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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Journal on Mathematics Education (JME) Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Southeast Asian Mathematics Education Journal Prosiding Seminar Nasional Official Statistics Jurnal Statistika dan Sains Data

Kismiantini Kismiantini

Jurusan Pendidikan Matematika, FMIPA Universitas Negeri Yogyakarta

Author-ID : 299045

Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Mathematics Social Sciences

Published : 13 Documents Claim Missing Document

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Analisis Data Multivariat Dengan Program R Wustqa, Dhoriva Urwatul; Listyani, Endang; Subekti, Retno; Kusumawati, Rosita; Susanti, Mathilda; Kismiantini, Kismiantini
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 2, No 2 (2018): Vol 2, No 2 (2018)
Publisher : Yogyakarta State University

Analisis multivariat adalah salah satu teknik dalam statistika yang digunakan untuk menganalisis secara simultan variabel lebih dari satu. Perhitungan dalam analisis data multivariat lebih kompleks dibandingkan dengan analisis univariat, sehingga penggunaan program statistika akan mempermudah dalam analisis.Â Salah satu program statistika yang dapat diperoleh secara gratis (tanpa lisensi) adalah program R. Workshop program R untuk analisis data multivariat bagi para lulusan S1 Pendidikan Matematika/Matematika dan mahasiswa program pasca sarjana Pendidikan Matematika secara umum bertujuan untuk memberikan pengetahuan dan ketrampilan dasar penggunaan program R pada analisis data multivariat. Metode yang digunakan dalam pelatihan meliputi tutorial dan praktek secara langsung. Sebagian peserta belum pernah menggunakan program R, dan terlihat bahwa mereka antusias dalam mengikuti pelatihan. Berdasarkan pengamatan dan tanya jawab dengan peserta pelatihan, tampak bahwa peserta bersemangat mengikuti kegiatan pelatihan. Dengan pelatihan ini para peserta mendapat pengetahuan secara teoritis tentang analisis komponen utama, analisis faktor dan secara praktek meliputi ketrampilan tentang bagaimana menganalisis data multivariat dengan program R, dan menginterpretasikan hasil analisis dengan kedua metode tersebut.Â Kata kunci: analisis multivariat, program statistika R.Â Multivariate Data Analysis Using R Program AbstractÂ Â Â Â Â Â Â Â Â Â Multivariate analysis is a technique in statistics that is used to simultaneously analyze more than one variable. Dealing with multivariate data analysis calculations are more complex than the univariate analysis, so the use of statistical program will make it easier. One of the free statistical programs (free license) is R program. Workshop R program on the multivariate data analysis for people who had mathematics or mathematics education degree or graduate students in general aims to provide multivariate data analysis skills using statistics R program. The training methods were tutorial and practices in class. Some participants had never used the R program prior to the training, and they were enthusiastic during training. According to the observations and questions and answers session, the participants appeared to have passions on learning the usage ofÂ the statistical R program on analyzing multivariate data. From the training, the participants gained theoretical knowledge about the principal component analysis, factors analysis, and practices about the skills on how to analyze mulivariate data, and interpret the results of the analysis with both methods using theÂ R program.Â Keywords: multivariat analysis, R statistical program

Pendugaan Amatan Yang Hilang Pada Rancangan Acak Kelompok (RAK) Kismiantini Kismiantini
Jurnal Matematika, Statistika dan Komputasi Vol. 12 No. 2: January 2016
Publisher : Department of Mathematics, Hasanuddin University

Pengumpulan data dengan metode percobaan seringkali ditemui adanya data hilang. Hal ini disebabkan diantaranya oleh kecerobohan peneliti atau kerusakan unit percobaan yang tidak dapat dihindari. Masalah data hilang pada rancangan acak lengkap dengan ulangan sama dapat diatasi dengan ulangan tidak sama. Namun data hilang pada rancangan acak kelompok tidak dapat diatasi dengan cara tersebut, karena ulangan pada rancangan ini berperan sebagai kelompok. Salah satu metode untuk menduga data hilang pada rancangan acak kelompok adalah dengan metode Least Mean Square (LMS). Masalah data hilang pada rancangan acak kelompok akan berakibat pada hasil analisis ragamnya, yaitu derajat bebas galat akan berkurang sebanyak total data hilang, dan besarnya jumlah kuadrat galat akan semakin kecil seiring dengan semakin banyaknya data hilang.

Drought-prone areas mapping using fuzzy c-means method in Gunungkidul district Kismiantini Kismiantini; Fajra Husniyah; Osval Antonio Montesinos-López
PYTHAGORAS Jurnal Pendidikan Matematika Vol 16, No 2: December 2021
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/pythagoras.v16i2.43780

Gunungkidul district is one of the districts in the Special Region of Yogyakarta that is frequently affected by drought disasters. The purpose of this study is to map drought-prone areas in Gunungkidul district using the fuzzy c-means method, making it easier for the government to allocate water-dropping assistance to drought-affected areas. The research variables include rainfall, soil type, infiltration, slope, and land use. The type of variables is an ordinal scale, so they must be transformed using the successive interval method before being analyzed using the fuzzy c-means method. The cluster validity indexes of the Xie and Beni index, partition coefficient, and modification partition coefficient were used to find the optimal k. The results of fuzzy c-means clustering revealed three clusters with a low level of vulnerability consisting of 7 sub-districts, a moderate level of vulnerability consisting of 8 sub-districts, and a high level of vulnerability consisting of 3 sub-districts. Rainfall, land use, soil type, infiltration, and slope were the drought hazard factors with the greatest to least effect in this study.

GROWTH MINDSET, SCHOOL CONTEXT, AND MATHEMATICS ACHIEVEMENT IN INDONESIA: A MULTILEVEL MODEL Kismiantini Kismiantini; Ezra Putranda Setiawan; Adi Cilik Pierewan; Osval Antonio Montesinos-Lopez
Journal on Mathematics Education Vol 12, No 2 (2021)
Publisher : Department of Doctoral Program on Mathematics Education, Sriwijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jme.12.2.13690.279-294

Shifting students to a growth mindset can increase their achievements. Nevertheless, only a few studies have been conducted on this topic in developing countries. This study aims to examine the relationship between growth mindset, school context, and mathematics achievement in Indonesia. Using a multilevel model on the PISA 2018 data, this study explored the variables that contributed to mathematics achievement. The multilevel analysis showed that students’ gender, growth mindset, index of economic social, and cultural status were statistically significant predictors of students’ mathematics achievement. Girls have been reported to have a higher mathematics achievement than boys in Indonesia. As the students’ growth mindset increases, so do their mathematics achievement.

ANALISIS PEUBAH RESPON BINER Kismiantini Kismiantini
PYTHAGORAS Jurnal Pendidikan Matematika Vol 3, No 1: Juni 2007
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Pada regresi linier klasik, peubah respon diasumsikan merupakan peubah yang bersifat kontinu. Bila peubah respon tidak lagi kontinu melainkan berupa kategori (biner, cacahan) maka model regresi linier klasik tidak dapat digunakan. Permasalahan tersebut dapat diatasi dengan model linier terampat. Model linier terampat yang digunakan dalam menganalisis peubah berskala biner adalah model logit, model probit dan model complementary log-log. Pada tulisan ini akan dikaji penggunaan ketiga model tersebut dalam menganalisis peubah respon biner. Bila nilai galat baku Pearson semakin kecil maka semakin baik pula model yang digunakan.Kata kunci : peubah respon biner, model logit, model probit, model complementary log- log

Workshop Analisis Faktor untuk Data Penelitian Ilmu Sosial dan Kependidikan Dhoriva Urwatul Wutsqa; Kismiantini Kismiantini; Muhammad Fauzan; Rosita Kusumawati; Sahid Sahid; Syarifah Inayati
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 5, No 1 (2021): Vol 5, No 1 (2021)
Publisher : Yogyakarta State University

Kegiatan PPM ini bertujuan memberikan pelatihan penggunaan program R dan SPSS dalam penelitian data ilmu sosial dan kependidikan kepada para praktisi lulusan S1, mahasiswa pasca sarjana, dan dosen di lingkungan universitas di Yogyakarta. Penelitian dalam ilmu sosial dan kependidikan seringkali melibatkan banyak variabel yang saling berkorelasi maupun mempunyai korelasi yang tinggi, misalnya dalam pengembangan suatu instrument penelitian. Penghapusan variabel yang mempunyai korelasi tinggi bisa mengakibatkan hilangnya informasi, untuk mengatasi hal tersebut dapat digunakan analisis komponen utama (Principal Component Analysis/PCA). Sedangkan dalam hal menentukan konstruk yang sesuai dari butir-butir soal yang terbentuk dapat dilakukan dengan dua pendekatan yaitu analisis faktor eksplorasi (Exploratory Factor Analysis/EFA) dan analisis faktor konfirmasi (Confirmatory Factor Analysis/CFA). Permasalahan yang terkait dengan reduksi variabel dan pembentukan konstruk pada pengembangan instrument ini merupakan hal yang sangat penting dalam penelitian ilmu sosial dan kependidikan. Sehingga suatu metode analisis PCA, EFA, dan CFA dengan menggunakan program R dan SPSS mutlak diperlukan. Workshop yang diikuti oleh 26 peserta peserta ini dapat berjalan dengan baik. Berdasarkan pelaksanaan dan evaluasi kegiatan ini dapat disimpulkan bahwa tujuan dapat tercapai dengan baik.

Workshop Analisis Regresi Logistik untuk Penelitian di bidang Ilmu Sosial dan Pendidikan Dhoriva Urwatul Wutsqa; Kismiantini Kismiantini; Rosita Kusumawati; Sahid Sahid; Syarifah Inayati; Ezra Putranda Setiawan
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 6, No 2 (2022): Vol 6, No 2 (2022)
Publisher : Yogyakarta State University

Penelitian-penelitian di bidang ilmu sosial dan pendidikan seringkali melibatkan variabel-variabel respon dengan tipe kategorik, yang memerlukan analisis menggunakan regresi logistik. Dibandingkan regresi linear, model regresi logistik lebih kompleks dalam hal pengolahan maupun interpretasinya. Oleh karena itulah, dilakukan kegiatan Pengabdian kepada Masyarakat dalam bentuk workshop analisis regresi logistik untuk penelitian di bidang ilmu sosial dan pendidikan. Kegiatan ini diikuti oleh praktisi lulusan S1 dan mahasiswa berbagai program studi pascasarjana di Indonesia. Workshop dilaksanakan secara daring selama dua hari dengan metode pemberian materi dan demo program R secara langsung. Pelatihan ini diawali dengan visualisasi data kategorik lalu dilanjutkan materi regresi logistik biner dengan prediktor kontinu pada hari pertama. Pada hari kedua, materi yang disampaikan adalah regresi logistik biner dengan prediktor kategorik dan regresi logistik dengan prediktor kategorik dan kontinu. Data yang digunakan sebagai contoh adalah data dalam penelitian ilmu sosial dan pendidikan. Berdasarkan hasil angket, pengamatan dan tanya jawab dengan peserta pelatihan, tampak bahwa peserta bersemangat mengikuti kegiatan pelatihan ini. Peserta dapat menggunakan perintah-perintah analisis regresi logistik untuk data penelitian ilmu sosial dan pendidikan serta dapat memberikan interpretasi dari output program R secara tepat.

Pengelompokkan Kecamatan Berdasarkan Alat Kontrasepsi Menggunakan Algoritma K-Means Putri Puspita Sari; Kismiantini Kismiantini
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Family Planning (KB) participants are couples of childbearing age who are using one of the modern contraceptives in the year of implementation of family data collection. The purpose of this study was to classify sub-districts in the DI Yogyakarta Province based on family planning contraceptives using the K-Means algorithm. The data used is the percentage of contraceptive users in the DI Yogyakarta Province in 2021 obtained from the Population and Family Information System. The research variables were 7 contraceptives, namely IUD, MOW, MOP, condoms, implants, injections, and pills. Determining the number of clusters using Principal Component Analysis obtained 2 clusters with within cluster sum of squares of 45.6%. The results showed that cluster 1 (30 sub-districts) consisted of IUD, MOW, MOP, and condoms. Cluster 2 (48 sub-districts) consists of implants, injections, and pills. Clusters are named based on the place where the contraceptive device was installed, cluster 1 for sex, and cluster 2 for non-gender.

Multilevel Model Analysis to Investigate Predictor Variables in Mathematics Achievement PISA Data Fani Yunida Anggraheni; Kismiantini Kismiantini; Fajar Ediyanto
Southeast Asian Mathematics Education Journal Vol 12, No 2 (2022)
Publisher : SEAMEO Regional Centre for QITEP in Mathematics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46517/seamej.v12i2.184

This study aims to examine the relationship between predictor variables at the student and school levels and the interaction between variables in predicting mathematics achievement in Indonesia. Stratified analysis was implemented in Indonesia’s Programme for International Student Assessment (PISA) 2018 data. The variables of student level encompassed gender, economic, social, and cultural status (ESCS), metacognition, and learning time. This study revealed that the variables of ESCS, metacognition and learning time possessed a significant positive effect on mathematics achievement. The variables of school level are class size, school type, school size, and student-teacher ratio. This study demonstrated that only the data of class size produced a significant effect on mathematics achievement. Furthermore, the interaction between the learning time and class size also significantly affected learning achievement in mathematics. Therefore, variables increasing students’ mathematics achievement are ESCS, metacognition, learning time, class size, and interaction of learning time and class size.

Workshop on Comparative analysis of k populations with Non Parametric for Research in Social Sciences and Education Rosita Kusumawati; Dhoriva Urwatul Wutsqa; Kismiantini Kismiantini; Syarifah Inayati; Muhammad Fauzan; Ezra Putranda Setiawan; Bayutama Isnaini
Jurnal Pengabdian Masyarakat MIPA dan Pendidikan MIPA Vol 6, No 2 (2022): Vol 6, No 2 (2022)
Publisher : Yogyakarta State University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpmmp.v6i2.46055

Data obtained from social science and education research is often in the form of categorical data, namely nominal or ordinal. This makes the parametric approach less appropriate for use in some social science and education data. One solution is to use a nonparametric approach. This underlies the holding of community service activities in a workshop on comparison analysis of k population with a nonparametric approach for social science research and education. Participants in this workshop consisted of academics and practitioners, and students from various study programs in Indonesia. The workshop was carried out by providing material and demonstrating using R software as an analytical tool, which was held online for two days. On the first day, the material presented was a nonparametric approach to the comparison of k independent populations along with a demonstration of using R software, while for k dependent populations along with a demonstration of using R software was given on the second day. Participants were given data on social sciences and education in providing materials and demos of the R software. Based on the results of questionnaires, observations, and questions and answers, participants seemed enthusiastic in participating in the R software's material and demo sessions. In addition, participants can perform various tests in a nonparametric approach for k independent and dependent populations using the R software. Participants can also provide an accurate interpretation of the output of the R software.

Co-Authors Adi Cilik Pierewan Afriadi Gunandi Andriati Langiran Ariyadi Wijaya Bayutama Isnaini Dhoriva Urwatul Wustqa Dhoriva Urwatul Wutsqa Endang Listyani Ezra Putranda Setiawan Ezra Putranda Setiawan Fajar Ediyanto Fajra Husniyah Fani Yunida Anggraheni Mathilda Susanti Muhammad Fauzan Muhammad Fauzan Osval Antonio Montesinos-López Osval Antonio Montesinos-Lopez Putri Puspita sari Retno Subekti Rosita Kusumawati Rosita Kusumawati Rosita Kusumawati Sahid Sahid Sahid Sahid Syarifah Inayati Syarifah Inayati

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