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All Journal ComEngApp : Computer Engineering and Applications Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) ILKOM Jurnal Ilmiah JURNAL PENDIDIKAN TAMBUSAI Journal on Education Gammath : Jurnal Ilmiah Program Studi Pendidikan Matematika Jurnal Pendidikan dan Konseling Jurnal Sains Riset Jurnal Sosial Humaniora Sigli JURNAL AXIOMA : Jurnal Matematika dan Pembelajaran Frontiers Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika MARISEKOLA: Jurnal Matematika Riset Edukasi dan Kolaborasi Education Journal: General and Specific Research
Sylvia Jane Annatje Sumarauw
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Other

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ANALISIS GRANGER CAUSALITY DAN APLIKASI PADA SAHAM-SAHAM ANGGOTA LQ 45 Regar, Vivian Eleonora; Sumarauw, Sylvia Jane A
FRONTIERS: JURNAL SAINS DAN TEKNOLOGI Vol 2, No 1 (2019): APRIL 2019
Publisher : Universitas Negeri Manado

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Abstract

Penelitian ini membahas tentang uji Granger Causality untuk melihat pengaruh satu saham terhadap saham lainnya khususnya yang tercatat pada Indeks LQ 45 di Bursa Efek Indonesia. Oleh karena untuk melihat pengaruh masa lalu pada kondisi sekarang sehingga data yang digunakan adalah data time series. Penelitian ini menggunakan data saham harian periode satu tahun. Metode yang digunakan adalah kuantitatif dengan model Vector Autoregressive (VAR). Hasil penelitian menunjukkan bahwa pada anggota sektor perbankan, properti dan group astra, anggota kelompok saling granger cause satu dengan yang lain. Saham sektor perbankan  granger cause saham properti dan sebaliknya terkecuali ELTY tidak granger cause BDMN. Saham perbankan granger cause saham group Astra dan sebaliknya. Saham property granger cause saham group astra tapi tidak semua sebaliknya yaitu ASII dan UNTR tidak  granger cause ELTY. Hal ini membawa efek kepada investor untuk lebih selektif dalam membangun portofolio saham sehingga bisa lebih meminimalkan resiko.
ALGORITMA PELATIHAN LEVENBERG-MARQUARDT BACKPROPAGATION ARTIFICIAL NEURAL NETWORK UNTUK DATA TIME SERIES Sumarauw, Sylvia Jane Annatje
FRONTIERS: JURNAL SAINS DAN TEKNOLOGI Vol 1, No 2 (2018): Agustus 2018
Publisher : Universitas Negeri Manado

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Abstract

Algoritma Levenberg-Marquardt merupakan salah satu algoritma backpropagation Artificial Neural Network yang dikembangkan sendiri oleh Kenneth Levenberg dan Donald Marquardt, memberikan solusi numerik untuk masalah meminimalkan fungsi non-linear. Algoritma inimemadukan metode steepest descent dan algoritma Gauss-Newton. yaitu kecepatan algoritma Gauss-Newton dan stabilitas metode steepest descent. Ide dasar dari algoritma LevenbergMarquardt adalah melakukan proses pelatihan gabungan. Pada sekitar area dengan kelengkungan yang kompleks, algoritma Levenberg-Marquardt beralih ke algoritma steepest descent, sampai kelengkungannya tepat untuk membuat pendekatan kuadrat dan pendekatannyamenggunakan algoritma Gauss-Newton, yang dapat mempercepat konvergensi secara signifikan. Dalam menerapkan algoritma Levenberg-Marquardt untuk pelatihan neural network, harus menyelesaikan dua masalah yaitu menghitung matriks Jacobian, dan bagaimana mengatur proses pelatihan iteratif untuk memperbarui bobot. Algoritma Levenberg-Marquardt memecahkan permasalahan yang ada di kedua metode gradient descent dan metode GaussNewton untuk pelatihan neural-netwok, dengan kombinasi dari dua algoritma maka algoritma ini dianggap sebagai salah satu algoritma pelatihan yang paling efisien.Kata Kunci: Levenberg-Marquardt Backpropagation, Artificial Neural Network
Fuzzy C-Means Clustering Model Data Mining For Recognizing Stock Data Sampling Pattern Sylvia Jane Annatje Sumarauw; Subanar Subanar
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 1, No 2 (2007): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.2278

Abstract

AbstractCapital market has been beneficial to companies and investor. For investors, the capital market provides two economical advantages, namely deviden and capital gain, and a non-economical one that is a voting .} hare in Shareholders General Meeting. But, it can also penalize the share owners. In order to prevent them from the risk, the investors should predict the prospect of their companies. As a consequence of having an abstract commodity, the share quality will be determined by the validity of their company profile information. Any information of stock value fluctuation from Jakarta Stock Exchange can be a useful consideration and a good measurement for data analysis. In the context of preventing the shareholders from the risk, this research focuses on stock data sample category or stock data sample pattern by using Fuzzy c-Me, MS Clustering Model which providing any useful information jar the investors. lite research analyses stock data such as Individual Index, Volume and Amount on Property and Real Estate Emitter Group at Jakarta Stock Exchange from January 1 till December 31 of 204. 'he mining process follows Cross Industry Standard Process model for Data Mining (CRISP,. DM) in the form of circle with these steps: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. At this modelling process, the Fuzzy c-Means Clustering Model will be applied. Data Mining Fuzzy c-Means Clustering Model can analyze stock data in a big database with many complex variables especially for finding the data sample pattern, and then building Fuzzy Inference System for stimulating inputs to be outputs that based on Fuzzy Logic by recognising the pattern.Keywords: Data Mining, AUz..:y c-Means Clustering Model, Pattern Recognition
Pengembangan Aplikasi Mobile Learning Berbasis Android pada Materi Persamaan Linear Satu Variabel Gratia I. Lintjewas; Sylvia J.A. Sumarauw; Rosiah J. Pulukadang
MARISEKOLA: Jurnal Matematika Riset Edukasi dan Kolaborasi Vol. 3 No. 1: April 2022
Publisher : Jurusan Matematika FMIPA Universitas Negeri Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/marisekola.v3i1.2491

Abstract

Penelitian pengembangan ini bertujuan untuk menghasilkan media pembelajaran Mobile Learning berbasis Android yang layak digunakan untuk menunjang pembelajaran matematika pada materi persamaan linear satu variabel. Selain itu penelitian ini bertujuan untuk mengetahui kelayakan dan efektif aplikasi Mobile Learning berbasis Android  pada siswa kelas VII SMP Negeri 1 Sonder. Penelitian ini merupakan penelitian pengembangan (R&D) dengan model ADDIE (analysis, design, development, implementation, dan evaluation). Analysis merupakan tahap untuk menganalisis kebutuhan dan masalah dalam pembelajaran. Tahap Design merupakan tahap perancangan produk. Development merupakan tahap pembuatan produk aplikasi dan validasi. Implementation merupakan tahap uji coba produk kepada responden. Evaluasi merupakan tahap untuk mengetahui hasil penilaian responden terhadap kelayakan aplikasi. Penelitian ini layak digunakan sebagai aplikasi penunjang pembelajaran matematika dengan presentase kelayakan sebesar 85,46%. Aplikasi mobile learning ini juga dikatakan efektif dilihat dari hasil post-test kelas eksperimen yang menggunakan aplikasi mobile learning lebih tinggi dibanding kelas kontrol yang tidak menggunakan aplikasi mobile learning.
DAMPAK PENGGUNAAN MEDIA SOSIAL PADA HASIL BELAJAR MATEMATIKA SISWA SMP NEGERI 1 PUSOMAEN Carina Olita Selin Tulandi; Sylvia J. A Sumarauw; Vivian E. Regar
EDUCATIONAL JOURNAL : General and Specific Research Vol. 2 No. 3 (2022): OKTOBER
Publisher : CV. ADIBA AISHA AMIRA

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Abstract

This study aims to determine the impact of the use of social media, especially YouTube on the mathematics learning outcomes of SMP Negeri 1 Pusomaen students. The social media youtube is the largest video presenter in the world today which contains all types of videos. Most of the students of SMP Negeri 1 Pusomen admitted that they prefer to use YouTube social media when they are at school rather than studying, besides that mathematics subjects are less attractive to students because they are considered very boring, making students rarely study when they are at home. Mathematics learning that is less attractive to students and excessive use of social media during class hours results in student learning outcomes that are still below the KKM. The type of research used is descriptive qualitative. Data collection techniques are observation, questionnaires/questionnaires, and interviews. Data analysis techniques in the form of data reduction, data presentation, and data verification. The results of the study at the time of observation showed that students had various reasons for using YouTube social media, but almost all of the students who were sampled very often used this social media anywhere and anytime, including at school when learning took place. The frequent use of social media by students has an impact on students' mathematics learning outcomes. The distributed questionnaire score data also shows that students really like YouTube social media with a percentage of 56% in the response aspect, and 54% in the reaction aspect. At the time of the research, the researcher tried to find out more about the impact of using YouTube social media on student learning outcomes, by making YouTube social media a learning resource, and it was found that students were very enthusiastic during the learning process and the learning outcomes obtained were 88 out of 100 students. have finished studying. This makes the use of YouTube social media a positive impact if used properly. So, the conclusion that can be drawn from the implementation of this research is that the use of appropriate social media has a positive impact on the mathematics learning outcomes of SMP Negeri 1 Pusomaen students and has a negative impact on student learning outcomes if it is used excessively and not as a learning resource.
OPTIMALISASI TAHAP PRESENTASI MODEL PIMCA PADA PEMBELAJARAN MATRIKS MATERI SPLTV Vellin F.E Londo; Sylvia J.A. Sumarauw; Vivian E. Regar
EDUCATIONAL JOURNAL : General and Specific Research Vol. 2 No. 3 (2022): OKTOBER
Publisher : CV. ADIBA AISHA AMIRA

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Abstract

In the learning process, how to provide material that does not can cause students to get less information about material, lack of understanding of concepts and difficulty solving problems such as training provided, thus causing low learning outcomes. Study on learning the SPLTV material matrix with the Optimization of the Presentation Stage based on MR (Multiple Representation) aims to enable student to obtain material information provided, can master the concept of material, and solve problems such as sample questions and can find out improvement of student learning outcomes. By using the PIMCA model which divided into 4 steps, namely Presentation, Idea Mapping, Conceptualization, Formative Assessment. This research was conducted in the Department of Mathematics with respondents 22 students. From the results of the calculation of the data obtained the average score pretest 6 and the average posttest score 65. Also obtained the average percentage an increase in understanding of the concept of 82,67 as a result there is an increase in understanding the concept so that the Optimization Stage is obtained PIMCA In SPLTV Material Matrix Learning, there is a improvement of learning outcomes and this model can also be an alternative in selection of learning models and can be continued in the STEM field.
PENGARUH MODEL DIRECT INSTRUCTION BERBANTUAN GEOGEBRA CLASSROOM TERHADAP HASIL BELAJAR SISWA PADA MATERI BANGUN RUANG SISI DATAR Sri Nesa Br Ginting, Sylvia J.A Sumarauw, Victor R. Sulangi
Gammath : Jurnal Ilmiah Program Studi Pendidikan Matematika Vol 7, No 2 (2022): Gammath : Jurnal Ilmiah Program Studi Pendidikan Matematika
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/gammath.v7i2.8677

Abstract

Penerapan model pembelajaran yang inovatif sangat dibutuhkan dalam meningkatkan hasil belajar siswa di kelas. Penelitian ini berfokus untuk mengetahui apakah model Direct Instruction berbantuan GeoGebra Classroom berpengaruh terhadap hasil belajar siswa di SMP Negeri 1 Tondano. Penelitian ini menggunakan pendekatan kuantitatif dengan metode Posttest-Only Control Group Design. Populasi pada penelitian ini adalah seluruh siswa kelas VIII SMP Negeri 1 Tondano yang dibagi menjadi 9 kelas. Sampel yang digunakan adalah kelas VIIIG Sebagai kelas eksperimen dan VIIIH sebagai kelas kontrol. Sampel diambil menggunakan teknik purposive sampling. Instrumen penelitian berupa tes uraian. Data yang diperoleh adalah hasil belajar siswa. Hasil penelitian menunjukkan bahwa rata-rata kelas eksperimen adalah  = 81,1, sedangkan kontrol  = 71,8, secara statistik data hasil tes berdistribusi normal dan homogen. Berdasarkan analisis data yang menggunakan uji t, diperoleh nilai t_hitung = 1,945 t_tabel = 1,679 pada taraf signifikan 5%, sehingga sesuai dengan rumusan hipotesis maka H0 ditolak. Dapat disimpulkan bahwa terdapat pengaruh model direct instruction berbantuan GeoGebra Classroom terhadap hasil belajar siswa pada bangun ruang sisi datar.Kata Kunci: Model Direct Instruction, GeoGebra Classroom, Hasil Belajar.
Fuzzy c-Means Clustering untuk Pengenalan Pola Studi kasus Data Saham Sylvia Sumarauw
Jurnal Axioma : Jurnal Matematika dan Pembelajaran Vol. 7 No. 2 (2022): Juli
Publisher : Universitas Islam Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56013/axi.v7i2.1395

Abstract

Fuzzy Clustering is one of the five roles used by data mining experts to transform large amounts of data into useful information, and one method that is often and widely used is Fuzzy c-Means (FCM) Clustering. FCM is a data clustering technique where the existence of each data point in the cluster is based on the degree of membership. This study aims to see the pattern of data samples or data categories using FCM clustering. The analyzed data is stock data on Jakarta Stock Exchange (BEJ) in the Property and Real Estate sector (issuer group). The data mining processes comply Cross Industry Standard Process Model for Data mining Process (Crisp-DM), with several stages, starting with the stage of getting to know the business process (Business Understanding) then studying the data (Data Understanding), continuing with the Data Preparation stage, Modeling stage, Evaluation stage and finally the Deployment stage. In the modeling stage, the FCM model is used. FCM clustering model data mining can analyze data in large databases with many variables and complicated, especially to get patterns from the data. Then a Fuzzy Inference System (FIS) was built based on a known pattern for simulating input data into output data based on fuzzy logic. Keywords: Fuzzy c-Means Clustering, Pattern Recognition
Learning Computer Programming Using Pimca Model: Project Assignments Sandy Salomo Saruan; Anetha L. F. Tilaar; Sylvia J. A. Sumarauw
Jurnal Pendidikan dan Konseling (JPDK) Vol. 4 No. 6 (2022): Jurnal Pendidikan dan Konseling
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jpdk.v4i6.9592

Abstract

Model pembelajaran PIMCA dapat memicu peserta didik untuk mengkonstruksi konsep dengan benar. Penelitian ini bertujuan untuk mengetahui bagaimana peningkatan rata-rata hasil belajar peseta didik pada pembelajaran pemrograman komputer dasar pada materi looping dengan menggunakan model pembelajaran PIMCA. Penelitian ini menggunakan metode penelitian campuran khususnya embedded design dengan teknik pengumpulan data melalui tes dan studi dokumentasi. Penelitian ini dilakukan di Jurusan Pendidikan Matematika Universitas Negeri Manado dengan subjek penelitian sebanyak 24 orang mahasiswa. Berdasarkan hasil penelitian, perhitungan hasil pretest dan posttest peserta didik menunjukkan peningkatan dari 9,58 menjadi 65,38 dari skala 0-100 dan skor n-gain diperoleh peningkatan rata-rata hasil belajar sebesar 62,13% dan rata-rata persentase peningkatan pemahaman konsep sebesar 83,86%. Peserta didik masih mengalami kesalahan sintaks pada code yang dibuat pada tugas proyek, namun sebanyak 83,3% subjek penelitian tidak memiliki masalah dalam memahami semantik, oleh karena itu pengajar harus lebih fokus dalam memahami sintaks.
Pengaruh Pembelajaran Kooperatif Tipe Stad terhadap Hasil Belajar Matematika Siswa Kelas VIII SMPN 4 Selaru Harry Henry Masrikat; Sylvia J.A. Sumarauw; Ontang Manurung; Navel Oktaviandy Mangelep
Journal on Education Vol 5 No 3 (2023): Journal on Education: Volume 5 Nomor 3 Tahun 2023 In Press
Publisher : Departement of Mathematics Education

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Abstract

The mathematics learning outcomes of SMPN 4 Selaru students are still very low, because students are less active in the learning process so that the mastery presentation is only 37%. An alternative to overcome this problem is to use STAD type cooperative learning. The purpose of this study was to find out whether the average mathematics learning outcomes of students who were taught using STAD type cooperative learning were more than the average mathematics learning outcomes of students taught without using STAD type cooperative learning. This type of research is quasi-experimental with a quantitative approach. Data analysis used is descriptive analysis, normality test, and homogeneity test. The instrument in this study was a test. The research subjects were 30 students of SMPN 4 Selaru. The results showed that the average student learning outcomes in the experimental class was 41.8 and the control class was 31.4. So it can be concluded that the average mathematics learning outcomes of students who are taught using STAD type cooperative learning is more than the average mathematics learning outcomes of students taught without using STAD type cooperative learning.
Co-Authors Anekke Pesik Anetha L.F. Tilaar Carina Olita Selin Tulandi Geofani Saul Darius Runtukahu Grachiella Aurelia Baweleng Gratia I. Lintjewas Harry Henry Masrikat Harrychoon Angmalisang Helen Yuliana Angmalisang Ichdar Domu Mersy Lesar Navel Oktaviandy Mangelep Oktafianti Kampongsipire Philotheus E. A. Tuerah Pitoy, Cori Renata Kamagi Rosiah J. Pulukadang Sandy Salomo Saruan Sri Wahyuni Mertosono subanar subanar Tristya Dewi Kosmani Vellin F.E Londo Victor R Sulangi Victor R. Sulangi Vivian E. Regar