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All Journal EKSAKTA: Journal of Sciences and Data Analysis JURNAL DERIVAT: JURNAL MATEMATIKA DAN PENDIDIKAN MATEMATIKA BAREKENG: Jurnal Ilmu Matematika dan Terapan Delta: Jurnal Ilmiah Pendidikan Matematika Building of Informatics, Technology and Science Refleksi Pembelajaran Inovatif Jurnal Statistika dan Aplikasinya Parameter: Journal of Statistics Enthusiastic : International Journal of Applied Statistics and Data Science Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Bulletin of Social Informatics Theory and Application Emerging Statistics and Data Science Journal
Primandari, Arum Handini
Universitas Islam Indonesia
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Grey Double Exponential Smoothing Dengan Optimasi Levenberg-Marquardt Untuk Peramalan Volume Penumpang Di Bandara Soekarno-Hatta Primandari, Arum Handini
Jurnal Derivat: Jurnal Matematika dan Pendidikan Matematika Vol 3, No 2 (2016): Jurnal Derivat (Desember 2016)
Publisher : Pendidikan Matematika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (998.441 KB) | DOI: 10.31316/j.derivat.v3i2.715

Abstract

Aircraft has  became the best choice for long distance traveling because it has shortest travel time than any other transportations. Moreover, in recent years, aviation industries have competed for providing low cost flight so that it can also be enjoyed by middle class society. Thus escalate the popularity of aircraft as economical carrier. Knowing the volume of passengers in advance will help government and related institutions to effectively providing facilities. The volume of passengers can be predicted using classic model such as double exponential smoothing model which is simpler and has high accuracy. However, the randomness of Indonesian passenger volume data cause double exponential smoothing (DES) cannot follow both data pattern and data trend. Moreover, classic model often encounters overfitting where the prediction is bigger than the actual data. Therefore, we employed Grey Method applied on DES (GDES) to overcome this problem. GDES enabled the researcher to perform better data fitting because it would generate smoothing curve which showed clearer trend. As the result, although GDES fitting curve had higher error measurement (MSE) than DES, the forecasting result of GDES was more precise than DES. Keyword: Double Exponential Smoothing, Grey Method, Levenberg-Marquardt
An Alternative Forecasting Using Holt-Winter Damped Trend for Soekarno-Hatta Airport Passenger Volume Arum Handini Primandari
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 17, ISSUE 1, February 2017
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol17.iss1.art1

Abstract

Located in the capital city of Indonesia, Soekarno-Hatta Airport is considered as the main airport. Since there are some aviation companies providing low cost flight, the number people coming and leaving trough this airport has increased. The passenger volume can be considered as seasonal data since it shows increment in particular months, such as long holiday. Knowing in advance the volume of passenger will help the government to improve its service effectively. There is a simple and accurate method for forecasting seasonal data that is called Holt-Winter Exponential Smoothing (HWE). However, HWE always encounters over forecasting problem when it is employed to forecast in some future periods (m>1). In order to solve this problem, we add the damped parameter that will be damping the exponentially growth on HWE. This method called HWE damped trend. We employed the domestic passenger volume data of Soekarno-Hatta Airport from January 2008 till December 2015. This data collected from prior research. As the result, HWE damped trend outperforms traditional HWE on either training data set or testing data.
IMPLEMENTASI CRISP-DM MODEL MENGGUNAKAN METODE DECISION TREE DENGAN ALGORITMA CART UNTUK PREDIKSI LILA IBU HAMIL BERPOTENSI GIZI KURANG Dita Anies Munawwaroh; Arum Handini Primandari
Delta: Jurnal Ilmiah Pendidikan Matematika Vol 10, No 2 (2022): Delta : Jurnal Ilmiah Pendidikan Matematika
Publisher : Universitas Pekalongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31941/delta.v10i2.2172

Abstract

LILA is measured in pregnant women to monitor nutritional levels during pregnancy. The classifications in the LILA's measurement are the good nutrition category if the LILA measurement is more or equal to 23.5 cm and the undernutrition category if the LILA measurement is less than 23.5 cm. This study aims to classify LILA based on age, height, weight, blood pressure, hemoglobin level, blood sugar, gestational age, and hip circumference by employing the CRISP-DM methodology. The data used is from May till June 2022 at the Sumber Health Center, Sumber District, Rembang Regency. The decision tree method (decision tree) with the CART algorithm is worked to classify LILA in either the good or poor category. The data is divided into training and testing data by a ratio of 80%:20%. The decision tree method can classify all training data correctly. While evaluating the method with data testing produces values of accuracy, precision, recall, and f1-score, respectively, are 90%, 96%, 92%, and 94%.
Meningkatkan Partisipasi Peserta Didik Menggunakan Problem Based Learning dan Strategi Blended Learning Arum Handini Primandari; Ayundyah Kesumawati
Refleksi Pembelajaran Inovatif Vol. 2 No. 2 (2020): Volume 2 Nomor 2 Tahun 2020
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/rpi.vol2.iss2.art2

Abstract

Mata kuliah Statistika di Program Studi Ekonomi Islam, Fakultas Ilmu Agama Islam, Universitas Islam Indonesia memiliki bobot sks cukup tinggi yaitu 6 sks. Pada umumnya, mahasiswa dengan latar belakang non eksakta cenderung mengalami keengganan dan kejenuhan ketika belajar material eksak. Namun maraknya inovasi bidang digital dalam pendidikan membuka peluang untuk mengatasi permasalahan tersebut. Strategi blended learning (separuh tatap muka dan separuh daring) diharapkan menjadi variasi dalam proses pembelajaran. Oleh karena pembelajaran dilakukan secara jarak jauh akibat kebijakan terkait pandemi, blended learning dilaksanakan dengan daring sinkron dan daring asinkron. Untuk membantu mahasiswa dalam memahami teori statistika, digunakan metode PBL (Problem Based Learning). Problem ekonomi disampaikan di awal pembelajaran, kemudian diikuti dengan penyampaian teori statistika yang mendukung penyelesaian problem. Berdasarkan kuisioner dan wawancara, sebanyak 61.7% mahasiswa memilih preferensi pembelajaran secara blended learning. Delapan dari sepuluh mahasiswa setuju bahwa pemberian problem ekonomi membantu mereka untuk memahami kegunaan teori statistika. Sebesar 67% mahasiswa memperoleh nilai A. Keterbatasan strategi dan metode dalam penelitian ini adalah ketersediaan ruang bagi mahasiswa untuk berdiskusi menjadi minim. Diskusi yang sebelumnya direnccanakan dalam pertemuan taatp muka menjadi tidak terakomodasi dengan pertemuan daring sinkron
Optimalisasi Virtual Lab Dan Google Collaboratory Untuk Pembelajaran Daring Bersama Berbasis Collaborative Project Based Learning Kesumawati Ayundyah; Mifrahi Mustika Noor; Primandari Arum Handini
Refleksi Pembelajaran Inovatif Vol. 4 No. 1 (2022): Volume 4 Nomor 1 Tahun 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/rpi.vol4.iss1.art2

Abstract

Metode pembelajaran tardisional saat ini dirasa memiliki banyak kekurangan bagi pembelajaran mandiri peserta didik. Penelitian ini bertujuan untuk melihat bagaimana penerapan proses pembelajaran dengan pendekatan PjBL kolaboratif. Proyek diberikan kepada mahasiswa dari dua prodi berbeda yaitu program studi Statistik dan Ilmu Ekonomi dimana isu yang diberikan mengenai isu ekonomi dengan pendekatan statistik. Observasi dilakukan pada dua kelas dengan total jumlah mahasiswa sebanyak 105. Hasil penerapan PjBL kolaboratif menunjukkan terdapat peningkatan perolehan capaian CPMK saat mahasiswa melakukan kegiatan PjBL kolaboratif yang diarahkan oleh dosen, daripada kolaboratif mandiri. Ketercapaian CPMK dengan menggunakan PjBL kolaboratif mencapai 100%. Selian itu, mayoritas mahasiswa (62.5%) kegiatan PjBL kolaboratif lintas prodi ini dilaksanakan dengan baik. Penelitian ini mendukung adanya penerapan kegiatan PjBL kolaboratif untuk diterapkan pada mata kuliah lintas prodi.
Seismic analysis using maximum likelihood of gutenberg-richter Primandari, Arum Handini; Khotimah, Khusnul
Bulletin of Social Informatics Theory and Application Vol. 1 No. 1 (2017)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v1i1.23

Abstract

An earthquake is one of catastrophe which often claim numerous lives and cause great damage to infrastructure. Multiple studies from various field have been conducted in order to make a precise prediction of earthquake occurrence, such as recognizing the natural phenomena symptoms leading to the shaking and ground rupture. However, up till now there is no definite method that can predict the time and place in which earthquake will occur. By assuming that the number of earthquake follow Gutenberg-Richter law, we work b-value derived using Maximum Likelihood Method to calculate the probability of earthquake happen in the next few years. The southern sea of D.I. Yogyakarta was divided into four areas to simplify the analysis. As the result, in the next five years the first and second area have high enough probability (>0.3) to undergo more than 6.0-magnitude earthquake.
Job applicants clustering using self-organizing map Primandari, Arum Handini; Ikasakti, Nur Aini
Bulletin of Social Informatics Theory and Application Vol. 1 No. 2 (2017)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v1i2.28

Abstract

Yogyakarta Government through Directorate of Manpower and Transmigration (Disnakertrans) have been canvassing people looking for job. An employment program was provided by Disnakertrans to allow job applicants meet companies. This research was carried out to identify educational background of applicants, in order to obtain the suitable worker. One of the ways to identify educational background is by district clustering in Yogyakarta. Clustering method is employed to reveal the characteristic of educational quality in every district in Yogyakarta. Clustering is a grouping method which is done by minimalize the characteristic among class members and minimalize the characteristic among clusters. This research used Self Organizing Maps to grouping districts in Yogyakarta according to educational background of its job seekers. The clustering results 3 clusters: 6 districts belong to cluster 1, 4 districts belong to cluster 2, and 4 districts belong to cluster 3. Then, Yogyakarta map is used to visualize the result of district clustering.
A Multivariate Approach: Forecasting Jakarta Composite Using Prophet Facebook Primandari, Arum Handini; Iskandar , Shafa Amalia
Jurnal Statistika dan Aplikasinya Vol. 8 No. 1 (2024): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.08111

Abstract

The Jakarta Composite Index (JCI, Composite Stock Price Index / IHSG) presents the average share price movement of companies listed on the Indonesia Stock Exchange (BEI/IDX), which can reflect the stock market performance. JCI forecasting can provide benefits for investors regarding risk management. On the other hand, gold is a low-risk asset with no credit risk and maintains its value over time. During the pandemic, gold prices increased significantly while stock prices decreased sharply, so gold prices can be used as a regressor in forecasting the JCI. Researchers obtained historical data on the JCI and gold prices (dollars/ounce) from January 1, 2018, to December 31, 2022. The approach used in this research is multivariate in the Prophet model. The Prophet model uses a procedure to estimate time series data based on an additive model with trends that can be adjusted for annual, weekly, and daily seasonality. Based on the analysis results, the Prophet's multivariate approach is the best method for predicting the JCI compared to the univariate approach. The parameters used in the model are as follows: yearly seasonality, multiplicative seasonality mode, seasonality prior scale, namely 0.5, and changepoint prior scale, namely 0.001. The Mean Absolute Percentage Error (MAPE) obtained from the model is 2.78%.
Peramalan Harga Cabai Merah Besar Keriting Kabupaten Banyumas menggunakan Metode Arima Box-Jenkins Perihatini, Denisha Intan; Lestari, Indri Fauzi; Primandari, Arum Handini
Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya 2018: Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1753.989 KB)

Abstract

Cabai merupakan komoditas sayuran yang cukup strategis dan merupakan komoditas sayuran yang paling banyak disukai masyarakat Banyumas serta merupakan salah satu bahan makanan yang menyumbang inflasi di Kabupaten Banyumas. Pada musim tertentu, kenaikan harga cabai cukup signifikan sehingga mempengaruhi tingkat inlfasi. Dari berbagai jenis cabai yang ada, umumnya cabai merah besar keriting merupakan jenis cabai dengan harga yang lebih tinggi dibanding yang lainnya.Umumnya harga cabai merah akan turun seiring dengan berlalunya hari besar tertenut. Namun, sejak tahun 2014 harga cabai merah besar keriting terus mengalami kenaikan yang fluktuatif hingga awal tahun 2017. Hal tersebut tentunya meresahkan masyarakat mengingat ketergantungan masyarakat akan cabai merah besar keriting masih terbilang tinggi. Oleh karena itu diperlakukan analisis untuk meramalkan harga beli cabai dengan tujuan mengantisipasi adanya kenaikan harga cabai dimasa mendatang. Dari hasil analisis yang dilakukan menggunakan metode ARIMA Box-Jenkins didapatkan hasil peramalan harga cabai besar merah keriting Kabupaten Banyumas pada bulan Maret sampai bulan Desember tahun 2017 yaitu sebesar Rp 31.774,55; Rp 25.563,45; Rp 22.042,37; Rp 20.240,37; Rp 19.408,84; Rp 19.086,05; Rp 19.004,86; Rp 19.020,34; Rp 19.061,59 dan Rp 19.099,41.
Analisis Clustering Tingkat Pengangguran Terbuka di Provinsi DIY Tahun 2010-2022 dengan Dynamic Time Warping: Analisis Clustering Tingkat Pengangguran Terbuka di Provinsi DIY Tahun 2010-2022 dengan Dynamic Time Warping Nabilla Wardah Bonitta; Primandari, Arum Handini
Emerging Statistics and Data Science Journal Vol. 2 No. 1 (2024): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol2.iss.1.art13

Abstract

Pengangguran merujuk pada seseorang yang termasuk dalam angkatan kerja, secara aktif mencari pekerjaan pada tingkat upah tertentu, tetapi tidak berhasil mendapatkan pekerjaan yang diinginkan. Masalah pengangguran sangat rumit karena dipengaruhi oleh banyak faktor yang kompleks yang saling berinteraksi dan tidak mudah dipahami. Dalam pembangunan ekonomi negara-negara berkembang, masalah pengangguran yang semakin meningkat menjadi lebih kompleks dan serius daripada masalah perubahan dalam pembagian pendapatan yang tidak menguntungkan bagi penduduk berpenghasilan rendah. Penelitian ini dilakukan dengan tujuan mengelompokkan kabupaten/kota di D.I. Yogyakarta berdasarkan tingkat pengangguran terbuka menggunakan Clustering Hierarki metode Ward serta model Dynamic Time Warping (DTW) untuk mengidentifikasi kelompok-kelompok yang memiliki karakteristik serupa dalam data dan mengukur kesamaan antara dua deret waktu (Time Series). Dalam pengelompokan ini diperoleh pengelompokan sebanyak 2 dengan tingkat pengangguran terbuka pada cluster 2 memiliki persentase lebih besar (76%) dibandingkan cluster 1 (24%). Oleh karena itu, kabupaten/kota yang termasuk ke dalam cluster 2 (Sleman dan Yogyakarta) memiliki tingkat pengangguran terbuka yang lebih tinggi dibandingkan dengan kabupaten/kota yang termasuk ke dalam cluster 1 (Bantul, Gunungkidul, dan Kulon Progo).
Co-Authors Achmad Fauzan, Achmad Ayundyah Kesumawati Dita Anies Munawwaroh Fadlilah, Dhika Nurul Hanifah, Salsabila Ikasakti, Nur Aini Iskandar , Shafa Amalia Kesumawati, Ayundyah khusnul khotimah Kusuma Arum, Widya Larasati, Kinanti Dhea Lestari, Indri Fauzi Mustika Noor Mifrahi Nabilla Wardah Bonitta Nur Faizin Perihatini, Denisha Intan Rachmatia, Baiq Wita Thalib, Achmad Kurniansyah