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PENGUATAN KAPASITAS PEREMPUAN MELALUI KEWIRAUSAAN ECOPRINT Setiawan Setiawan; Djoko Kuswanto; Muhammaf Sjahid Akbar; Dedy D. Prastyo; Santi Puteri Rahayu; Neni Alya Firdausanti; Ahmad Saikhu
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 6, No 4 (2022): Desember
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v6i4.11871

Abstract

ABSTRAKAdanya kewajiban dosen (Perguruan Tinggi) untuk pengabdian kepada masyarakat, KKN mahasiswa  , serta Program pemerintah kota  Surabaya untuk pengentasan Masyarakat Berpenghasilan Rendah (MBR), merupakan tantangan bagi Perguruan Tinggi untuk berpartisiasi.  Di sisi lain, salah satu kerajinan yang sedang booming adalah ecoprint.  Beberapa alasannya adalah : (i) proses produksi tidak terlalu sulit, tidak sesulit membatik, serta (ii) di wilayah Kelurahan Keputih kaya akan tanaman yang daunnya dapat digunakan untuk produksi ecoprint. Tim Pengabdian Masyarakat  ITS menggandeng UMKM Sinawa Ecoprint dan Any’s Art & Craft untuk memberdayakan ibu-ibu rumah tangga (pemberdayaan Wanita) warga Kelurahan Keputih, khususnya Masyarakat Berpenghasilan Rendah.  Kegiatan ini meliputi pelatihan produksi ecoprint, dilanjutkan  dengan mengadopsi konsep sistem intiplasma, UMKM Sinawa Ecoprint dan Any’s Art & Craft sebagai inti yang akan menyediakan sarana produksi, menampung dan memasarkan hasil kerajinan ecoprint  ibu-ibu rumah tangga warga Keputih, secara berkelanjutan. Setelah  ibu-ibu rumah tangga terampil menghasilkan  ecoprint, mereka  dapat mejual hasil ecoprint,  sehingga mendapatkan  tambahan penghasilan bagi keluarga. Selain itu, dampak kegiatan ini diharapkan turut serta berperan dalam upaya PEMKOT Surabaya untuk pengentasan kemiskinan melalui pemberdayaan wanita. Kata Kunci : pemberdayaan wanita; ecoprint; inti-plasma; berkelanjutan; MBR ABSTRACTThe existence of the obligation of lecturers (Universities) for community service, student community service activities (KKN), and the Surabaya city government program for alleviating Low-Income Communities (MBR), is a challenge for universities to participate. On the other hand, one of the booming crafts is ecoprint. Some of the reasons are: (i) the production process is not too difficult, not as difficult as batik, and (ii) the Keputih Village area is rich in plants whose leaves can be used for ecoprint production. The ITS Community Service Team collaborates with the Sinawa Ecoprint and Any's Art & Craft SMEs to empower housewives (Women Empowerment) residents of Keputih Village, especially Low-Income Community. This activity includes training on ecoprint production, followed by adopting the concept of the nucleus plasma system, the MSME Sinawa Ecoprint and Any's Art & Craft as the core which will provide production facilities, accommodate and market the ecoprint handicrafts of Keputih housewives, in a sustainable manner. After skilled housewives produce ecoprints, they can sell the ecoprints, thereby earning additional income for the family. In addition, the impact of this activity is expected to play a role in the Surabaya City Government's efforts to alleviate poverty through empowering women. Keywords: women empowerment; ecoprints; nucleus-plasma system; sustainable; low-income community
Pengelompokan Pertumbuhan Ekonomi (PDRB) dan Pengeluaran di Jawa Timur Berdasarkan Jumlah UMK serta Faktor-faktor yang Mempengaruhi dengan Model Persamaan Simultan Santi Puteri Rahayu; Irene Monica Amanda
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 15 No 2 (2022): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Fakultas Sains dan Teknologi Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36456/jstat.vol15.no2.a5802

Abstract

Pertumbuhan ekonomi Produk Domestik Regional Bruto (PDRB) diidentikkan sebagai ukuran kesejahteraan masyarakat. Usaha mikro kecil (UMK) di Indonesia dapat menjadi pendukung dalam pertumbuhan ekonomi karena UMK memiliki karakteristik positif sebagai sektor yang mampu menyediakan lapangan pekerjaan yang besar. Pengeluaran juga dapat mempengaruhi PDRB, karena dapat menunjukkan kesejahteraan masyarakat dalam memenuhi kebutuhan hidupnya. Jawa Timur sebagai salah satu provinsi Indonesia yang memiliki perekonomian yang baik, karena memiliki PDRB terbesar kedua setelah DKI Jakarta dan memiliki UMK yang menjadi pendukung pertumbuhan ekonomi. Adanya hubungan simultan antara PDRB dan pengeluaran yang over identified dapat dimodelkan menggunakan metode persamaan simultan 2SLS dan 3SLS. Hasil menunjukkan bahwa estimasi model persamaan simultan lebih baik daripada model persamaan tunggal, berdasarkan kriteria koefisien determinasi maksimum dan kesamaan nilai estimasi. Lebih dari itu, estimasi model persamaan simultan 3SLS ditunjukkan ecara empiris bersifat lebih baik dibandingkan model 2SLS, dengan kriteria koefisien determinasi maksimum dan standard error minimum. Hasil estimasi model 3SLS menunjukkan bahwa jumlah UMK dan pengeluaran berpengaruh positif terhadap PDRB, tetapi rasio ketergantungan berpengaruh negatif terhadap PDRB. Sementara itu, IPM dan PDRB berpengaruh positif terhadap pengeluaran, tetapi pengangguran berpengaruh negatif terhadap pengeluaran. Hasil konfirmasi pengelompokan estimasi sepuluh daerah PDRB terendah dengan data aktual hanya meliputi empat kabupaten/kota, sedangkan estimasi pengeluaran terdiri dari tiga kabupaten/kota.
Modeling Multi-Output Back-Propagation DNN for Forecasting Indonesian Export-Import Maharsi, Rengganis Woro; Saputra, Wisnowan Hendy; Roosyidah, Nila Ayu Nur; Prastyo, Dedy Dwi; Rahayu, Santi Puteri
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 16 No 1 (2024): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v16i1.459

Abstract

Introduction/Main Objectives: International trade through the mechanisms of exports and imports plays a significant role in the Indonesian economy, making the timely availability of export and import value data crucial. Background Problems: Export and import values are influenced by inflation and exchange rate factors. Novelty: This study identifies two categories of variables, namely output (export value and import value) and input (inflation rate and the exchange rate of the Rupiah against the US Dollar). Research Methods: the research approach utilizes a Multi-output Deep Neural Network (DNN) with a Back-propagation algorithm to model the input-output relationship. The method can provide forecasting results for two or more bivariate or multivariate output variables. Finding/Results: The modeling analysis results indicate that the optimal model network structure is DNN (3.4). This model successfully predicts output 1 (export value) and output 2 (import value) with Mean Absolute Percentage Error (MAPE) rates of 13.76% and 13.63%, respectively. Additionally, the forecasting results show predicted export and import values for November to be US$ 16,208.13 billion and US$ 15,105.33 billion, respectively. These findings offer important insights into the direction of Indonesia's international trade movement, which can serve as a basis for future economic decision-making.
ESTIMASI PARAMETER MODEL PROBIT PADA DATA PANEL MENGGUNAKAN OPTIMASI BFGS Halistin, Halistin; Ratnasari, Vita; Rahayu, Santi Puteri; Patih, Tandri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 2 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (885.055 KB) | DOI: 10.30598/barekengvol14iss2pp167-174

Abstract

One model that may explain the pattern of the relationship between the categorical dependent variable and the independent variables is probit regression. In the probit regression, the independent variable can be categorical or continuous. Probit regression is using the link function of the standard normal distribution. If the probit regression modeling involves a cross-section data and time series data, it is called probit data panel model. Parameter estimation of random effect probit data panel model is using the maximum likelihood estimation (MLE) method with Gauss Hermite Quadrature approach. Iterative procedure by using BFGS method. BFGS method used to obtain the close form value of the parameter estimates.
Application of Zero Inflated Ordered Logit (ZIOL) (Case Study: The Employment Status Of The Working-Age Population In Banten Province) Marshiela, Jessie Reyna; Ratnasari, Vita; Rahayu, Santi Puteri
Jurnal Ilmiah Global Education Vol. 6 No. 2 (2025): JURNAL ILMIAH GLOBAL EDUCATION, Volume 6 Nomor 2
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/jige.v6i2.3675

Abstract

Unemployment remains a major economic issue in Indonesia, particularly in Banten Province, which has the highest open unemployment rate. Traditional models struggle to capture the zero inflation characteristics in labor force data, where most individuals are employed. This study applies the Zero-Inflated Ordered Logit (ZIOL) model to better analyze labor force status in Banten by distinguishing between genuinely unemployed individuals and those appearing unemployed due to external factors.Using data from the National Labor Force Survey (SAKERNAS) 2023, this study examines the impact of gender, education, residence, job training access, and work experience on employment. The results show that women, individuals with lower education, and those lacking work experience are more likely to be unemployed or underemployed. ZIOL outperforms traditional ordinal logit models in capturing these dynamics.The findings provide insights for policymakers to design more effective employment strategies, particularly in regions facing high unemployment.
Multivariate Time Series Forecasting using Hybrid Vector Autoregressive and Neural Network for Coupled Roll-Sway-Yaw Motions Prediction Suhermi, Novri; Suhartono, -; Rahayu, Santi Puteri; Ali, Baharuddin; Dahlila, Dea; Aisy, Rahida Rihhadatul
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3077

Abstract

There are six types of motion referred to as the six degrees of freedom, which define the motion of a ship. For a ship to remain stable, it must be in a symmetrical position. Therefore, a ship's stability can be determined based on its motion. Ship motions can be analyzed either in an uncoupled system or a coupled system. One of the coupled motion systems that is often studied is the roll-sway-yaw motion. In this study, we apply the Hybrid Vector Autoregressive–Neural Network (VAR-NN) model to build a multivariate time series model for predicting the roll-sway-yaw motions of a prototype ship. The Hybrid VAR-NN is a data analysis technique that integrates the linear capabilities of the VAR model with the nonlinear capabilities of the NN model to capture both linear and nonlinear trends simultaneously. The dataset for this study was generated from waves in a prototype ship experiment and divided into in-sample and out-of-sample data. The model was trained using the in-sample data, and predictions were made on the out-of-sample data using the trained model. The forecast results of the VAR-NN model were compared with those from the pure VAR and pure NN models. Model selection was based on out-of-sample performance criteria, with the Root Mean Square Error (RMSE) employed as the prediction performance metric. According to the experimental results, the Hybrid VAR-NN model outperformed the other models, demonstrating its ability to improve the prediction performance of the pure models through its hybrid approach.
The Theoretical Study of Rare Event Weighted Logistic Regression for Classification of Imbalanced Data Sulasih, Dian Eka Apriana; Purnami, Santi Wulan; Rahayu, Santi Puteri
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2015: Proceeding ISETH (International Conference on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.2376

Abstract

One of the problems in data classification is imbalanced data. In two-class classification, imbalance problem occurs where one of the two classes has more samples than another class. In such situation, most of the classifier will be biased towards the major class, while the minor class will be subordinated eventually which leads to inaccurate classification. Therefore, a method to classify the imbalanced data is required. Rare Event Weighted Logistic Regression (RE-WLR) which is developed by Maalouf and Siddiqi is a method of classification applied to large imbalanced data and rare event. This study showed the review of RE-WLR for the classification of imbalanced data. It explicated the steps to obtain the estimator specifically, particularly for IRLS. RE-WLR is a combination of Logistic Regression (LR) rare events corrections and Truncated Regularized Iteratively Re-weighted Least Squares (TR-IRLS). Rare event correction in LR is applied to Weighted Logistic Regression (WLR). Regularization was added to reduce over-fitting. The estimation of ߚ is performed by using the method of maximum likelihood (ML), while WLR maximum likelihood estimates (MLE) were obtained by using IRLS method of Newton-Raphson algorithm. In order to solve large optimization problems, Truncated-Newton method is applied.
Sectoral Employment in Indonesia with Spatial and Seemingly Unrelated Regression (SUR) Model Approach Dewi, Vivin Novita; Setiawan, S; Rahayu, Santi Puteri
Proceeding ISETH (International Summit on Science, Technology, and Humanity) 2015: Proceeding ISETH (International Conference on Science, Technology, and Humanity)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/iseth.2377

Abstract

Employment becomes one of the most important focuses of development in Indonesia. Analysis of employment and its factors could be the consideration in making employment policies. Several studies of employment related to a particular economic sector have been carried out. For a comparison, this paper discussed the model of labor absorption with three economic sectors. The source of data was derived from all the provinces in Indonesia for five years. Spatial model was estimated with Maximum Likelihood Estimation (MLE) for each year of observation. Moran’s I and LM test were used to identify the spatial dependency. SUR model was estimated with Ordinary Least Square (OLS) and General Least Square (GLS).The variables used to estimate labor absorption were the output and real wage. The resultindicated that the spatial dependency was significant particularly in the agricultural sector with a spatial error model. Meanwhile, labor absorption was significantly affected by the output and real wage for both OLS estimation and GLS estimation for SUR model. Service sector had the highest R2 value. UR model with GLS estimation was evidenced to be more efficient than OLS estimation, in addition, standard error of parameters using GLS estimation evenly was lower than OLS estimation.