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All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Statistika Universitas Muhammadiyah Semarang CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Antropologi: Isu-Isu Sosial budaya Jurnal Sains Matematika dan Statistika Science and Technology Indonesia AGRISAINTIFIKA Jurnal Ilmu-ilmu Pertanian JURNAL GALUNG TROPIKA Jurnal Matematika: MANTIK Jurnal Elementer (Elektro dan Mesin Terapan) Desimal: Jurnal Matematika Syntax Literate: Jurnal Ilmiah Indonesia BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) International Journal of Supply Chain Management JURNAL AGRIBISAINS Eksakta : Berkala Ilmiah Bidang MIPA M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jurnal Matematika UNAND JAS (Jurnal Agri Sains) Jurnal Baabu Al-ilmi : Ekonomi dan Perbankan Syariah Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Jurnal Kajian Matematika dan Aplikasinya Daengku: Journal of Humanities and Social Sciences Innovation Journal of Science and Technology Lattice Journal : Journal of Mathematics Education and Applied STATISTIKA IIJSE Prosiding Seminar Nasional Unimus Jurnal Research Ilmu Pertanian BAABU AL-ILMI: Ekonomi dan Perbankan Syariah
Devianto, Dodi
Department Of Mathematics And Data Science, Andalas University
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Perankingan Proporsi Kematian Pasien Covid-19 di Indonesia Menggunakan Metode Bayes Muhammad Qolbi Shobri; Ferra Yanuar; Dodi Devianto
Statistika Vol. 21 No. 2 (2021): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v21i2.328

Abstract

Jumlah kematian akibat terinfeksi Coronavirus Deases 2019 (Covid-19) kian hari kian bertambah. Hal ini dikarenakan belum ada obat yang tepat dan penanganan yang baik dalam mengatasi Covid-19 ini. Hampir setiap provinsi di Indonesia angka kematian akibat terinfeksi penyakit ini terbilang cukup memprihatinkan. Hal ini perlu dilakukan perankingan wilayah untuk melihat pemusatan daerah yang memiliki tingkat proposi kematian yang tinggi. Perankingan adalah upaya untuk mengurutkan sesuatu dari yang terbaik sampai yang terburuk dan sebaliknya. Nilai yang diurutkan berdasarkan hasil pendugaan parameter populasi seperti mean, standar deviasi, proporsi dan lain sebagainya. Penelitian ini bertujuan untuk melakukan perankingan proporsi kematian pasien Covid-19 di Indonesia dengan menggunakan metode Bayes. Metode bayes merupakan salah satu teknik pendugaan parameter yang menggunakan fungsi likelihood dengan fungsi distribusi prior untuk memperoleh distribusi posterior. Nilai mean dari distribusi posterior akan dijadikan parameter dugaan dari metode Bayes. Data penelitian ini diasumsikan berdistribusi Binomial dengan parameter p sebagai proporsi tingkat kematian. Dari penelitian ini diperoleh bahwa provinsi Jawa Timur, Lampung dan Sumatera Selatan merupakan daerah dengan proporsi kematian pasien Covid-19 tertinggi. Sementara itu, provinsi Jawa Barat, Kalimantan Barat dan Papua memiliki proporsi kematian pasien Covid-19 yang lebih rendah dibandingkan dengan provinsi lainnya.
PEMODELAN ARIMA-GARCH UNTUK VOLATILIAS DAN VALUE AT RISK PADA SAHAM PT. GUDANG GARAM TBK Rosi Ramayanti; Dodi Devianto; Delvia Alhusna
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.373

Abstract

Investment is one of the development factors in economic activity, there are two basic things that investor must know before making investment decisions, namely: returns and risk. One of the statistical methods to calculate the maximum loss in investment is Value at Risk (VaR). this study aims to calculate VaR on the closing stock price data of Pt. Gudang Garam TBK for the daily period starting from 4 January 2021 to 30 December 2021. Log return data is model by ARIMA. The ARIMA model contains a heteroscedasticity effect so it is inadequate for modelling, one of the models that can overcome the heteroscedasticity problem is the ARCH-GARCH model. Forecasting the volatility of the data is done using the ARCH-GARCH model. The results show that the GARCH (1,1) is the best model for predicting volatility. Volatility is predicted for the next 30 days, after the volatility forecasting results are obtained, the VaR calculation can be continued. Based on the results, it shows that volatility increases over time, which means that the risk that investor will accept will be higher and the returns will also be greater
PEMODELAN PERTAMBAHAN TINGGI BADAN BALITA STUNTING DI KABUPATEN SOLOK DENGAN METODE REGRESI TOBIT KUANTIL BAYESIAN Arfarani Rosalindari; Ferra Yanuar; Dodi Devianto
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.383

Abstract

This study analyzes the model of stunting toddler height gain and its influencing factors with Bayesian Tobit Quantile Regression (BTQR). The data used in this study are secondary data in the form of height data for stunting toddlers in Solok Regency, West Sumatra in calculations conducted in August 2021 and February 2022 obtained from the Solok Regency Health Office, West Sumatra. After analyzing the height gain data with the BTQR method, it was found that the model at quantile 0.50 was the best model because it produced smaller MAE and RMSE values than other quantiles in estimating parameters with the BTQR method and it was found that the exclusive breastfeeding variable  and the Immunization variable  had a significant effect on the height gain of stunting toddlers
PEMODELAN DATA HARGA CABAI DENGAN PENDEKATAN DERET WAKTU FRAKSIONAL ARFIMA Elsa Wahyuni; Dodi Devianto; Maiyastri Maiyastri
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.399

Abstract

Long-memory is a type of time series data that has a high correlation between long observation times. This can be seen from the autocorrelation function where the lag falls slowly over a long period. Such long-memory data can be modeled in the form of an Autoregressive Fractionally Integrated Moving Average (ARFIMA). One of the data that meets the long-memory criteria is the monthly chili price from March 2017 to April 2023 as much as 73 data. ARFIMA model selection is done by comparing the AIC and BIC values of each candidate model, so that the best model is ARFIMA (1;0.22785;0), this means that the movement of chili prices is influenced by previous prices in the long term
PERBANDINGAN METODE MLE BAYESIAN LOSS FUNCTION DALAM PENDUGAAN PARAMETER DISTRIBUSI INVERS RAYLEIGH Muhammad Iqbal; Ferra Yanuar; Dodi Devianto
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.400

Abstract

The purposes of this study are to estimate the scale parameter  of invers Rayleigh distribution under MLE, Bayesian Generalized square error loss function (SELF), and Bayesian LINEX loss function . The posterior distribution is considered to use two types of prior, namely Jeffrey’s prior and exponential distribution. The proposed methods are then employed in the real data. Several criteria AIC, AICc, and BIC for the selection model are considered in order to identify the method which results in a suitable value of parameter estimated. This study found that Bayesian Generalized SELF at first polynomial  and Bayesian LINEX loss function under exponential distribution  yielded better estimation values than MLE based on AIC, AICc, and BIC
MODEL VOLATILITAS SAHAM LQ45 DENGAN PENDEKATAN MARKOV-SWITCHING GARCH Ermanely Ermanely; Dodi Devianto; Ferra Yanuar
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.402

Abstract

Financial markets have an important role in the economy of a country including Indonesia. One of the activities chosen by investors in the financial market is investing. In the world of investment, especially in stocks, there is a phenomenon of volatility, which is a situation where a stock price value increases and decreases. Volatility in this financial market is something that is very interesting for investors because of its impact on the existence of global financial markets. The purpose of this study is to model the LQ45 index data using a model that can overcome the problem of heteroscedasticity and changes in data structure. The commonly used model for heteroscedasticity problem is ARCH/GARCH. Furthermore, a model that can account for structural changes is the Markov Switching model. The model that can overcome the problem of heteroscedasticity as well as structural changes is the MS GARCH model. The financial data used in this study are daily data for the LQ45 Index from 10 June 2019 to 28 May 2020. Based on the results of data analysis conducted using the MS GARCH model is the best model in modelling the volatility of the LQ45 index. The best model selection uses the criteria for the AIC and BIC values with the smallest value
PENGELOMPOKKAN KABUPATEN/KOTA DI INDONESIA BERDASARKAN MASALAH GIZI BALITA DENGAN MENGGUNAKAN METODE TWO STEP CLUSTER DAN ENSEMBLE CLUSTERING Cichi Chelchillya Candra; Ferra Yanuar; Dodi Devianto
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.413

Abstract

The purpose of this study was to group districts/cities in Indonesia based on toddler nutrition problems.. The research method used in this research is Two Step Cluster, Fuzzy C-Means and K-Modes method. In the Two Step Cluster method, there are two stages carried out, namely Pre-Clustering and Case of Clustering. In the Ensemble K-modes method, there are two methods, namely Fuzzy C-Means and K-Modes. The data used in this study are secondary data in the form of data on under-five nutrition problems in Indonesia in 2022. After analysis, the grouping results obtained using the Two Step Cluster method consist of 2 clusters, while the Ensemble K-modes method produces 5 clusters
Pengklasteran Kabupaten/Kota di Indonesia Berdasarkan Masalah Gizi Balita Dengan Menggunakan Metode Two Step Cluster dan Ensemble K-Modes Cichi Chelchillya Candra; Ferra Yanuar; Dodi Devianto
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v7i10.13108

Abstract

Pemerintah selalu berupaya untuk mengurangi prevalensi masalah gizi yang terjadi pada anak melalui berbagai program kesehatan. Namun karena berbagai masalah gizi tersebut memiliki penanganan yang berbeda, maka pemerintah suatu daerah perlu mengetahui masalah gizi anak apa yang dominan ditemui di daerahnya sehingga program yang akan dijalankan tepat. Tujuan dari penelitian ini adalah mengklasterkan kabupaten/kota di Indonesia berdasarkan masalah gizi balita dengan menggunakan metode Two Step Cluster dan Ensemble K-Modes serta mendeskripsikan karakteristik masalah gizi pada masing-masing klaster akhir yang terbentuk. Objek yang diamati pada penelitian ini terdiri dari 492 kabupaten/kota di Indonesia. Data yang digunakan yaitu data masalah gizi balita di semua kabupaten/kota di Indonesia. Hasil penelitian ini yaitu pengklasteran kabupaten/kota di Indonesia berdasarkan masalah gizi balita menggunakan metode two step cluster dan ensemble k-modes menghasilkan klaster yang berbeda. Metode ensemble k-modes lebih baik dalam mengklasterkan data gizi balita daripada metode two step cluster. Hal ini dapat dilihat dari nilai keragaman pengklasteran yang lebih kecil, yaitu 0,569015. Karakteristik klaster 1 menunjukkan bahwa sebagian besar kabupaten/kota dalam klaster ini terletak di wilayah Indonesia bagian barat, dengan total 229 kabupaten/kota.
Pemodelan Gizi Buruk Balita Di Indonesia Dengan Model Robust Spasial Autoregresif Tasya Abrari; Ferra Yanuar; Dodi Devianto
Jurnal Sains Matematika dan Statistika Vol 9, No 2 (2023): JSMS Juli 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v9i2.23362

Abstract

Gizi buruk merupakan suatu keadaan kekurangan konsumsi zat gizi yang disebabkan oleh rendahnya konsumsi energi protein dalam makanan sehari-hari, ditandai dengan berat dan tinggi badan di bawah rata-rata. Penelitian ini bertujuan untuk menentukan model terbaik pada kasus gizi buruk balita serta melihat faktor-faktor apa saja yang mempengaruhi gizi buruk balita pada provinsi-provinsi di Indonesia. Data yang digunakan adalah data hasil studi status gizi Indonesia oleh Kementerian Kesehatan Republik Indonesia. Untuk mendapatkan model terbaik, diperlukan model regresi spasial dengan mempertimbangkan pengaruh spasial suatu daerah. Metode regresi spasial yang menunjukkan adanya efek spasial pada variabel terikatnya disebut Spatial Autoregressive Model (SAR). Pada kasus tertentu, pengujian efek spasial yang melibatkan data pencilan menyebabkan suatu metode gagal dalam menangani efek spasial tersebut sehingga perlu adanya kombinasi model SAR dengan metode regresi robust yang membentuk Robust Spatial Autoregressive Model (RSAR). Hasil penelitian menunjukkan bahwa variabel persentase asuransi kesehatan dan akses air bersih berpengaruh terhadap gizi buruk balita. RSAR M-estimator mengakomodir keberadaan outlier dalam model regresi spasial, hal ini ditunjukkan dengan penurunan RMSE yang disebabkan oleh perubahan parameter koefisien penduga. Model Robust-SAR merupakan model terbaik karena memiliki nilai RMSE terkecil serta robust terhadap spatial outlier.
Bantuan Dana Hibah Anggaran Pendapatan dan Belanja Daerah (APBD) dan Pengaruhnya Terhadap Kinerja Manajemen BAZNAS di Provinsi Sumatera Barat Rini ELvira; Yaswirman Yaswirman; Nursyirwan Effendi; Dodi Devianto
Jurnal BAABU AL-ILMI: Ekonomi dan Perbankan Syariah Vol 8, No 2 (2023)
Publisher : Universitas Islam Negeri Fatmawati Sukarno Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29300/ba.v8i2.12298

Abstract

This study aims to determine the causal-comparative relationship between the variable of APBD grant funding assistance and BAZNAS management performance. This study involved all BAZNAS in West Sumatra Province selected by total sampling with data sourced from PuskasBAZNAS publication. Simple linear regression analysis tested the comparative causal relationship between the two variables. The research show that the variable of APBDfunding does not affect to the management performance of BAZNAS in West Sumatra Province, but it is influenced by other factors, such as leadership, employees and organisational culture, availability of financial resources, governance, policies and strategies, technology utilisation, muzakki trust in BAZNAS, transparency and accountability, and local cultural values. The implication of this research is as a basis for future local government policy considerations in allocating APBD grant funding assistance, and for BAZNAS efforts to improve the efficiency and effectiveness of BAZNAS in zakat management.
Co-Authors Abdi Mulya Acnesya, Vivin Admi Nazra Afnanda, Afridho Afrimayani Afrimayani Ainul Mardhiyah, Ainul Almuhayar, Mawanda Amalia Dwi Putri AMALIA DWI PUTRI ANNISA RAHMADIAH Arfarani Rosalindari ARNEZDA PUTRI Arrival Rince Putri Asdi, Yudiantri Astari Rahmadita Aulia Safitri Bahri, Susila Baqi, Ahmad Iqbal Boby Canigia Bukti Ginting Cesa Febri Desti Cichi Chelchillya Candra Cichi Chelchillya Candra Cindyana Aldrifisia Cintya Mukti Citra Ariadini Chairunnisa Claudia Putri Zoelanda Darvi Mailisa Putri Defriman Djafri Delvia Alhusna Des Welyyanti Desi Susanti Dina Monica DIRAMADHONA MUTIASALISA Efendi Efendi Eka Rahmi Kahar Elfa Rafulta Elfindri, Elfindri Elisa Sri Hastuti Elsa Wahyuni Elvi Yati Ermanely Ermanely Fadila Aulia Fadila Rasyid Fadilla Nisa Uttaqi Fajriyah, Rahmatika Faldo Aditya Farhah Anggana Fery Murtiningrum Fery Murtiningrum, Fery Finti Warni FITARI RESMALANI FITRI SABRINA Fitria Sarah Ginting, Yanti Mayasari Gusmanely Z Hafiz Rahman HANDIKA WAHYU VIKRANTHA Hasibuan, Lilis Harianti Hazmira Yozza Herliani Evinda Husnul Fikri Ihsan Kamal Ikhlas Pratama Sandi Irfan Suliansyah Istiqamah . Iswahyuli . Izzati Rahmi HG Jatu Visitasari Jayanti Herli Kamarni, Neng Khatimah, Havifah Husnatul Kiki Ramadani Lana Fauziah Lathifah Yulyanisa Lily Zuhrat Lita Wulandari Aeli Livia Amanda LOLANDA SYAMDENA M. Pio Hidayatullah M. Rizki Oktavian Maisan Nusa Putri Maiyastri Maiyastri, Maiyastri Majbur, Ridha Fauza maMaiyastri Maiyastri Mardha Tillah Maulini Septya Mawanda Almuhayar Mayastri Mayastri Melinda Noer Melisa Febriyana MUHAMMAD HAFANDRY Muhammad Iqbal Muhammad Qolbi Shobri Muhammad Ridho Muharisa, Catrin Mutia Yollanda Nadia Husna Nadya Risna Putri Narwen Narwen NASTHASYA, NOVALISA Nisa, Alvi Khairin Nova Noliza Bakar NOVALISA NASTHASYA Noverina Alfiany Nursyirwan Effendi, Nursyirwan NURUL AISHAH Nurwijayanti Olivia Prima Dini Partini Partini Partini Partini, Partini Puteri Bulqis Azhari Putri Permathasari Putri Permathasari Putri Putri Putri Riza Chaniago Radhiatul Husna Rahma Diana Safitri Rahmawati Ramadhan RAHMI HG, IZZATI Ramadhani, Eza Syafri Ramadhani, Nia Rasyid, Fadila Religea Reza Putri Riau, Ninda Permata Ridhatul Ilahi Ridho Pascal Willmar Ridho Saputra, Ridho Rini Elvira Riri Lestari Risma Yulia Rosi Ramayanti Rudiyanto Rudiyanto, Rudiyanto SAIDAH . Sani, Ridha Fadhila Saputri, Ovi Delviyanti SARAH SARAH Sarmada Sarmada Sarmada, Sarmada Selfinia, Selfinia SHINTA YULIANA Siska Dwi Kumala Sri Meiyenti Sri Wahyuni Sri Wahyuni Suci Sari Wahyuni SUMINDANG YUZAN Surya Puspita Sari Surya Puspita Sari, Surya Puspita Syauqi, Irfan Tasya Abrari Tessy Oktavia Mukhti Tiara Shofi Edriani Tomi Desra Yuliandi ULLYA IZZATY UMMU BUTSAINATUL EL KHAIR Uqwatul Alma Wisza Uswatul Hasanah Vira Agusta Wikasanti Dwi Rahayu William Huda Willmar, Ridho Pascal WULANDARI, FRILIANDA Yanuar, Ferra Yaswirman, Yaswirman Yosika Putri Yurinanda, Sherli Zetra, Aidinil Zuardin, Aulia Zul Ahmad Ersyad Zulakmal, Zulakmal