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Analisis Diskriminan dalam Menentukan Fungsi Pengelompokan Kabupaten/Kota di Indonesia berdasarkan Indikator Indeks Pembangunan Manusia Nurhasanah, Nurhasanah; Salwa, Nany; Ornila, Lyra; AR, Fitriana; Hasan, Amiruddin
Jurnal EMT KITA Vol 5, No 1 (2021): Journal EMT KITA
Publisher : Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/emt.v5i1.320

Abstract

The Human Development Index (HDI) is a measure used to measure the success of human development in an area. There are several indicators used to compile the HDI value. Previously, regencies/cities were grouped based on the HDI indicator. The grouping is done using K-means cluster analysis with 4 categories, namely regencies/cities that have low, medium, high, and very high HDI indicator values. From the results of determining the category of the HDI indicator in an area, we need a function that can be used to classify an object into one of the HDI indicator value categories. The compilation of the classification function is carried out using discriminant analysis. The results obtained from the discriminant analysis are that there are 10 variables or indicators that fall into the discriminant function. The resulting discriminant function is quite good in classifying each group with a success rate of more than 85% and the discriminant function is supported by a fairly good validation success rate, namely with a classification accuracy of 93.20%.
Analisis Biplot untuk Mengetahui Kebutuhan terhadap Lulusan Program Studi Statistika Fitriana AR; Asep Rusyana
Jurnal Matematika, Statistika dan Komputasi Vol. 8 No. 1: July 2011
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (327.191 KB) | DOI: 10.20956/jmsk.v8i1.3384

Abstract

Untuk melahirkan lulusan statistika yang berkualitas dibutuhkan program studi statistika yang dapat di andalkan. Dengan menyebar kuesioner pada pengguna lulusan program studi statistika, telah dikumpulkan data terkait kebutuhan instansi terhadap lulusan menggunakan teknik purposive sampling. Instansi pengguna lulusan adalah 22 dinas yang ada di Banda Aceh. Metode Biplot digunakan untuk menentukan tingkat kebutuhan instansi pengguna lulusan statistika. Sebagian besar instansi, yaitu sebanyak 9 dari 22 instansi meyakini bahwa sarjana statistika akan menyelesaikan banyak pekerjaan pada instansi tersebut, sekaligus menganggap bahwa penganggaran dana untuk pengembangan lulusan statistika sangat perlu untuk dilakukan.
Analisis Faktor-Faktor Yang Memengaruhi Keluhan Kesehatan Di Indonesia Menggunakan Metode Regresi Data Panel Rahmayuni, Titin; AR, Fitriana; Salwa, Nany; Nurhasanah, Nurhasanah
Transcendent Journal of Mathematics and Applications Vol 3, No 2 (2024)
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/tjoma.v3i2.43045

Abstract

Health complaints are one aspect of the problem that is the focus of attention in Indonesia. Over the past 3 years, the percentage of health complaints in Indonesia has increased. One of the ways that can be done to reduce the problem of health complaints is to find out the factors that influence it. This study aims to find a suitable model to determine the factors that influence health complaints in Indonesia. To find out the factors that influence health complaints in Indonesia, this study uses a panel data regression analysis method with 3 basic models, namely the Common Effect Model (CEM), Fixed Effect Model (FEM), Random Effect Model (REM). The data in this study consists of cross section data in the form of 34 provinces in Indonesia and time series data in the form of data from 2020 to 2022 with 1 dependent variable and 9 independent variables. The results showed that the selected model of health complaints in Indonesia was the Random Effect Model with individual effects. This model produces an R2 value of 58.19% and an adjusted R2 value of 54.09%. This study obtained 3 significant variables, namely the sick population who did not seek treatment, the population who self-medicated, and the birth process that was not assisted by health workers. Meanwhile, the variables that have a positive effect are the sick population that does not seek treatment, women with marital status using family planning, and population who smoke.
Analysis of Academic Characteristics of USK FMIPA Undergraduate Students Using the Chaid Method AR, Fitriana
Transcendent Journal of Mathematics and Applications Vol 2, No 2 (2023)
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/tjoma.v3i1.36550

Abstract

The purpose of this research is to find out the most significant factors to the students study period, to divide the data into smaller groups based on the relationship between the response variables ande the explanatory variables. The characteristics and educational background are gender, school origin, major, supervisors level of education, Grade Point Average (GPA), and trial grades. The method displays a graphical tree structure in the form of a diagram that explains the relationship between categorical response variables and categorical explanatory variables so that it is easy to interpret. The test used to produce a tree diagram is the Chi-square test and Bonferroni correction. In this study, data were used on graduates of the faculty of Mathematics and Natural Sciences USK class of 2017 who graduated from september 2020 to August 2022. The result of the study showed that the most significant factors for the period of study were GPA, school origin, supervisor education,level, type gender, and major. In terms of classification accuracy, the percentage accuracy of the model correctly classifying the study period is 71,8%.
An Analysis of Internal Factors Affecting the Study Continuation Interest of High School Students in Banda Aceh Toward Universitas Syiah Kuala Nurhasanah, Nurhasanah; Pranata, Aditya; AR, Fitriana; Mulyani, Riska
Transcendent Journal of Mathematics and Applications Vol 4, No 1 (2025)
Publisher : Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/tjoma.v4i1.44757

Abstract

Interest is a psychological tendency that drives individuals to choose certain objects or activities based on their needs, later manifested through attention and active engagement. In high school students (SMA), interest in pursuing higher education typically begins to form in the 11th grade as awareness of future planning increases. However, a phenomenon observed in several high schools in Aceh, particularly in Banda Aceh, shows that many high-achieving students prefer to continue their studies outside the province, despite the presence of a well-accredited university Universitas Syiah Kuala (USK) which offers 67 study programs across 12 faculties and serves around 30,000 students. This study aims to verify this trend using a quantitative survey approach conducted among public high school students in Banda Aceh. The main focus is to identify the best model representing student interest data and to reveal factors influencing their decision to choose USK. Using logistic regression due to the binary categorical nature of the dependent variable (interested vs. not interested), the study found that at a 10% significance level, three variables significantly influence students interest: affiliation ability (X), goal orientation (X), and hope for the future (X). Among these, goal orientation (X) had the strongest influence, with an odds ratio of 1.712. This indicates that the stronger a students academic or career goals, the higher their tendency to choose Universitas Syiah Kuala for further education.
Peramalan Tonase Sampah TPST Bantargebang Sebagai Upaya Awal Penanganan Masalah Sampah Daerah Khusus Jakarta Zedha, Hazulil Fitriah; Anwar, Samsul; AR, Fitriana
Jurnal Kesehatan Lingkungan Indonesia Vol 24, No 3 (2025): Oktober 2025
Publisher : Master Program of Environmental Health, Faculty of Public Health, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jkli.67624

Abstract

Latar belakang: Salah satu masalah lingkungan yang timbul akibat semakin bertambahnya jumlah penduduk yang disertai dengan perubahan pola hidup di Daerah Khusus Jakarta (DKJ) adalah pengelolaan sampah yang semakin kompleks dengan kuantitas yang mencapai 7.000 ton/harinya. Penelitian ini bertujuan untuk meramalkan tonase sampah yang mungkin dihasilkan pada masa yang akan datang sebagai salah satu upaya awal dalam membantu proses penyusunan rencana pengelolaan sampah yang lebih baik.Metode: Penelitian ini menganalisis data tonase sampah bulanan yang masuk ke TPST Bantargebang yang diperoleh dari website Jakarta Open Data. Data dianalisis dengan menggunakan statistika deskriptif dan inferensia dengan menggunakan metode Triple Exponential Smoothing (TES) dan Autoregressive Fractionally Integrated Moving Average (ARFIMA).Hasil: Peramalan dengan metode terbaik menunjukkan bahwa tonase sampah yang masuk ke TPST Batargebang diprediksi akan semakin tinggi setiap tahunnya terutama pada bulan Desember dan Januari. Tonase sampah pada bulan Desember tahun 2026 diprediksi mencapai 293.317,5 ton, jauh meningkat dari hasil prediksi pada bulan Desember tahun 2021 yang hanya mencapai 254.113,3 ton. Simpulan: Hasil peramalan tonase sampah pada penelitian ini dapat menjadi salah satu acuan dalam upaya penanganan sampah di DKJ. Pemerintah DKJ bersama seluruh komponen masyarakat perlu bekerjasama dalam mengantisipasi lonjakan sampah tersebut dengan melakukan berbagai upaya yang dapat menekan laju peningkatan tonase sampah di Jakarta dan sekitarnya. Pemerintah DKJ direkomendasikan untuk memperbaiki sistem pengelolaan sampah, baik di tingkat masyarakat maupun di TPST Batargebang dengan mengeluarkan regulasi/aturan pengelolaan sampah yang lebih efektif, menambah anggaran pengelolaan sampah dan melakukan sosialisasi serta pembinaan terutama bagi masyarakat yang tinggal di wilayah padat penduduk. ABSTRACT Forecasting Waste Tonnage at TPST Bantargebang as an Initial Effort to Handle Waste Problems in Special Region of JakartaBackground: One of the environmental problems arising from the increasing population accompanied by changes in lifestyle in the Special Region of Jakarta (DKJ) is increasingly complex waste management with quantities reaching 7,000 tons per day. This study aims to forecast the tonnage of waste that may be generated in the future as one of the initial efforts in helping the process of preparing a better waste management plan .Method: This study analyzes monthly waste tonnage data entering TPST Bantargebang obtained from the Jakarta Open Data website. The data was analyzed using descriptive and inferential statistics using the Triple Exponential Smoothing (TES) and Autoregressive Fractionally Integrated Moving Average (ARFIMA) methods..Result: Forecasting with the best method shows that the tonnage of waste entering TPST Batargebang is predicted to be higher every year, especially in December and January. The waste tonnage in December 2026 is predicted to reach 293,317.5 tons, a far increase from the prediction results in December 2021 which only reached 254,113.3 tons. Conclusion: The results of forecasting the tonnage of waste in this study can be one of the references in waste management efforts in DKJ. The DKJ government together with all components of society need to work together in anticipating the surge in waste by making various efforts that can reduce the rate of increase in waste tonnage in Jakarta and its surroundings. The DKJ government is recommended to improve the waste management system, both at the community level and at TPST Batargebang by issuing more effective waste management regulations, increasing the waste management budget and conducting socialization and guidance, especially for people living in densely populated areas. ABSTRACT Forecasting Waste Tonnage at TPST Bantargebang as an Initial Effort to Handle Waste Problems in Special Region of JakartaBackground: One of the environmental problems arising from the increasing population accompanied by changes in lifestyle in the Special Region of Jakarta (DKJ) is increasingly complex waste management with quantities reaching 6,500 to 7,000 tons per day. This study aims to forecast the tonnage of waste that may be generated in the future as one of the initial efforts in helping the process of preparing a better waste management plan .Method: This study analyzes monthly waste tonnage data entering TPST Bantargebang obtained from the Jakarta Open Data website. The data was analyzed using descriptive and inferential statistics using the Triple Exponential Smoothing (TES) and Autoregressive Fractionally Integrated Moving Average (ARFIMA) methods..Result: Forecasting with the best method shows that the tonnage of waste entering TPST Batargebang is predicted to be higher every year, especially in December and January. The waste tonnage in December 2026 is predicted to reach 293,317.5 tons, a far increase from the prediction results in the same month for 2021 which only reached 254,113.3 tons. Conclusion: The results of forecasting the tonnage of waste entering the TPST Batargebang in this study can be one of the references in waste management efforts in DKJ. The DKJ government together with all components of society need to work together in anticipating the surge in waste by making various efforts that can reduce the rate of increase in waste tonnage in Jakarta and its surroundings. The DKJ government is recommended to improve the waste management system, both at the community level and at TPST Batargebang by issuing more effective waste management regulations, increasing the waste management budget and conducting socialization and guidance, especially for people living in densely populated areas.