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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Kreativitas PKM Jambura Journal of Mathematics Jurnal Riset Pembangunan JSO: Journal of Social Outreach VARIANSI: Journal of Statistics and Its Application on Teaching and Research Eksponensial STATISTIKA
Meiliyani Siringoringo
Program Studi Statistika, Fakultas MIPA, Universitas Mulawarman
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Peramalan Inflasi Provinsi Kalimantan Timur Menggunakan Model Hybrid Singular Spectrum Analysis-Autoregressive Integrated Moving Average Melisa Arumsari; Sri Wahyuningsih; Meiliyani Siringoringo
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 1 (2021): September 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i1.14284

Abstract

The Singular Spectrum Analysis (SSA)-Autoregressive Integrated Moving Average (ARIMA) hybrid method is a good combination of forecasting methods to improve forecasting accuracy and is suitable for economic data that tends to have trend and seasonal patterns, one of which is inflation data. The purpose of this study is to obtain the results of inflation forecasting for East Kalimantan Province in 2021 using the SSA-ARIMA hybrid model. The results of the inflation forecasting for East Kalimantan Province in 2021 using the SSA-ARIMA(1,1,1) hybrid model overall experienced an increase and the highest inflation in 2021 occurred in December of 0.92% with a forecasting accuracy level based on the Root Mean Square Error (RMSE) was 0.069399 and Mean Absolute Percentage Error (MAPE) was 32.61084%  
Aplikasi Double Exponential Smoothing Holt dan Triple Exponential Smoothing Holt-Winter dengan Optimasi Golden Section untuk Meramalkan Nilai Ekspor Provinsi Kalimantan Timur Novita Andriani; Sri Wahyuningsih; Meiliyani Siringoringo
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 3 (2022): MAY, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i3.17492

Abstract

Exponential smoothing is one of the short term forecasting methods. The selection of the forecasting method can be done by considering the type of data pattern, such as the Double Exponential Smoothing (DES) Holt method which can be used on trend patterned data and the Triple Exponential Smoothing (TES) Holt-Winter method which can be used on trend and seasonal patterned data. The main problem in using the Holt DES and Holt-Winter TES methods is the parameter selection which is usually done by trial and error, but this method takes a long time so that in this research a more efficient method is used to obtain optimal parameters, namely the golden section method. The purpose of this research was to forecast and obtain the best method for forecasting the export value of East Borneo Province. The results showed that the forecasted of export values used the Holt DES, the additive Holt-Winter TES, and the multiplicative Holt-Winter TES with golden section optimization method had a MAPE of less than 10%, which means that the forecast used these methods were very good. The best method to predict the export value of East Borneo Province was the additive Holt-Winter TES with golden section optimization method.
PERAMALAN JUMLAH WISATAWAN MANCANEGARA MENGGUNAKAN MODEL ARIMA Annisa Fitri; Ika Purnamasari; Meiliyani Siringoringo
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 7, No 1 (2019): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (151.966 KB) | DOI: 10.26714/jsunimus.7.1.2019.%p

Abstract

Wisatawan mancanegara adalah setiap orang yang mengunjungi suatu negara di luar tempat tinggalnya, didorong oleh satu atau beberapa keperluan tanpa bermaksud memperoleh penghasilan di tempat yang dikunjungi. Kunjungan wisatawan mancanegara dapat berpengaruh terhadap penerimaan devisa negara dan perencanaan kedepan. Tujuan penelitian ini adalah untuk mengetahui model terbaik dan hasil peramalan berdasarkan data jumlah wisatawan mancanegara menurut pintu masuk Bandara Sultan Aji Muhammad Sulaiman Sepinggan Balikpapan Bulan Januari 2011 sampai Desember 2018. Model yang digunakan dalam penelitian ini adalah model ARIMA. Model ARIMA merupakan salah satu dari model deret waktu yang umum digunakan karena terdapat metode statistik, dikenal dengan metode Box-Jenkins yang digunakan dalam penentuan model. Model ARIMA juga memiliki tingkat akurasi peramalan yang cukup tinggi dan cocok digunakan untuk meramal sejumlah variabel dengan cepat dan akurat. Berdasarkan hasil analisis model ARIMA terbaik yaitu model ARIMA (2,1,0) yang memiliki nilai MSE sebesar 6,9267. Dengan rata-rata hasil peramalan jumlah wisatawan mancanegara menurut pintu masuk Bandara Sultan Aji Muhammad Sulaiman Sepinggan Balikpapan Bulan Januari sampai Desember 2019 sekitar 366 orang/bulan.
Peramalan Nilai Tukar Petani Subsektor Peternakan Menggunakan Fuzzy Time Series Lee Mahadi Muhammad; Sri Wahyuningsih; Meiliyani Siringoringo
Jambura Journal of Mathematics Vol 3, No 1: January 2021
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (648.747 KB) | DOI: 10.34312/jjom.v3i1.5940

Abstract

ABSTRAKFuzzy time series (FTS) Lee adalah suatu metode peramalan yang digunakan ketika jumlah data historis yang tersedia sedikit, serta tidak mensyaratkan asumsi-asumsi tertentu yang harus terpenuhi. Metode ini menggunakan data historis berupa himpunan fuzzy yang berasal dari bilangan real atas himpunan semesta pada data aktual. FTS Lee adalah perkembangan dari FTS Song dan Chissom, FTS Cheng, serta FTS Chen. Pada penelitian ini dibahas penerapan FTS Lee pada data Nilai Tukar Petani Subsektor Peternakan (NTPT) di Kalimantan Timur. Tujuan penelitian ini adalah memperoleh hasil peramalan NTPT di Kalimantan Timur pada bulan Januari 2020 dengan menggunakan FTS Lee. Langkah awal dalam penelitian ini yaitu menentukan himpunan semesta pembicaraan, langkah kedua menentukan banyaknya himpunan fuzzy, langkah ketiga mendefinisikan derajat keanggotaan himpunan fuzzy terhadap  dan melakukan fuzzyfikasi pada data aktual, langkah keempat membuat fuzzy logical relationship, langkah kelima membuat fuzzy logical relationship group, langkah keenam melakukan defuzzyfikasi sehingga diperoleh hasil peramalan, serta dilanjutkan dengan menghitung nilai mean absolute percentage error. Hasil penelitian menunjukkan bahwa peramalan menggunakan FTS Lee pada bulan Januari 2020 adalah 110,25. Nilai mean absolute percentage error pada  hasil peramalan dengan menggunakan FTS Lee adalah sangat baik.  ABSTRACTLee’s Fuzzy time series (FTS) is a forecasting method that is used when the number of historical data that available was small and does not require certain assumptions to be fulfilled. This method uses historical data in the form of fuzzy sets derived from real numbers over the set of universes in the actual data. FTS Lee is a development of FTS Song and Chissom, FTS Cheng, and FTS Chen. This research discusses the application of FTS Lee to the Exchange Rate of Farmers Subsectors Farm (ERFSF) in Kalimantan Timur. The purpose of this study was to obtain the results of ERFSF forecasting in Kalimantan Timur in January 2020 using FTS Lee. The first step during research is to determine the set of speech universes, the second step is to determine the number of fuzzy sets, the third step is to define the degree of fuzzy association membership and fuzzification on the actual data, the fourth step is to create a fuzzy logical relationship, the fifth step is to create a fuzzy logical relationship group, the sixth step is to perform defuzzification in order to obtain forecasting results, and continue by calculating the mean absolute percentage error value. The results showed that forecasting using FTS Lee in January 2020 was 110,25. The mean absolute percentage error value in forecasting results using FTS Lee is very good.
PELATIHAN MATEMATIKA DAN STATISTIKA CERDIK (CERDAS DAN ASYIK) UNTUK IBU-IBU DI DESA BUKIT RAYA KECAMATAN TENGGARONG SEBERANG Fidia Deny Tisna Amijaya; Wasono Wasono; Syaripuddin Syaripuddin; Yoki Novia Nasution; Meiliyani Siringoringo
Journal of Social Outreach Vol 1, No 2 (2022): Journal of Social Outreach
Publisher : Fakultas Sains dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.568 KB)

Abstract

Bukit Raya adalah salah satu Desa di Kecamatan Tenggarong Seberang, Kabupaten Kutai Kartanegara, Provinsi Kalimantan Timur, Indonesia. Desa Bukit Raya memiliki kepadatan penduduk yaitu 617 penduduk/km2 dan angka ini merupakan angka kepadatan rumah tangga paling tinggi di Kecamatan Tenggarong Seberang. Dari sisi pendidikan, jumlah siswa yang bersekolah di SD di Desa Bukit Raya berjumlah 527 siswa, dan belum ada siswa pada jenjang SMP dan SMA di Desa Bukit Raya, sehingga iklim akademis dirasa kurang. Oleh karena itu, perlu adanya kegiatan pengabdian kepada masyarakat dalam bentuk pelatihan matematika dan statistika Cerdas dan Asyik untuk menambah iklim akademis di Desa Bukit Raya. Kegiatan pengabdian kepada masyarakat menghasilkan data kuesioner pendampingan belajar dan data tes awal dan tes akhir Ibu-Ibu di Desa Bukit Raya. Data kuesioner pendampingan belajar akan dianalisis menggunakan statistika deskriptif untuk melihat seberapa banyak Ibu-Ibu di Desa Bukit Raya yang melakukan pendampingan belajar. Data tes awal dan tes akhir akan dianalisis menggunakan uji Wilcoxon untuk mengetahui ada tidaknya perubahan pemahaman terhadap pelatihan matematika dan statistika Cerdas dan Asyik. Hasilnya, 14 dari 40 peserta kegiatan pengabdian yang melakukan pendampingan belajar dan terdapat perbedaan rata-rata yang meningkat antara hasil tes awal dan tes akhir pelatihan matematika dan statistika Cerdas dan Asyik.Kata Kunci: Bukit Raya, Ibu, Matematika, Pelatihan, Statistika
Peramalan Jumlah Kunjungan Wisatawan Mancanegara ke Indonesia Menggunakan Analisis Intervensi Fungsi Step Adelia Ramadhani; Sri Wahyuningsih; Meiliyani Siringoringo
Jurnal Matematika, Statistika dan Komputasi Vol. 19 No. 1 (2022): SEPTEMBER, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v19i1.21607

Abstract

   Intervention analysis is a method for processing time series data that can be used to explain the effect of an intervention that is influenced by external and internal factors. One application of this method is the data on the number of foreign tourist visits. Since the emergence of COVID-19 in Indonesia, especially in March 2020, Indonesia has begun to implement a lockdown policy and restrict foreign tourists from entering Indonesia. Lockdown policy caused the number of foreign tourist arrivals to decreased drastically. The purpose of this study was obtained a model and forecast results for the number of foreign tourist arrivals for the period November 2021 to November 2022 used a step function intervention analysis. The results of the analysis was shown that the ARIMA intervention model (0,1,1) with a step function with an intervention orde of b=0, s=0, and r=0 was the best model. The results of forecasting the number of foreign tourist visits to Indonesia will increase slowly from November 2021 to November 2022 with a MAPE value 9.91%.
Peramalan Jumlah Produksi Kelapa Sawit Provinsi Kalimantan Timur Menggunakan Metode Singular Spectrum Analysis Meiliyani Siringoringo; Sri Wahyuningsih; Ika Purnamasari; Melisa Arumsari
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 4 No. 3 (2022)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm46

Abstract

Singular spectrum analysis (SSA) is a nonparametric method that does not rely on assumptions such as stationary nature or residual normality. SSA separates time series data into its components, which are trend, seasonality, and error (noise). This study aimed to obtain forecasting results for the amount of oil palm production in East Kalimantan Province for the period January 2021 to December 2021 using SSA. Based on the results of the data analysis, in the process of forming the forecasting model with in-sample data, the parameter window length (L) was 24, which produced a MAPE value of 0.464%, and while the forecasting model validation process used out-sample data, it produced a MAPE value of 41.172%.
Pelatihan Penggunaan Fungsi Hitung Dasar dan Logika Matematika Statistika untuk Penyelesaian TIU Ika Purnamasari; Meiliyani Siringoringo; Sri Wahyuningsih; Memi Nor Hayati; Suyitno Suyitno; Rito Goejantoro; Surya Prangga
Jurnal Kreativitas Pengabdian Kepada Masyarakat (PKM) Vol 6, No 1 (2023): Volume 6 No 1 Januari 2023
Publisher : Universitas Malahayati Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/jkpm.v6i1.8423

Abstract

ABSTRAK  Pegawai Negeri Sipil (PNS) yaitu warga negara Indonesia yang memenuhi syarat tertentu, diangkat sebagai Pegawai ASN secara tetap oleh pejabat pembina kepegawaian untuk menduduki jabatan pemerintahan. Pada proses perimaaan CPNS, terdapat dua tahapan Seleksi yaitu SKD dan SKB. Pada SKD, pemerintah memberlakukan passing grade yang menjadi penentu kelulusan ke tahap SKB. Salah satu jenis tes pada tahap SKD yaitu TIU yang merupakan tes untuk mengukur tingkat intelegensi dalam analisa numerik, verbal, figural, serta kemampuan untuk berpikir logis dan analitis. Tujuan kegiatan pelatihan yaitu memberikan informasi kepada masyarakat umum, khusunya masyarakat yang akan mengikuti tes seleksi SKD CPNS 2021 tentang penggunaan fungsi hitung dasar dan logika dalam mengerjakan soal TIU dengan lebih mudah, cepat dan tepat. Berdasarkan hasil penilaian pada saat pelatihan, peserta dapat menunjukkan adanya peningkatan pemahaman dalam menyelesaikan soal TIU dengan mudah, cepat dan tepat.  Hal ini terlihat dari peningkatan nilai skor posttes yang jauh lebih tinggi dibandingkan saat pretes. Kedepannya diharapkan adanya kegiatan lanjutan dengan intensif agar peserta kegiatan dapat terbiasa dalam pemecahan soal dengan cepat. Kata Kunci: ASN; PNS; SKB; SKD; TIU  ABSTRACT  Civil Servants (PNS) is an Indonesian citizen who meets certain conditions, appointed as an ASN employee regularly by the office of staffing to occupy government positions. In the CPNS acceptance process, there are two stages of selection, namely SKD and SKB. In SKD, the government imposes a passing grade that determines graduation to the SKB stage. One type of test at the SKD stage is TIU which is a test to measure the level of intelligence in numerical analysis, verbal ability, figural ability, and the ability to think logically and analytically. The purpose of the training is to provide information to the general public, especially the public who will take the 2021 SKD CPNS selection test on the use of fundamental calculation functions and logic in working on TIU problems more simply, quickly, and precisely. Based on the yield of the assessment at the time of training, participants can show an increased understanding of solving TIU problems simply, quickly, and precisely. The posttest score is much higher than during pretests. In the future, expected that this training can continue intensive so that participants can get used to solving problems more quickly. Keywords: ASN; PNS; SKB; SKD; TIU
Pemodelan Geographically Weighted Panel Regression pada Data Indeks Pembangunan Manusia di Provinsi Kalimantan Timur Tahun 2017-2020 Ni Made Shantia Ananda; Suyitno Suyitno; Meiliyani Siringoringo
Jurnal Matematika, Statistika dan Komputasi Vol. 19 No. 2 (2023): JANUARY 2023
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v19i2.23775

Abstract

Geographically Weighted Panel Regression (GWPR) model is a panel regression model applied on spatial data. This research applied Fixed Effect Model (FEM) on panel regression as the global model and GWPR as the local model for Human Development Index (HDI) regencies/municipalities in East Kalimantan Province data over the years 2017-2020. The aim of this research is to obtain the GWPR model of HDI data, as well as to acquire factors that influence it. The parameter of GWPR model was estimated on each observation location using the Weighted Least Square (WLS) method, namely Ordinary Least Square (OLS) with addition of spatial weighting. The spatial weighting on GWPR model was calculated using fixed bisquare, fixed tricube, adaptive bisquare and adaptive tricube. After the selection process, the optimum weighting function is adaptive tricube which provides a minimum Cross Validation (CV) value of 5.1419. Based on GWPR parameter testing, factors that affect HDI are local and diverse in each 10 regencies/municipalities in East Kalimantan Province. These factors are the labor force participation rate, number of health facilities, Gini ratio, population growth rate, open unemployment rate, poverty gap index and percentage of food expenditure. The coefficient of determination of the GWPR model obtains a value of 94.36% with the RMSE value of 0.1221.
Peramalan Menggunakan Model Hybrid ARIMAX-NN untuk Total Transaksi Pembayaran Nontunai Nuning Kusumaningrum; Ika Purnamasari; Meiliyani Siringoringo
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 01 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm57

Abstract

Non-cash payment transactions in Indonesia continue to experience an increase marked by the high consumptive behavior of the people. This consumptive behavior is based on the many attractive offers, especially on year-end holidays which are the effect of calendar variations. ARIMAX is a time series method that is able to detect the effects of calendar variations. Meanwhile, to increase the level of forecasting accuracy, it can be combined with other methods such as Neural Networks (NN). This study aims to predict the total non-cash payment transactions in Indonesia in the period January to December 2022 using the ARIMAX-NN hybrid model. Based on the forecasting results, four highly accurate models were obtained, namely the hybrid model ARIMAX(0,1,2)-NN 1 neuron, ARIMAX(0,1,2)-NN 2 neurons, ARIMAX(1,1,0)-NN 1 neurons, and ARIMAX(1,1,0)-NN 2 neurons with MAPE values ​​for each model below 5%. Based on the four models formed, the results of forecasting in the period January to December 2022 as a whole the data tends to fluctuate and has an upward trend pattern, especially in December, which is the month when year-end holidays occur.
Co-Authors Adelia Ramadhani Alfian Hidayat Anak Agung Gede Sugianthara Andrean Sergio Annisa Fitri, Annisa Darnah Andi Nohe Darnah Darnah Dini Elizabeth Dwi Ayu Anggraini Edy Fahrin Fidia Deny Tisna Amijaya Iis Yustiani Ika Purnamasari Khairun Nida Mahadi Muhammad Melisa Arumsari Melisa Arumsari Memi Nor Hayati Memi Nor Hayati Memi Nor Hayati Muhammad Fathurahman Nadya Pratiwi Ni Made Shantia Ananda Novita Andriani Nuning Kusumaningrum Prangga, Surya Puspa Chairina Rito Goejantoro Rito Goejantoro Sekar Nur Utami Siti Mahmudatur Rahmah Sri Wahyuningsih Sri Wahyuningsih Sri Wahyuningsih Sri Wahyuningsih Sri Wahyuningsih Suyitno Suyitno Suyitno Suyitno Suyitno Suyitno Syaripuddin Syaripuddin Ulfah Resti Inayah Vivi Dwi Lestari Wasono Wasono William Yulius Karimuse Yetty Veronica Lestari Sinaga Yoki Novia Nasution