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Pratiwi, Hasih
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Penerapan Model Epidemic Type Aftershock Sequence (ETAS) pada Data Gempa Bumi di Nusa Tenggara Barat Annisa Indah Kurnia; Hasih Pratiwi; Sugiyanto Sugiyanto
Prosiding Industrial Research Workshop and National Seminar Vol 10 No 1 (2019): Prosiding Industrial Research Workshop and National Seminar
Publisher : Politeknik Negeri Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.464 KB) | DOI: 10.35313/irwns.v10i1.1445

Abstract

Kejadian gempa bumi bersifat acak, sehingga pengembangan metode prakiraan gempa bumi sangat diperlukan. Salah satu metode prakiraan gempa bumi dari aspek stokastik adalah proses titik. Model epidemic type aftershock sequence (ETAS) merupakan model pada proses titik yang mempertimbangkan keterkaitan gempa satu dengan yang lainnya. Model ETAS dinyatakan dengan fungsi intensitas bersyarat yang berguna untuk mengetahui peluang kemunculan terjadinya gempa bumi. Tujuan penelitian ini adalah menerapkan model ETAS pada data gempa bumi di Nusa Tenggara Barat. Metode estimasi likelihood maksimum digunakan untuk memperoleh estimasi parameter model ETAS. Hasil estimasi parameter tersebut yaitu laju kegempaan dasar sebesar 0.0080, produktivitas gempa susulan sebesar 1.9066, efisiensi gempa bumi dengan magnitudo tertentu menghasilkan gempa susulan sebesar 0.9192, skala waktu laju peluruhan gempa susulan sebesar 0.0237, dan laju peluruhan gempa susulan sebesar 1.0923.
Parameter Estimation Robust Regression Method of Moment (MM) in Cases of Maternal Death in Indonesia Putri Ayu Pramesti; Yuliana Susanti; Hasih Pratiwi
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Bidang MIPA dan Kesehatan
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.348 KB)

Abstract

Regression analysis is used to determine the relationship between the dependent and independent variables with a parameter estimator. The parameter estimator that is usually used is the Least Squares Method (LSM), this requires a classical assumption test. Some cases have normality assumptions that are unfulfilled because there are outliers so the result regression parameter estimates are not accurate so that robust regression is used in the analysis. Robust regression is a regression analysis method that can withstand outliers. The purpose of this study is the application of robust regression estimation Method of Moment (MM) with Tukey Bisquare weighting in the case of data on the number of maternal deaths in Indonesia 2020 with the number of maternal deaths as a dependent variable, and with independent variables such as the number of pregnant women who experience bleeding, the number of diabetics in pregnancy, and the number of HIV positive in pregnancy. The result showed that every one unit increase of three independent variables had a positive effect on the number of cases of maternal deaths, each of which was 2,8064; 2,5014; 1,1577.
Vocational High School Students Ability in Mathematics Literacy Asih Ciptaningtyas; Mardiyana Mardiyana; Hasih Pratiwi
Pancaran Pendidikan Vol 7, No 1 (2018)
Publisher : The Faculty of Teacher Training and Education The University of Jember Jember, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (373.377 KB) | DOI: 10.25037/pancaran.v7i1.143

Abstract

Mathematical literacy is a person's ability to formulate, apply, and interpret mathematics in various contexts. This study is a qualitative descriptive that aims to describe the ability of mathematics literacy of students in the subject of exponents and logarithms in Vocational High School. Data analysis is done by collecting data, reducing data, and verifying data. The results obtained in this study are subjects with values above the MEC can solve the problem by using information, performing representations based on concepts, using procedural knowledge in the form of algebraic manipulation in accordance with the nature of exponents and logarithms, and can connect it with the real world to determine the outcome of completion, according to level 4 PISA. Subjects with the same value as MEC can solve problems, interpret by using the properties of exponents and logarithms, and implement procedures according to the 3rd level of PISA. Subjects below the MEC can only solve commonly resolved problems using simple properties, corresponding to the PISA 1st level.
Peramalan curah hujan di kota bandung menggunakan singular spectrum analysis Tri Kartika Febrianti; Winita Sulandari; Hasih Pratiwi
Jurnal Ilmiah Matematika Vol 8, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/konvergensi.v0i0.21461

Abstract

Curah hujan merupakan fenomena alam yang selalu terjadi di Indonesia setiap tahunnya. Fenomena ini bisa saja menyebabkan bencana seperti banjir dan tanah longsor. Adanya peramalan sangat dibutuhkan sebagai bentuk peringatan dini mengenai kondisi di waktu yang akan datang. Singular Spectrum Analysis (SSA) merupakan suatu teknik analisis deret waktu dan peramalan. SSA bertujuan untuk menguraikan deret waktu asli menjadi sejumlah kecil komponen yang dapat diinterpretasikan menjadi tren, osilasi dan noise. Tujuan dari penelitian ini yaitu menyajikan model peramalan curah hujan di Kota Bandung menggunakan metode Singular Spectrum Analysis (SSA). Berdasarkan penelitian ini, diketahui bahwa data curah hujan di Kota Bandung memiliki pola musiman. Penentuan window length (L) dilakukan dengan trial and error, yang dalam kasus ini diperoleh window length 17. Melalui dekomposisi dan rekonstruksi dengan window length 17 diperoleh 4 pengelompokan, yaitu satu kelompok tren dan tiga kelompok musiman. Pada penelitian ini digunakan RMSE untuk mengukur kesalahan hasil peramalan. Berdasarkan hasil pengujian dengan metode Singular Spectrum Analysis (SSA) diperoleh RMSE sebesar 167,510.
KLASIFIKASI PENYAKIT PNEUMONIA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK DENGAN OPTIMASI ADAPTIVE MOMENTUM Lingga Aji Andika; Hasih Pratiwi; Sri Sulistijowati Handajani
Indonesian Journal of Statistics and Applications Vol 3 No 3 (2019)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v3i3.560

Abstract

Pneumonia is an infection of the bacterium Streptococcus pneumoniae which causes inflammation in the air bag in one or both lungs. Pneumonia is a disease that can spread through the patient's air splashes. Pneumonia can be dangerous because it can cause death, therefore it is necessary to have early detection using chest radiograph images to determine the symptoms of pneumonia. Diagnosis using a chest radiograph image manually by medical personnel or a doctor requires a long time, even difficult to detect pneumonia disase. Convolutional neural network (CNN) is a deep learning method that adopts the performance of human brain neurons called neural network and convolution functions to classify images. CNN can also help classify pneumonia based on chest radiograph images. This study used data from Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification as many as 5860 images entered into two classes, namely normal and pneumonia, then 2400 data samples were taken using simple random sampling. This study uses adaptive momentum optimization (Adam) which serves to improve the accuracy of the model. Adam optimization is a development of existing optimizations such as Stochastic gradient descent (SGD), AdaGard, and RMSProp. The classification results of the models built were 99.98% for training data with 100 epochs, and accuracy in the test data was 78% which means that the model was able to qualify 78% of the test data into normal classes and pneumonia appropriately.
Co-Authors Annisa Indah Kurnia Ardina Nilam Prawastyorini Asih Ciptaningtyas Budiyono Budiyono Fransisca Trisnani Ardikha Putri Hafiz Yusuf Heraldi Handajani Handajani Handajani, Sri Sulistijowati Isnandar Slamet Kiki Ferawati Lingga Aji Andika Mardiyana Mardiyana Muhammad Bayu Nirwana Nabila Churin Aprilia Niswatul Qona’ah Nur Rohman Putri Ayu Pramesti Siti Khodijatunnuriyah Sugiyanto Sugiyanto Sugiyanto Sugiyanto Tito Tatag Prakoso Tri Kartika Febrianti Ulinnuha Rhohmawati Winita Sulandari Yuliana Susanti Yuliana Susanti Yulvia Fitri Rahmawati Zukhronah, Etik