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All Journal Jurnal Manajemen dan Organisasi Jurnal Gaussian Epsilon: Jurnal Matematika Murni dan Terapan IJIBE (International Journal of Islamic Business Ethics) Jurnal Al-Qardh BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Kajian Ilmiah Jurnal Abdimas Ekonomi dan Bisnis TIERS Information Technology Journal Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Selvi Annisa
Department Of Statistics, Faculty Of Mathematics And Natural Science, Universitas Lambung Mangkurat, Indonesia
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Pengaruh Covid-19, Nilai Tukar Rupiah dan Indeks Harga Saham Gabungan Asing Terhadap Indeks Harga Saham Gabungan Indonesia (IHSG) Novia Nour Halisa; Selvi Annisa
Jurnal Manajemen dan Organisasi Vol. 11 No. 3 (2020): Jurnal Manajemen dan Organisasi
Publisher : IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jmo.v11i3.32657

Abstract

Kasus covid-19 muncul pertama kali di Wuhan Cina pada akhir tahun 2019 dan menyebar ke seluruh dunia termasuk Indonesia. Wabah ini menyebabkan kekhawatiran baik di kalangan masyarakat, pemerintah, maupun dunia usaha. Respon masyarakat dan pemerintah dalam melakukan upaya-upaya pencegahan yaitu social distancing dan pemberlakuan Pembatasan Sosial Berskala Besar (PSBB) di berbagai daerah di Indonesia menimbulkan roda perputaran ekonomi melambat. Penyebaran wabah covid-19 yang sangat cepat di Indonesia memberikan pengaruh yang besar pada sektor ekonomi khususnya pasar keuangan di Indonesia. Ketidakpastian pasar keuangan yang tinggi tercermin dari volatilitas Indeks Harga Saham Gabungan (IHSG). Penelitian ini bertujuan menganalisis pengaruh covid-19 terhadap pergerakan Indeks Harga Saham Gabungan (IHSG). Pengumpulan data sekunder penelitian diperoleh dari data harian perkembangan jumlah kasus covid-19 dan IHSG periode Maret – Mei 2020. Metode analisis data yang digunakan adalah analisis regresi linier sederhana dan uji hipotesis menggunakan Uji F. Hasil penelitian menunjukkan bahwa jumlah kasus covid-19 di Indonesia pada hari sebelumnya berpengaruh secara signifikan terhadap fluktuasi IHSG hari ini. Kata Kunci: covid-19, IHSG, saham
Peningkatan Kompetensi Peneliti Yayasan Kakikota Banajrmasin Dalam Melakukan Pre-Proccesing Data Hasil Survei, Analisis Data Kategorik, Dan Pembuatan Peta Tematik Yeni Rahkmawati; Selvi Annisa; Dewi Anggraini; Dewi Sri Susanti; Nur Salam; Yuana Sukmawaty; Fuad Muhajirin Farid
Jurnal Pengabdian ILUNG (Inovasi Lahan Basah Unggul) Vol 3, No 1 (2023)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ilung.v3i1.9334

Abstract

Banjarmasin KAKIKOTA Foundation is one of the NGOs based in South Kalimantan that works on urban issues in Banjarmasin City. Banjarmasin KAKIKOTA Foundation has conducted several social stuides on phenomena in Banjarmasin City through several surveys. However, due to the lack of knowledge about data processing, the researchers of the Banjarmasin KAKIKOTA Foundation experienced difficulties in analyzing survey results data. Therefore, Program Studi Statistika, FMIPA, Universitas Lambung Mangkurat (ULM) provides assistance in the form of statistical training to researcher of the Banjarmasin KAKIKOTA Foundation in order to improve the researcher’s competency and technical skills  in analyzing research data. The method used in this community service was training. The training was divided into three subthemes, namely: 1) Data preprocessing, 2) Categorical data analysis, and 3) Thematic map making. Based on the evaluation results, this training was very useful for the researcher of the Banjarmasin KAKIKOTA Foundation and is expected to carry out further training in 2023. Keywords: Statistical Training; NGO; Banjarmasin KAKIKOTA Foundation; Research
Resampling Techniques in Rainfall Classification of Banjarbaru using Decision Tree Method Selvi Annisa; Yeni Rahkmawati
TIERS Information Technology Journal Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i2.5069

Abstract

Continuous heavy rains, such as in 2021, can cause flood emergencies in various areas of Banjarbaru. Therefore, classification modeling is needed to predict rainfall classes based on climate parameters. The problem faced in the classification case is the unbalanced class distribution. Class imbalance occurs when the minority class is much smaller than the majority class. This research aims to compare three resampling techniques in handling imbalanced rainfall data in Banjarbaru using the Decision Tree model. The comparison methods used were sensitivity, specificity, and G-Mean values. In this research, the method used is a decision tree model with Random undersampling, Random Oversampling, and SMOTE. The result shows that the best model is the Decision tree model with the Random Undersampling technique because it provides the highest G-Mean value and sensitivity and specificity values above 70%. Based on this model, the variables that can separate the Rainy and Cloudy classes are Minimum temperature, Maximum temperature, and Sunshine duration, with the best separator being Maximum Temperature.
Clustering Time Series Using Dynamic Time Warping Distance in Provinces in Indonesia Based on Rice Prices Yeni Rahkmawati; Selvi Annisa
TIERS Information Technology Journal Vol. 4 No. 2 (2023)
Publisher : Universitas Pendidikan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38043/tiers.v4i2.5081

Abstract

Rice is a food commodity that is a basic need for Indonesian people. Since the end of 2022, average rice prices in Indonesia have been increasing, breaking the record for the highest price from August to October 2023. The price of rice in each province in Indonesia is different. This can happen because rice center provinces will distribute their rice production to other regions to meet rice needs. The grouping of provinces in Indonesia based on rice prices over time is an interesting thing to research. The analysis method used to group similar objects into groups for time series data is called clustering time series. The distance that can be used to measure the closeness of two-time series is the Dynamic Time Warping (DTW) distance. The clustering analysis used is the single, complete, average, Ward, and median linkage method. The results of the analysis show that time series clustering in provinces in Indonesia based on rice prices is best using median linkage hierarchical clustering. The median linkage method has a cophenetic correlation coefficient value of 0.899064, meaning that clustering using the DTW distance with the median difference is very good. The resulting clusters contained 3 clusters which had different characteristics between the clusters. There are 2 clusters that can be of concern to the government, because there are clusters that have rice prices that have always been high in the last period and there are provincial clusters that have rice prices that are very diverse or can be said to be unstable.
Application of Binary Logistic Regression Analysis on Household Welfare in Banjarmasin City Norhidayati, Annisa; Farid, Fuad Muhajirin; Annisa, Selvi; Hamidy, Anwaril
AL-QARDH Vol 8 No 2 (2023): AL-QARDH
Publisher : Fakultas Ekonomi dan Bisnis Islam Institut Agama Islam Negeri Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Household welfare refers to the conditions in which households can achieve a good standard of living and fulfill their basic needs. CIFOR states that decreasing poverty can be interpreted as increasing prosperity. Based on data on the number of poor people in South Kalimantan in 2022, Banjarmasin City has the highest number of poor people and has not yet met the poverty target contained in the South Kalimantan Regional RPJM for 2021
PREDIKSI INDEKS HARGA KONSUMEN KELOMPOK BAHAN MAKANAN DI PROVINSI KALIMANTAN SELATAN Annisa, Selvi; Azizah, Rahma Dina Nur; Susanti, Dewi Sri
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN (EPSILON: JOURNAL OF PURE AND APPLIED MATHEMATICS) Vol 18, No 1 (2024)
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/epsilon.v18i1.9814

Abstract

Inflation is a phenomenon that shows a continuous increase in the price of goods, which can cause a decline in the economic condition of a country. One of the indicators used to measure the inflation rate is the Consumer Price Index (CPI). By knowing the CPI value earlier, food prices can be controlled to be more stable. One method that can be used to predict CPI is Support Vector Regression (SVR), where this method is able to overcome linear and non-linear data conditions. This research aims to get the best prediction for CPI in South Kalimantan Province using CPI data for food groups in Tanjung, Banjarmasin, and Kotabaru in the 2014-2022 range. The best prediction results are obtained through the SVR method with Linear Kernel. The prediction error value measured through the MAPE value for Tanjung, Banjarmasin and Kotabaru is 0.77%,  and . While the size of the meaning of the model measured through the coefficient of determination, respectively 0.8826,  and . Based on these values, it is concluded that the prediction model formed is very good and feasible. The prediction results for the next 12 months show an increase, so that the government and related parties can formulate policies such as market operations and subsidy programs for the community.
ANALISIS REGRESI COX UNTUK MENENTUKAN FAKTOR-FAKTOR YANG MEMPENGARUHI LAMA STUDI MAHASISWA S1 FMIPA UNIVERSITAS LAMBUNG MANGKURAT Tanjung, Winda Adinda; Anggraini, Dewi; Annisa, Selvi
Jurnal Gaussian Vol 13, No 1 (2024): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.13.1.1-12

Abstract

The length of study is the time it takes a student to complete his education. One of the tertiary institutions that is trying to improve the quality of its student degrees in Indonesia is the Faculty of Mathematics and Natural Sciences, University of Lambung Mangkurat (ULM). This study aims to determine the factors that influence the length of study of ULM FMIPA undergraduate students. The analysis used to determine the effect of these factors is survival analysis through the Cox Proportional Hazard Regression method. The results of this study indicate that the Chemistry Study Program has the greatest chance of being able to complete studies ≤4 years or graduate on time compared to other Study Programs. From the process of the Cox Proportional Hazard Regression method, it was found that the factors that significantly affected the length of study of FMIPA ULM undergraduate students were Gender (Female), GPA (> 3.50) and Status of Residence (Bos/Dormitory/Lodge).
PEMODELAN TINGKAT PENGANGGURAN TERBUKA TERHADAP FAKTOR – FAKTOR YANG MEMPENGARUHINYA DI PULAU KALIMANTAN MENGGUNAKAN REGRESI NONPARAMETRIK SPLINE TRUNCATED Ma’rifa, Aulia; Anggraini, Dewi; Annisa, Selvi
Jurnal Gaussian Vol 13, No 1 (2024): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.13.1.48-58

Abstract

The Open Unemployment Rate is an indicator used to measure the unemployment rate in the labor force. Kalimantan Island is one of the largest islands in Indonesia with a population of around 16.8 million people and is still experiencing problems in overcoming unemployment. Efforts are needed to overcome the problem of unemployment so that it can be resolved and does not have an impact on many things. The purpose of this study was to determine the factors that influence unemployment in Kalimantan using truncated spline nonparametric regression. The nonparametric spline truncated regression analysis approach is used because the pattern of relationship between the open unemployment rate and the factors that are thought to influence it does not form a specific pattern. The results of this study obtained the best model using one knot, with the average length of schooling  and labor force participation rate  variables able to explain the variability of the open unemployment rate in Kalimantan of 56,05 percent.
MACROECONOMICS EFFECT ON CONVENTIONAL AND SHARIA STOCKS DURING THE COVID-19 PANDEMIC Halisa, Novia Nour; Annisa, Selvi
IJIBE (International Journal of Islamic Business Ethics) Vol 7, No 1 (2022): March 2022
Publisher : UNISSULA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/ijibe.7.1.69-84

Abstract

This study aims to analyze the effect of macroeconomics on conventional and sharia stocks during the COVID-19 pandemic. The data collected for this study was obtained from monthly stock index data on the Indonesia Stock Exchange (IDX) as well as macroeconomic development reports from the Ministry of National Development Planning/Bappenas. The population in this study are all conventional and sharia stocks listed on the IDX. The sampling technique was carried out using a purposive sampling method with the criteria of conventional and sharia stocks listed on the IDX for the period March 2020 to June 2021. The macro variables used in researching the Jakarta Composite Index (JCI) and the Jakarta Islamic Index (JII) consisted of four variables, which are exports, imports, inflation rate, and foreign exchange reserves. The data analysis technique used in this research is multivariate multiple linear regression analysis accompanied by simultaneous and partial testing to determine the predictor variables that affect JCI and JII. The results shows that exports and foreign exchange reserves had a significant positive effect on JCI and JII, while imports and the inflation rate did not have a significant effect. The goodness of the model is 93%.
PENERAPAN METODE DOUBLE EXPONENTIAL SMOOTHING BROWN UNTUK MERAMALKAN JUMLAH KEMATIAN HIV/AIDS DI INDONESIA Anggraini, Dewi; Suwindi, Akhmad; Azhar, Muhammad; Ma’rifah, Nurul; Khairani, Diva Ghefira Mahardika; Annisa, Selvi
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 7 No. 01 (2025)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm299

Abstract

Penelitian ini bertujuan untuk memprediksi jumlah kematian akibat HIV/AIDS di Indonesia menggunakan metode Double Exponential Smoothing Brown. Data yang digunakan merupakan data sekunder dari situs Vizhub, yang mencatat kematian tahunan akibat HIV di Indonesia dari tahun 1990 hingga 2021. Metode pemulusan eksponensial ganda dipilih karena adanya tren peningkatan jumlah kematian dari tahun ke tahun. Nilai parameter α terbaik ditentukan melalui metode trial and error untuk meminimalkan tingkat kesalahan peramalan. Hasil analisis menunjukkan bahwa model Double Exponential Smoothing Brown dengan nilai α=0.9 memberikan peramalan yang akurat. Berdasarkan model ini, diproyeksikan bahwa jumlah kematian akibat HIV di Indonesia akan terus meningkat hingga tahun 2030. Hasil penelitian ini diharapkan dapat menjadi dasar bagi pembuat kebijakan untuk mengambil langkah-langkah pencegahan yang lebih efektif.
Co-Authors Adzim, Muhammad Fauzan Anwaril Hamidy Azizah, Rahma Dina Nur Dewi Anggraini Dewi Anggraini Dewi Sri Susanti Fuad Muhajirin Farid Genardi, Angelina Ivanna Halisa, Novia Nour Hamda, Tazkiratul Hardianti Hafid Irawan, Siti Fatimah Marliany Khairani, Diva Ghefira Mahardika Ma’rifa, Aulia Ma’rifah, Nurul Muhammad Azhar Norhidayati, Annisa Novia Nour Halisa Nur Salam Oktaviani, Viona Perdana, Muhammad Akmal Sembiring, Rinawati Suwindi, Akhmad Tanjung, Winda Adinda Utami, Radias Kartika Yeni Rahkmawati Yuana Sukmawaty