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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Business Innovation and Entrepreneurship Journal Budapest International Research and Critics in Linguistics and Education Journal (Birle Journal) Jurnal Ilmiah Matematika Prosiding Konferensi Nasional PKM-CSR Industrial Research Workshop and National Seminar Prosiding University Research Colloquium Pancaran Pendidikan Jurnal Elektronika dan Telekomunikasi
Pratiwi, Hasih
Universitas Sebelas Maret
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Penerapan Model ARIMA-ARCH untuk Meramalkan Harga Saham PT. Indofood Sukses Makmur Tbk Yulvia Fitri Rahmawati; Etik Zukhronah; Hasih Pratiwi
Jurnal Inovasi Bisnis dan Kewirausahaan Vol 3 No 3 (2021): Business Innovation and Entrepreneurship Journal (August)
Publisher : Entrepreneurship Faculty, Universitas Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (380.444 KB) | DOI: 10.35899/biej.v3i3.307

Abstract

Abstract– The stock price is the value of the stock in the market that fluctuates from time to time. Time series data in the financial sector generally have quite high volatility which can cause heteroscedasticity problems. This study aims to model and to predict the stock price of PT Indofood Sukses Makmur Tbk using the ARIMA-ARCH model. The data used is daily stock prices from 2nd June 2020 to 15th February 2021 as training data, while from 16th February 2021 to 1st March 2021 as testing data. ARIMA-ARCH model is a model that combines Autoregressive Integrated Moving Average (ARIMA) and Autoregressive Conditional Heteroscedasticity (ARCH), which can be used to overcome the residues of the ARIMA model which are indicated to have heteroscedasticity problems. The result showed that the model that could be used was ARIMA(1,1,2)-ARCH(1). This model can provide good forecasting result with a relatively small MAPE value of 0.515785%. Abstrak– Harga saham adalah nilai saham di pasar yang berfluktuasi dari waktu ke waktu. Data runtun waktu di sektor keuangan umumnya memiliki volatilitas cukup tinggi yang dapat menyebabkan masalah heteroskedastisitas. Penelitian ini bertujuan untuk memodelkan dan meramalkan harga saham PT Indofood Sukses Makmur Tbk menggunakan model ARIMA-ARCH. Data yang digunakan adalah harga saham harian dari 2 Juni 2020 hingga 15 Februari 2021 sebagai data training, sedangkan dari 16 Februari 2021 hingga 1 Maret 2021 sebagai data testing. Model ARIMA-ARCH merupakan suatu model yang menggabungkan Autoregressive Integrated Moving Average (ARIMA) dan Autoregressive Conditional Heteroscedasticity (ARCH), yang dapat digunakan untuk mengatasi residu dari model ARIMA yang terindikasi memiliki masalah heteroskedastisitas. Hasil penelitian menunjukkan bahwa model yang dapat digunakan adalah ARIMA(1,1,2)-ARCH(1). Model tersebut mampu memberikan hasil peramalan yang baik dengan perolehan nilai MAPE yang relatif kecil yaitu 0,515785%.
Model ARIMA-GARCH Pada Peramalan Harga Saham PT. Jasa Marga (Persero) Fransisca Trisnani Ardikha Putri; Etik Zukhronah; Hasih Pratiwi
Jurnal Inovasi Bisnis dan Kewirausahaan Vol 3 No 3 (2021): Business Innovation and Entrepreneurship Journal (August)
Publisher : Entrepreneurship Faculty, Universitas Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (420.185 KB) | DOI: 10.35899/biej.v3i3.308

Abstract

Abstract– PT Jasa Marga is a great reputation company, the leader in comparable businesses, has a steady income, and paying dividends consistently. This paper aims to find the best model to forecast stock price of PT Jasa Marga using ARIMA-GARCH. The data used is daily stock price of PT Jasa Marga from March 2020 to March 2021. Autoregressive Integrated Moving Average (ARIMA) is a method that can be used to forecast stock prices. However, an economical data tend to have heteroscedasticity problems, one of the methods used to overcome them is Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Future stock price of PT Jasa Marga is forecasted with ARIMA-GARCH model. The data is modeled with ARIMA first, if there is heteroscedasticity, combine the model with GARCH model. The result of this study indicated that ARIMA (1, 1, 1) – GARCH (2, 2) is the best model, with MAPE 1,5647 Abstrak– PT Jasa Marga adalah perusahaan yang reputasinya baik, terdepan di perusahaan-perusahaan sejenis, stabil pendapatannya, dan pembayaran devidennya konsisten. Paper ini bertujuan untuk mencari model terbaik dalam meramalkan harga saham PT Jasa Marga menggunakan ARIMA-GARCH. Data harga saham yang diolah yaitu data sekunder dari PT Jasa Marga pada Maret 2020 hingga Maret 2021. Autoregressive Integrated Moving Average (ARIMA) sebagai metode yang dapat dimanfaatkan guna meramalkan harga saham. Akan tetapi, data tentang ekonomi cenderung memiliki masalah heteroskedastisitas, metode yang umum dipakai untuk mengatasinya adalah Generalized Autoregressive Conditional Heteroskedasticity (GARCH). Harga saham PT Jasa Marga diramalkan dengan model ARIMA-GARCH. Data terlebih dahulu dimodelkan dengan ARIMA, jika didapati adanya heteroskedastisitas, maka model tersebut dikombinasikan dengan GARCH. Penelitian ini menghasilkan ARIMA (1,1,1)-GARCH(2,2) sebagai model terbaik dengan MAPE 1,5647.
Analisis Data Panel pada Tingkat Pengangguran Terbuka Kabupaten/Kota di Pulau Jawa Hasih Pratiwi; Ardina Nilam Prawastyorini; Sugiyanto Sugiyanto
Jurnal Matematika, Statistika dan Komputasi Vol. 16 No. 1 (2019): JMSK, July, 2019
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (362.724 KB) | DOI: 10.20956/jmsk.v16i1.6713

Abstract

Unemployment rate is the percentage of the number of unemployed to the total labor force, it has become some problems in economic development. The aim of this study is to choose the best model between common, fixed, and random effects in modeling open unemployment rate of regency/city in Java. It based on open unemployment rate with several influence factors in Java Island 2010-2016 which are panel data types. The best model choosen based on the results of the Chow test and Hausman test. The fixed effect model was obtained as the best model with a value of  79,26 percent.
Sentiment Analysis Using Maximum Entropy on Application Reviews (Study Case: Shopee on Google Play) Ulinnuha Rhohmawati; Isnandar Slamet; Hasih Pratiwi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 5, No 1 (2019): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (287.386 KB) | DOI: 10.26555/jiteki.v5i1.13087

Abstract

Shopee was one of the e-commerce application that could found on Google Play. The amount of Shopee application reviews on Google Play continues to grow over time. These make the company trying to get the overall information from all reviews because it would take a long time to read each of the reviews on Google Play. Therefore analysis was used using text mining. One part of text mining was sentiment analysis that applied the maximum entropy method to classification. Based on the results of the analysis found an accuracy of 97.32%. By using the maximum entropy method it could be concluded that word association obtained related to “application”, “promo”, “satisfy”, and “discount” for positive sentiment. Meanwhile for negative sentiment, the reviewers of Shopee application on Google Play were related to “problematic”, “login”, “old”, “verification”, and “expensive”. The results of this research in Indonesian.
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.
The Analysis of Flipped Learning Model Based on Geogebra and PBL on Mathematics Nur Rohman; Budiyono Budiyono; Hasih Pratiwi
Budapest International Research and Critics in Linguistics and Education (BirLE) Journal Vol 5, No 1 (2022): Budapest International Research and Critics in Linguistics and Education, Februa
Publisher : BIRCU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birle.v5i1.3914

Abstract

This research is motivated by the low learning outcomes of students' mathematics with an average national exam of around 55 low, the low learning outcomes are influenced by one of various factors including learning models or methods which sometimes do not support mathematics. Based on this, an alternative learning model is needed to provide understanding both in terms of cognitive and psychomotor. In this case, the geogebra-based flipped learning model helps understand the theory and practice of mathematics. This study aims to determine the regression between flipped learning and problem based learning (PBL) learning models in learning outcomes using geogebra software. This research is in SMPN/SMPT/SMP with the subject of class VIII students. The type of research is an experiment with a 3x3 factorial design with a random sampling technique, each of which is taught using the Flipped learning and problem based learning (PBL) models. Collecting data with tests and questionnaires, while the data analysis technique using inferential analysis of MANOVA and two-way ANOVA through prerequisite, balance, hypothesis and further tests. The conclusion is the knowledge aspect, the GeoGebra flipped learning (FLG) learning model provides better knowledge aspects than the Flipped learning (FL) and problem-based learning (PBL) learning models. The FL learning model provides better knowledge aspects than problem based learning (PBL). Meanwhile, in terms of skills, Flipped learning (FL) learning model provides better skill aspects than problem based learning (PBL); in the aspect of high interpersonal communication knowledge have better knowledge aspects than students with moderate interpersonal communication and low interpersonal communication. Students with moderate interpersonal communication have better aspects of knowledge than students with low interpersonal communication. Meanwhile, in the aspect of skills, students with high interpersonal communication have better skill aspects than students with moderate interpersonal communication and low interpersonal communication. Students with moderate interpersonal communication have better skill aspects than students with low interpersonal communication.
Penggunaan Geoda untuk Pemetaan Bencana Alam di Kabupaten Karanganyar Hasih Pratiwi; Niswatul Qona’ah; Kiki Ferawati; Sri Sulistijowati Handajani; Handajani Handajani; Yuliana Susanti; Muhammad Bayu Nirwana
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 3 (2020): Peran Perguruan Tinggi dan Dunia Usaha Dalam Pemberdayaan Masyarakat Untuk Menyongsong
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.354 KB) | DOI: 10.37695/pkmcsr.v3i0.817

Abstract

Kemampuan mengolah data menjadi kebutuhan di masa kini, apalagi dengan banyaknya data yang tersedia yang dapat diakses secara bebas. Statistika dapat digunakan untuk membantu masyarakat dalam menjelaskan dan memahami gambaran tentang kejadian bencana alam. Karanganyar, yang terletak di Provinsi Jawa Tengah, merupakan salah satu kabupaten di Indonesia yang rawan bencana alam. Oleh karena itu, diperlukan visualisasi data sebagai upaya untuk memberikan pemahaman kepada masyarakat tentang bencana alam yang terjadi di wilayah Kabupaten Karanganyar. Pemetaan bencana alam dengan Geoda dapat memberikan informasi kondisi kecamatan-kecamatan di Karanganyar yang rawan bencana alam. Untuk menyusun peta, diperlukan data bencana alam serta file peta wilayah. Setelah program Geoda terinstal, peta dapat disusun melalui menu toolbar, mengurutkan kolom kode kabupaten, create project file, dan map. Peta spasial menunjukkan bahwa tanah longsor sering terjadi di wilayah Kabupaten Karanganyar bagian timur yang berbatasan dengan Kabupaten Magetan di Jawa Timur, kebakaran di bagian tengah, dan angin ribut di bagian utara.
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

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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.
Co-Authors Ade Ramdan Ana Heryana Annisa Indah Kurnia Ardina Nilam Prawastyorini Arnetta Listiana Dewi Asih Ciptaningtyas Asri R Yuliani Budiyono Budiyono Endang Suryawati Fransisca Trisnani Ardikha Putri Hafiz Yusuf Heraldi Handajani Handajani Handajani, Sri Sulistijowati Hilman F. Pardede 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