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All Journal Jurnal Matematika Health Science Journal of Indonesia CELEBES Agricultural Inisiatif: Jurnal Ekonomi, Akuntansi Dan Manajemen Jurnal Statistika Industri dan Komputasi
Yudi Setyawan
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Agriculture, Biological Sciences & Forestry Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Health Professions Mathematics Nursing Public Health

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Priority setting in responding crisis: a hospital leaders’ perspective at the early stage of COVID-19 pandemic Aryo Dewanto; Yudi Setyawan; Viera Wardhani
Health Science Journal of Indonesia Vol 12 No 2 (2021)
Publisher : Sekretariat Badan Penelitian dan Pengembangan Kesehatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22435/hsji.v12i2.5295

Abstract

Background: The COVID-19 pandemic hit Indonesia when hospitals were striving to adjust to a changing environment after a new health insurance system implementation, a government’s effort to achieve Universal Health Coverage. As a result, the pandemic forced hospitals to exploit their resources. Due to limited resources, setting accurate priorities is highly important to secure hospital operations and maintain its track towards the expected goals. This study aims to explore how deep the crisis impacts hospitals and how hospital leaders in Indonesia set their priorities in responding to the impact of this pandemic. Methods: This study used a descriptive and analytical approach. Data were collected through an online survey from hospital leaders and several documentary sources. Results: The results show that almost all hospital directors consider patient visits and hospital finance the most significant impacts of the COVID-19 pandemic. However, government hospital directors emphasize different areas compared to non-government hospital directors; the former sets their priorities on the hospital’s human resources, quality of service, and operations, while the latter focuses on the impact of patient visits and hospital finance. Conclusion: Although directors of government and non-governmental hospitals have a different emphasis, their priority is the same, maintaining hospital sustainability to provide quality services to people. Keywords: COVID-19 pandemic, hospital leaders’ perspective, impacts, Indonesia, priority setting Abstrak Latar belakang: Pandemi COVID-19 melanda Indonesia ketika rumah sakit berusaha menyesuaikan diri dengan lingkungan yang berubah setelah penerapan sistem jaminan kesehatan baru sebagai upaya pemerintah untuk mencapai Universal Health Coverage. Akibatnya, pandemi memaksa rumah sakit untuk mengeksploitasi sumber daya mereka. Sumber daya yang terbatas membuat penetapan prioritas yang akurat menjadi sangat penting untuk menjamin keberlangsungan operasional rumah sakit dan memastikan rumah sakit bergerak menuju tujuan yang diharapkan. Penelitian ini bertujuan untuk mengeksplorasi seberapa dalam dampak krisis ini terhadap rumah sakit dan bagaimana pemimpin rumah sakit di Indonesia menetapkan prioritasnya dalam merespon dampak pandemi ini. Metode: Penelitian ini menggunakan pendekatan deskriptif dan analitik. Data dikumpulkan melalui survei online dari pimpinan rumah sakit dan beberapa sumber dokumenter. Hasil: Hasil penelitian menunjukkan bahwa hampir semua direktur rumah sakit menganggap kunjungan pasien dan pembiayaan rumah sakit mendapat dampak paling signifikan dari pandemi COVID-19. Namun, direktur rumah sakit pemerintah menekankan bidang yang berbeda dibandingkan dengan direktur rumah sakit non-pemerintah. Direktur rumah sakit pemerintah menetapkan prioritas mereka pada sumber daya manusia rumah sakit, kualitas layanan, dan operasi, sedangkan direktur rumah sakit non-pemerintah fokus pada dampak kunjungan pasien dan keuangan rumah sakit. Kesimpulan: Meskipun direktur rumah sakit pemerintah dan non-pemerintah memiliki penekanan yang berbeda, tetapi prioritas mereka sama yaitu menjaga keberlanjutan rumah sakit untuk memberikan pelayanan yang berkualitas kepada masyarakat. Kata kunci: pandemi COVID-19, perspektif pemimpin rumah sakit, dampak, Indonesia, penetapan prioritas.
Perbandingan ELM dan Double Exponential Smoothing Untuk Meramalkan PDRB Di Provinsi NTT Laura Liokelly Toron; Yudi Setyawan; Noviana Pratiwi
Jurnal Matematika Vol 12 No 1 (2022)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2022.v12.i01.p147

Abstract

Abstract: Gross Regional Domestic Product is the total number of goods and services produced by production units of all economic sectors of a particular region during one year. BPS NTT noted that the economic growth rate of NTT in 2020 experienced a contraction of -0.83% from 5.24% in the previous year, so this study aims to predict NTT's GRDP using the ELM method and Holt's Double Exponential Smoothing. ELM is an artificial neural network that has one hidden layer that is applied through training and testing process, then involves a binary sigmoid activation function and a Moore Penrose Pseudo Inverse matrix to get the output weight used to predict. DES Holt is a forecasting method that pays attention to trend data plots and uses two parameters in its calculations. The results of the forecasting research show that the ELM method with a proportion of 80%:20% is the best method for predicting the GRDP of NTT. The ELM method produces quarterly GRDP values in 2021, which are 17493.19754, 18154.80753, 18712.02153, and 18822.97416 (billion rupiah) with 4 input neurons, 12 hidden layer neurons, 1 output neuron and the MAPE value is 0.7968% which is smaller than DES Holt.
Analisis Positioning Merk Laptop dengan Menggunakan Metode MDS Nonmetrik dan CA Maria Romaana Ona Sain; Yudi Setyawan; Rokhana Dwi Bekti
Jurnal Matematika Vol 12 No 2 (2022)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2022.v12.i02.p152

Abstract

Abstract: This study aims to determine the positioning of laptop brands on attributes based on the perceptions and preferences of IST AKPRIND students. The method used is nonmetric multidimensional scaling and correspondence analysis. The results showed that: multidimensional scaling of perception data, quadrant I was occupied by HP and Dell, quadrant II was occupied by Toshiba, quadrant III was occupied by Acer, Lenovo, Asus, and quadrant IV was occupied by Apple. Then multidimensional scaling preference data, it is known that quadrant I is occupied by storage and price attributes, quadrant II is occupied by Apple with attributes of laptop resistance to damage, feature set, RAM, processor, quadrant III is occupied by brand image and warranty attributes, and quadrant IV is occupied by HP, Dell, Toshiba, Acer, Lenovo, Asus, and there are no attributes in quadrant IV. Using correspondence analysis, it is known that quadrant I is occupied by Apple with price attributes, quadrant II is occupied by Toshiba with attributes of brand image, processor, RAM, feature set, quadrant III is occupied by HP, Dell, Lenovo, Acer, Asus with attributes of laptop resistance to damage, quadrant IV is occupied storage and warranty attributes. There is no laptop in quadrant IV.
ESTIMASI PARAMETER MODEL REGRESI LOGISTIK BINER MENGGUNAKAN METODE JACKKNIFE Rizal Ariefaidzin Asikin; Yudi Setyawan
Jurnal Statistika Industri dan Komputasi Vol. 4 No. 01 (2019)
Publisher : Program Studi Statistika, Fakultas Sains dan Teknologi Informasi, Universitas AKPRIND Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34151/statistika.v4i01.1053

Abstract

Logistic regression is one of the statistical methods used to identify a causal relationship (causality) between one dependent variable and one or more independent variables, where the dependent variable has 2 or more categories. To find a good logistic regression model, sufficient amount of data is needed, if the amount of data is insufficient, the modeling can be done using the resampling method, namely using Bootstrap or Jackknife. The working principle of the Jackknife method use computers in generating data from the original samples to generate artificial samples. An artificial sample is generated by removing an observation from the original sample which can then be used to calculate estimator value. In this case, the Jackknife Method is used to resampling the data of beras miskin admission in Yogyakarta. Based on the results of the analysis, Jackknife method can minimize the standard error in calculating the estimation of parameters until Jackknife Method erases two datas. Based on data obtained from SUSENAS (Sensus Sosial Ekonomi Nasional) of Yogyakarta in 2016, there are 641 households being sample. The dependent variable which is used was the admission of beras miskin. Beras miskin consists of two categories. That is receiving beras miskin and not-receiving beras miskin. From the number of households affected by sample, it shows that the number of households receiving beras miskin is 15% (98 households) and the number of households which isn’t receiving beras miskin is 85% (543 households). The significant variables after logistic regression test were the main floor of house (X2) and the source of drinking water (X4). Those variables affect admission of beras miskin with the odds ratio =0,2476 and =0,1999 . The best logistic regression model for case studies discussed in the previous chapter is a logistic regression model with the two datas erased by jackknife method, in which the probability model of a household receiving raskin is: P(Y = 1|X) = π (x) = With the level of accuracy of the model in predicting at 84.2%
Analisis Pengaruh Kepercayaan, Kualitas Pelayanan, Dan Promosi Terhadap Kepuasan Pelanggan (Studi Pada Bengkel Mobil Sinar Audio Semarang) Citra Rizkiana; Yudi Setyawan; Johanis Souisa
Inisiatif: Jurnal Ekonomi, Akuntansi dan Manajemen Vol. 2 No. 2 (2023): April : Inisiatif: Jurnal Ekonomi, Akuntansi dan Manajemen
Publisher : Universitas 45 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30640/inisiatif.v2i2.810

Abstract

Perkembangan industri otomotif yang semakin meningkat terlebih pada kendaraan roda empat atau lebih membuat layanan purna jual semakin banyak dan harus memenuhi kepuasan dari pelanggan. Penelitian ini bertujuan untuk menganalisis pengaruh kepercayaan, kualitas pelayanan dan promosi terhadap kepuasan pelanggan (Studi Pada Bengkel Mobil Sinar Audio Semarang). Populasi yang digunakan dalam penelitian ini adalah seluruh pelanggan Bengkel Mobil Sinar Audio Semarang yang tidak diketahui jumlahnya. Sedangkan untuk sampelnya sendiri berjumlah 96 orang dengan menggunakan metode purposive sampling (sampel dengan kriteria). Metode analisis data yang digunakan dalam penelitian ini menggunakan analisis regresi linier berganda. Hasil penelitian ini membuktikan bahwa variabel kepercayaan tidak berpengaruh terhadap kepuasan pelanggan, variabel kualitas pelayanan mempunyai pengaruh positif dan signifikan terhadap kepuasan pelanggan, variabel promosi mempunyai pengaruh positif dan signifikan terhadap kepuasan pelanggan (studi pada pelanggan Bengkel Mobil Sinar Audio Semarang).
Development of Spatial Platform Based Earth Engine Apps for Mangrove Carbon Stock: Case Study in Serang Coastal Zone, Banten Province Puspitasari, Raditya Febri; Aisyah; Usnil Khotimah; Mahadika Rifka Nugraha; Ali Dzulfigar; Khairani Putri Marfi; Danik Septianingrum; Rahmat Asy'ari; Rahmat Pramulya; Neviati Putri Zamani; Yudi Setyawan
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.746

Abstract

Mangroves exhibited considerable potential in mitigating global climate change, as these ecosystems can sequester and store substantial amounts of carbon in the form of live and decayed plant biomass across coastal areas. This research aimed to estimate carbon stocks and assess the dynamics of carbon reserves in the silvofishery area of Serang City, Banten, utilizing geospatial technology and cloud computing. Additionally, the study sought to develop the Indo InaC Data platform to monitor CO2 uptake on silvofishery land. The methodology employed included mangrove detection through unguided classification, and carbon stock estimation was performed using regression models derived from vegetation indices, specifically the Integrated Remote Sensing and Ecological Index (IRECI) and the Transformed Vegetation Index (TRVI). The results revealed fluctuations in mangrove vegetation cover between 2016 and 2023, with a notable decrease occurring from 2016 to 2017, as the cover declined from approximately 61.91 hectares to 50.53 hectares. This decrease was followed by an increase from 2017 to 2022, during which the area rose to 78.1 hectares; however, a subsequent decrease was observed in 2023, with the area reducing to 66.82 hectares. The estimated carbon reserves in the study area for 2023 amounted to 315 tons, reflecting similar dynamics to those observed in mangrove vegetation cover. The development of the Indo InaC Data platform is anticipated to facilitate ongoing monitoring of CO2 emissions uptake, and it is expected to inform future strategies for managing silvofishery land on an annual basis.
Co-Authors Aisyah Ali Dzulfigar Aryo Dewanto Citra Rizkiana Danik Septianingrum Johanis Souisa Khairani Putri Marfi Laura Liokelly Toron Mahadika Rifka Nugraha Maria Romaana Ona Sain Neviati Putri Zamani Noviana Pratiwi Pramulya, Rahmat Puspitasari, Raditya Febri Rahmat Asy'ari Rizal Ariefaidzin Asikin Rokhana Dwi Bekti Usnil Khotimah Viera Wardhani