina Severina Lumbantobing Shafira Shafira, Shafira Siahaan, Chontina Sinta Faradilla Sri Rahayu Tri Astuti St Fatimah Azzahra, St Fatimah Stivens Situmeang, Bramcov Sukmawati Sukmawati Sumiati Sumiati Sumiati Sumiati Syarif, Rezki Amriati Amriati Taat Guswantoro, Taat Thesa Ghozali, Muhammad Winda Wahyuni Yohanes, Andreas Yonas Firdinal Silaban Yoshua, Steven Yufran Meliando Olla Yulianto, Yuni Zakinah Zainal Abidin Zealfiana, Gracia Zebua, Tesalonika Febriani