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MENINGKATKAN KEMAMPUAN PEMAHAMAN DAN KOMUNIKASI MATEMATIK SISWA SMK MELALUI PENDEKATAN KONTEKSTUAL DAN STRATEGI FORMULATE-SHARE-LISTEN-CREATE (FSLC) Anggraeni, Dian
Infinity Journal Vol 2, No 1 (2013): Volume 2 Number 1, Infinity
Publisher : STKIP Siliwangi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (450.102 KB) | DOI: 10.22460/infinity.v2i1.p1-12

Abstract

Makalah ini melaporkan temuan satu eksperimen dengan disain pretest-postest dengan kelompok kontrol dan menerapkan pendekatan kontekstual dan strategi formulate-share-listen-create (FSLC), untuk menelaah kemampuan pemahaman dan komunikasi matematik siswa SMK. Subyek penelitian ini adalah 80 siswa SMK program keahlian pemasaran di Bandung. Instrumen penelitian terdiri dari tes kemampuan pemahaman dan komunikasi matematik serta disposisi matematik. Berdasarkan analisis data menggunakan SPSS 16.0 dan Microsoft Excel 2010, penelitian menemukan: Pencapaian dan peningkatan kemampuan pemahaman dan komunikasi matematik siswa yang memperoleh pendekatan kontekstual dan strategi formulate-share-listen-create (FSLC) lebih baik daripada pencapaian dan peningkatan kemampuan siswa yang memperoleh pembelajaran konvensional.  Penelitian juga menemukan adanya asosiasi sedang antara kemampuan pemahaman dan komunikasi matematik, dan siswa menunjukkan disposisi matematik yang positif terhadap pendekatan kontekstual dan strategi formulate-share-listen-create (FSLC) Kata Kunci    : pendekatan kontekstual, strategi formulate-share-listen-create, pemahaman dan komunikasi matematik, disposisi matematik  This paper reports the findings from an experimental prettest-posttest control group design conducted by using contextual approach and formulate-share-listen-create (FSLC) strategy to investigate students’ mathematical understanding and communication abilities.The study involved 80 grade-11 students from SMK of marketing field program in Bandung. The instrumens of this study are mathematical undestanding test, mathematical communication test, and mathematical disposistion scale. By using SPSS 16.0 and Microsoft Excel 2010, the study found the contextual approach and formulate-share-listen-create (FSLC) strategy was able to improve students’ mathematical understanding and mathematical communication abilities better than that of conventional approach. Students’ mathematical understanding and communication abilities were classified as mediocore. Furthermore, the study found there was medium association between mathematical understanding and mathematical communication abilities, and students performed positive disposition on contextual approach and formulate-share-listen-create (FSLC) strategy. Key words     :  contextual approach, formulate strategies, share, listen, create, understanding and mathematical communication, mathematical disposition
ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R Holipah, Holipah; Tirta, I Made; Anggraeni, Dian
Majalah Ilmiah Matematika dan Statistika Vol 19 No 2 (2019): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v19i2.17272

Abstract

Structural Equation Model (SEM) is a statistical technique with simultaneous processing involves measurement errors, indicator variables, and latent variables. SEM is used to test hypotheses that state the relationships between latent variables when latent variables have been assessed through each of the indicator variables. Multiple Group SEM is a basic model analysis that uses more than one sample. This analysis aims to determine whether the components or models of measurement and structural models are invariant for the two sample groups. In this study, the data generated by some requirements. First, the data generated with sample size n = 250. The first generated data is homogeneous data where the measurement model is the same as the structural model in group 1 and group 2, while the second data is non-homogeneous data where the measurement model and the structural model in group 1 and group 2 is not the same. The data was analyzed using the help of the lavaan package available in R to obtain SEM estimation results and Goodness of Fit Model from some data that was formed. From the results of the merger of the two groups, it shows that the invariant of the two models with the largest df (63) which is Fit Mean model states the simplest model. However, the smallest df (48) with Fit.configural model states the most complex model. Keywords: SEM, Multiple Group, R Program
Fruit Nutrients of Five Species of Wild Raspberries (Rubus spp.) from Indonesian Mountain’s Forests Surya, Muhammad Imam; Suhartati, Siti; Ismaini, Lily; Lusini, Yuyun; Destri, Destri; Anggraeni, Dian; Normasiwi, Suluh; Asni, Nurul; Sidiq, Mirwan Abu Bakar
Journal of Tropical Life Science Vol 8, No 1 (2018)
Publisher : Journal of Tropical Life Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (709.404 KB) | DOI: 10.11594/jtls.08.01.13

Abstract

Rubus spp. (wild raspberries) is one of genera belongs to Rosaceae, also distributed in the mountain forest of Indonesia. It has a high potency to be cultivated plant. Although, some of the potential of Rubus has already known, information of about fruit nutrients of species that distribute in the mountain forest of Indonesia are not known yet. This study was aimed to determine the fruit nutrients of five species of wild raspberries that was collected in Cibodas Botanical Garden. The results of our experiments demonstrate that the fruits nutrients contents varied among five species of wild raspberries from Indonesian mountain's forests. Rubus fraxinifolius has the highest content of sugar (5.05 g sugar per 100 g fruits) compared to Rubus rosifolius, Rubus chrysophyllus, Rubus lineatus and raspberry. During the ripening and ripe period, there were a different value of vitamin C and iron contents. The highest vitamin C of R. fraxinifolius (83.65 mg/100 gram) on the ripening fruit stage II. On the other hand, the highest vitamin C of R. rosifolius (54.30 mg/100 gram) found on the stage of ripe fruit.
ANALISIS PRODUKSI DAN PENDAPATAN USAHATANI PADI SAWAH DI DESA DOLAGO KECAMATAN PARIGI SELATAN KABUPATEN PARIGI MOUTONG Anggraeni, Dian; Damayanti, Lien; Rauf, Rustam Abd.
Mitra Sains Vol 7, No 2 (2019)
Publisher : Tadulako University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (398.305 KB)

Abstract

The research intends to find out the factors that influence farming production of rice field in and to find out the income of farming production of rice filed in Dolago Village South Parigi District Parigi Moutong Regency. This Research used survey method and samples were taken through simple random method. The samples were 38 people. The data were analyzed by using SPSS 21 and Income Analysis. The research result showed that independent variables (X1-X5) simultaneously gave significant influence on the independent bariable (Y) the farming production of rice field. It can be seen from the value of F-Test 50,966 > F-Table 2,409. The results of t-test on five variables showed that partially, there were four variables that gave significant influence the farming production of rice field, they are land area, seeds, urea Fertilizer and labors. While Phonska fertilizer variable gave negative influence. The income of the farmers of rice farm in Dolago Village was IDR 18.316.637,-/1,08Ha/planting season or IDR 16.976.395,-/Ha/planting season.
APLIKASI GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) PADA PEMODELAN VOLUME KENDARAAN MASUK TOL SEMARANG Anggraeni, Dian; Prahutama, Alan; Andari, Shofi
MEDIA STATISTIKA Vol 6, No 2 (2013): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (625.794 KB) | DOI: 10.14710/medstat.6.2.61-70

Abstract

Time series data from neighboring separated location often associated both spatially and through time. Generalized space time autoregrresive (GSTAR) model is one of the most common used space-time model to modeling and predicting spatial and time series data. This study applied GSTAR to modeling vehicle volume entering four tollgate (GT) in Semarang City: GT Muktiharjo, GT Gayamsari, GT Tembalang, and GT Manyaran. The data was collected by month from 2003 to 2009. The best model provided by this study is GSTAR (21)-I(1,12) uniformly weighted with the smallest REMSE mean 76834. Key words: GSTAR, Vehicle Volume, Space-Time Model
PEMODELAN FAILURE TIME PADA MAHASISWA BERHENTI STUDI DI UNIVERSITAS JEMBER Hanifia, Fidiatma Foristy; Fatekurohman, M.; Anggraeni, Dian
Majalah Ilmiah Matematika dan Statistika Vol 20 No 1 (2020): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v20i1.17218

Abstract

Problems in higher education concerning students are always interesting objects studied from any side. One of the problems faced by universities and students is stopping study. Stopping the study of students became a problem in universities, including the University of Jember. One of the statistical methods used is Survival Analysis. In its development, survival analysis was carried out by combining the concepts of Geometric regression. Geometric is one of the non linear regression for discrete data. Geometric regression modeling cannot be done with ordinary linear modeling, but must be done using the Generalized Linear Model (GLMs) method. In this study the variables used were gender, GPA, faculty, age of entry and entry point. The results of the study students stopped studying in the first semester 140 students. Average GPA of 1.54. 62.85% male sex. Student faculty of education and teacher stopped most studies. The student entry pathway stopped the most SBMPTBR studies and 54.40% were 18 years old. Significant influential factors for stopping the study were GPA, gender and entry point. From the Geometric opportunity, it was found that female students were slower when they stopped studying than men. The faculty stops studying at the latest is the Faculty of Medicine. Keywords: Drop Out, Failure Time, Regrition Geometric Method
ANALISIS DISKRIMINAN UNTUK VALIDASI CLUSTER PADA STUDI KASUS PENGELOMPOKAN KECAMATAN DI KABUPATEN JEMBER BERDASARKAN STATUS KEMISKINAN Istiqomah, Fikriana Nur; Tirta, I Made; Anggraeni, Dian
Majalah Ilmiah Matematika dan Statistika Vol 18 No 1 (2018): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v18i1.17239

Abstract

. Cluster validation is a procedure to evaluate the results of cluster analysis quantitatively and objectively on a data. The validation process is very important to get the results of a good and appropriate grouping. In the validation process, the author uses internal validation, stability, and discriminant analysis test. This study aims to obtain validation results from the hierarchy and kmeans method. This data grouping uses “iris” simulation data, which results from the grouping method used can be applied to the original data to see which validation method is used for all data and produce an optimal grouping. The result of the study show that in the “iris” data, a single linkage link is an appropriate grouping method because the result of the grouping are optimal for all validations and classification of group members whose groups are significant. In Sub-district poverty data in Jember district with a single linkage link optimal grouping was obtained and complete linkage links were also used as a method that resulted in optimal grouping for all validation. Cluster validation using discriminant analysis test is appropriate for various types of data in general and shows that single linkage methods are better than other methods for grouping and validation methods for “iris” data and Sub-district data in Jember district based on variables of poverty status. Keywords: Cluster Analysis, Diskriminant Analysis, Multivariate Analysis, Validation Cluster
ANALISIS STRUCTURAL EQUATIONMODELING(SEM) UNTUK SAMPEL KECIL DENGAN PENDEKATAN PARTIAL LEAST SQUARE (PLS) Ulum, Miftahul; Tirta, I Made; Anggraeni, Dian
Prosiding Seminar Matematika dan Pendidikan Matematik Vol 1, No 1 (2014): Prosiding Seminar Nasional Matematika 2014
Publisher : Prosiding Seminar Matematika dan Pendidikan Matematik

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Abstract

Analisis Structural Equation Modeling (SEM) sering diaplikasikan pada permasalahan sosial yang membutuhkan model yang relatif kompleks. Pendugaan parameter pada analisis SEM membutuhkan beberapa asumsi penting seperti ukuran sampel minimal 10 kali banyaknya indikator dan data harus berdistribusi normal. Pada prakteknya tidak mudah untuk memenuhi asumsi tersebut. Dalam perkembangannya terdapat sebuah metode SEM yang tidak membutuhkan asumsi tersebut yang dikenal dengan metode analisis Partial Least Square (PLS).Metode ini merupakan analisis SEM berbasis varian atau dikenal dengan SEM-PLS. Pendugaan parameter pada metode ini tidak membutuhkan ukuran sampel yang besar dan data tidak harus berdistribusi normal. Pada penelitian ini akan ditunjukkan perbandingan analisis data menggunakan metode SEM-PLS dengan metode CB-SEM. Perbandingan analisis data menggunakan data serdos yang berupa 4 variabel laten dan 24 variabel indikator yang sebelumnya sudah dianalisis menggunakan metode analisis CB-SEM dengan data ditransformasi ke z-score untuk memenuhi asumsi. Pada penelitian ini digunakan tiga macam ukuran sampel yaitu 35,55, dan 75yang diambil dari parent sample sebanyak160kemudian dilakukan tahap Bootstrapping sebanyak 50 kali. Tahap tersebut dilakukan padasetiap ukuran sampel untuk mengetahui seberapa minim ukuran sampel pada metode SEM-PLS yang representatif terhadap sample parent. Hasil penelitian menunjukkan bahwa ukuran sampel yang digunakan pada metode analisis SEM-PLS adalah sebanyak 55. Nilai R2 pada ukuran sampel 55 sama baik dengan nilai R2 pada parent sample dengan data tidak ditransformasi ke z-score sebagaimana metode CB-SEM.
RANCANG BANGUN DATA WAREHOUSE DAN R BERBASIS WEB Anggraeni, Dian; Muharom, Lutfi Ali; Hadi, Alfian Futuhul
Prosiding Seminar Matematika dan Pendidikan Matematik Vol 1, No 1 (2014): Prosiding Seminar Nasional Matematika 2014
Publisher : Prosiding Seminar Matematika dan Pendidikan Matematik

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Abstract

Pemanfaatan teknologi informasi sudah merupakan kebutuhan yang mendesak untuk melihat informasi dari berbagai sumber didalam pengambilan keputusan. Informasi membutuhkan suatu data yang dikelola dalam bentuk tertentu untuk memberikan arti. Perekaman data merupakan suatu aktifitas atau kejadian yang tersimpan dan membutuhkan suatu pengolahan yang baik. Data warehouseadalah salah satu bentuk pengolahan data yang nantinya digunakan untuk mendukung proses pengambilan keputusan tersebut. Data warehouse ini dimulai dari tahapan pengumpulan data, pemilihan data, perancangan data warehouse dan pemuatan data ke warehouse. Analisa data akan menggunakan program R yang terimplementasi berbasiskan web dan terintegrasi dengan data warehouse. R yang terimplementasi berbasiskan web akan mempermudah pengguna didalam pengoperasiannya. Perkembangan teknologi yang semakin maju, memungkinkan menjalankan R dengan browser. Dengan adanya data warehouse dapat dihasilkan koleksi data yang terstruktur dan integrasi dengan R dapat digunakan sebagai analisa dalam proses pengambilan keputusan.
ImplementasiMetode Penalized Maximum Likelihood Estimation Pada Model RegresiLogistikBiner Sholihin, Miftahus; Hadi, Alfian Futuhul; Anggraeni, Dian
Prosiding Seminar Matematika dan Pendidikan Matematik Vol 1, No 1 (2014): Prosiding Seminar Nasional Matematika 2014
Publisher : Prosiding Seminar Matematika dan Pendidikan Matematik

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

Abstract

Model regresi logistik biner merupakan salah satu model regresi logistik yang digunakan untuk menganalisa hubungan antara satu variabel respon bersifat biner dengan beberapa variabel prediktor bersifat kategorik. Parameter dari model regresi logistik biner diduga dengan metode Maximum Likelihood Estimation (MLE) yang selanjutnya diselesaikan dengan metode iteratif Newton-Raphson. Namun, dalam suatu kondisi tertentu metode Maximum Likelihood Estimation (MLE) tidak dapat digunakan karena diperoleh penduga yang tidak konvergen. Untuk menyelesaikan hal tersebut, digunakan pendekatan metode Penalized Maximum Likelihood Estimation (PMLE) yang pertama kali diusulkan oleh Firth (1993). Penalized Maximum Likelihood Estimation (PMLE) merupakan hasil modifikasi fungsi skor likelihood menjadi fungsi skor Penalized likelihood. Data yang digunakan dalam penelitian ini adalah data sekunder tentang pemberian kredit dari suatu badan usaha kepada peternak ayam potong, yang diperoleh dari Badan Usaha Peternakan di Kabupaten Magetan, Jawa Timur. Langkah-langkah dalam penelitian ini yang pertama adalah melakukan pendugaan parameter pada data menggunakan metode MLE dan Iteratif Newton-Raphson dengan bantuan ProgramR. Dari data yang di analisis, ditemukan masalah yaitu penduga parameter tidak konvergen. Kedua, mencari masalah yang mengakibatkan penduga tidak konvergen menggunakan peluang ketepatan alokasi yang dilanjut dengan memeriksa ragam penduga prediktor yang dibakukan. Dari data yang dianalisis mengandung masalah pemisahan kurang sempurna. Langkah terakhir mencari penduga parameter pada data tersebut yang telah teridentifikasi masalah pemisahan kurang sempurna menggunakan Metode PMLE untuk mendapatkan model terbaik. Hasil penelitian ini menunjukkan bahwa model terbaik dari data pembeikan kredit peternak ayam potong mengandung faktor-fakor yang paling mempengaruhi pemberian kredit tersebut, antara lain: faktor pengalaman, tingkat kebersihan kandang, tingkat kelembaban kandang, dan luas area kandang.