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All Journal SAINSMAT Indonesian Journal of Human Nutrition Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jambura Geoscience Review Jurnal Varian Mattawang: Jurnal Pengabdian Masyarakat Panrannuangku Jurnal Pengabdian Masyarakat ARRUS Journal of Mathematics and Applied Science Jurnal Klinik dan Riset Kesehatan Unnes Journal of Mathematics SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Management, Economic, and Accounting
Ruliana Ruliana, Ruliana
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Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Health Professions Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Training on Structural Equation Modelling (SEM) Analysis for Lecturers at Patompo University: Pelatihan Analisis Structural Equation Modelling (SEM) Bagi Dosen Universitas Patompo Ruliana, Ruliana; Sudarmin, Sudarmin; Meliyana, Sitti Masyitah; Rais, Zulkifli
Mattawang: Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2025)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang3180

Abstract

This community service project aims to enhance the understanding and skills of lecturers at Universitas Patompo in using Structural Equation Modelling (SEM) for research data analysis. The activity took place on September 18, 2024, and was attended by 28 lecturers. The main issues faced by the participants were a lack of understanding of SEM techniques and limited skills in using statistical software for analysis. The solution offered was an intensive training session that included the introduction of statistical software and the application of SEM using the Jamovi software. In addition, a community action planning process was implemented, involving the lecturers in the organization of the training. The results of this project showed a significant improvement in the participants' understanding and skills in SEM analysis.
Cluster Analysis Using Ensemble ROCK Method in District/City Grouping in South Sulawesi Province based on People's Welfare Indicators Hidayat, Taufiq; Ruliana, Ruliana; Rais, Zulkifli; Botto-Tobar, Miguel
ARRUS Journal of Mathematics and Applied Science Vol. 3 No. 1 (2023)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/mathscience1761

Abstract

Cluster analysis is a data mining technique used to group data based on the similarity of attributes of object data. One of the problems that are often encountered in cluster analysis is data with a mixed categorical and numerical scale. The clustering stage for mixed data using the ensemble ROCK (Robust Clustering using links) method is carried out by combining clustering outputs from categorical and numeric scale data. The method used for categorical data is the ROCK method and the method used for numerical data is the Hierarchical Agglomerative method. The best clustering method is determined based on the criteria for the ratio between the standard deviations within the group (SW) and the smallest standard deviation between groups (SB). Based on 24 observation objects in the regencies and cities of the Province of South Sulawesi, the ROCK ensemble method with a value of 0.1 produces three clusters with a ratio value of 2,27 x10-16 based on the combination of the output results of the ROCK method and the Hierarchical Agglomerative method
Pengaruh Makanan Kaya Gizi (KAYAZI) sebagai Variasi Diet Energi Protein Tinggi terhadap Daya Terima Makanan Pasien Covid-19 Anggraeny Putri, Nur; Ruliana, Ruliana; Yulianingrum, Chintya
Jurnal Klinik dan Riset Kesehatan Vol 1 No 2 (2022): Edisi Februari
Publisher : RSUD Dr. Saiful Anwar Province of East Java

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/jk-risk.01.2.2

Abstract

Background: Energy-Protein High (EPH) diet given as nutrition support in infection cases, including Covid-19. Low diet acceptance impact the patient’s recovery; but it can be solved by modified the diet menu. KAYAZI (Makanan Kaya Gizi) as innovation of EPH diet menu can be applied too for covid-19’s patients. Objective: Knowing the effect of KAYAZI as EPH diet variation on food acceptability in terms of food waste and dietary satisfaction in PUS at General Hospital dr. Saiful Anwar Malang. Method: Quasy Experimental with purposive sampling. Total 33 samples for each groups (standard-TKTP diet; KAYAZI diet) based on inclusion-exclusion criteria. Food waste data obtained from observing and filling in Comstock visual form. Dietary satisfaction data obtained from filling out Likert-scale questionnaire in hedonic-scale test. Data processed by software SPSS ver.16, with hypothesis testing nonparametric Mann-Whitney test (p value <0.05). Result: percentage of food waste from KAYAZI was smaller (10.5%) than TKTP diet (25.03%); the mean value of KAYAZI satisfaction level was higher in all assessment categories than the TKTP diet. From the Mann-Whitney, p value <0.05 on food waste and dietary satisfaction for parameters: aroma, taste, color, shape, food containers and cutlery. Meanwhile, dietary satisfaction on parameters of texture and way of food presenting, the value of p> 0.05. Conclusion: The provision of KAYAZI as diet variation affects food acceptability in term of food waste and dietary satisfaction for parameters: aroma, taste, color, shape, food containers and cutlery. But it has no effect in food texture parameter and way of food presenting.
PEMODELAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) PADA INDEKS HARGA SAHAM GABUNGAN (IHSG) TAHUN 2018 – 2023 Zakiyah Mar'ah; Ruliana, Ruliana; Magfirah Septiana
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 6 No. 01 (2024)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm144

Abstract

Nonparametric regression is one of the methods used to estimate the pattern of the relationship between response variables and predictor variables where the shape of the regression curve is unknown and is generally assumed to be contained in an infinite dimensional function space and is a smooth function (Eubank, 1999). The MARS method is one method that uses a nonparametric regression approach and high-dimensional data. These namely data has a number of predictor variables of 3 ≤ k ≤ 20 and data samples of size 50 ≤ n ≤ 1000. This research discusses Multivariate Adaptive Regression Spline (MARS) Modeling on the Composite Stock Price Index (JCI) 2018 - 2023. MARS modeling is obtained from a combination of basis function (BF), maximum interaction (MI), and minimum observation (MO) based on the minimum Generalized Cross Validation (GCV) value. The results of this study were obtained from the combination value of BF = 16, MI = 1, and MO = 2 with GCV = 60710.98. The factors that affect the Jakarta Composite Index (JCI) are Inflation (X1), Rupiah to USD Exchange Rate (X3), and Money Supply (X4).
Perbandingan Metode ARIMA dan Single Exponential Smoothing dalam Peramalan Nilai Ekspor Kakao Indonesia Fahmuddin S, Muhammad; Ruliana, Ruliana; Mustika M, Sitti Sri
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 03 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm193

Abstract

Indonesia is a country with an open economy, one of the sources of foreign exchange needed by a country with an open economy is exports. Cocoa is one of Indonesia's main export commodities that makes an important contribution to the country's economy, but the value of Indonesian cocoa exports fluctuates, that is there are inconsistent changes from time to time. The purpose of this study is to determine the results of forecasting the value of Indonesian cocoa exports, as well as to determine the best method for forecasting. This research compares the ARIMA and Single Exponential Smoothing methods to determine the best forecasting method. The best method is selected based on the smallest MAPE value. Based on the results of data analysis, the best forecasting model using the ARIMA method is the ARIMA (1, 0, 1) model, which has a MAPE value of 10.38060%. Meanwhile, the best forecasting model using the Single Exponential Smoothing method is with α = 0.16, which has a MAPE value of 10.92874%. So that the best method for forecasting the value of Indonesian cocoa exports is the ARIMA method
Metode Radial Basis Function Neural Network Untuk Klasifikasi Kab/Kota Tertinggal Di Provinsi Sulawesi Selatan Ruliana, Ruliana; Rais, Zulkifli; Mar'ah, Zakiyah; Hasnita, Hasnita
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol. 5 No. 03 (2023)
Publisher : Program Studi Statistika Fakultas MIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm197

Abstract

A disadvantaged area is an area that has the characteristics of tending to be left behind compared to other areas. Radial basis function neural networks are a part of Artificial Neural Networks, which use radial basis activation functions and are commonly used in classification cases. All districts/cities in South Sulawesi province have different characteristics from other districts/cities. Therefore, districts/cities are grouped into 2 groups to identify districts/cities that have characteristics that tend to be the same based on indicators of regional underdevelopment. The grouping results are then used as actual values ​​for classification using the RBFNN method, to determine the classification results and performance of the RBFNN method. In classifying districts/cities in South Sulawesi province based on indicators of regional underdevelopment using the radial basis function neural network method, an accuracy value of 91% was obtained using a comparison of 55% training data and 45% testing data and an f-measure value of 92% was obtained
Pengaruh Edukasi Gizi terhadap Asupan dan Status Gizi Pasien Sirosis Hati Mustika, Syifa; Nurmalita, Shafira; Samichah, Samichah; Putri, Fildzah Karunia; Sembiring, Frinny; Ruliana, Ruliana; Handayani, Dian
Indonesian Journal of Human Nutrition Vol. 7 No. 2 (2020)
Publisher : Department of Nutrition, Faculty of Health Sciences, Universitas Brawijaya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.ijhn.2020.007.02.5

Abstract

ABSTRAK Malnutrisi adalah masalah yang umum terjadi pada pasien sirosis hati. Kurangnya pengetahuan tentang gizi sehingga menyebabkan adanya pembatasan diet yang tidak perlu dan kemudian berkontribusi pada kejadian malnutrisi. Penelitian ini bertujuan untuk mengetahui adanya pengaruh pemberian edukasi gizi terhadap status gizi dan asupan pasien sirosis hati di Poli Gastroenterohepatologi Rumah Sakit dr. Saiful Anwar Malang. Jenis penelitian yang dilakukan termasuk dalam penelitian experimental dengan desain penelitian pre-post test control group design. Kelompok intervensi adalah kelompok yang diberi edukasi gizi pada awal pengambilan data, sedangkan kelompok kontrol adalah kelompok yang tidak diberi edukasi gizi. Data yang diambil pada penelitian ini adalah data antropometri, data asupan saat pengambilan data awal dan akhir serta data asupan makan partisipan yang dimonitoring selama 1 bulan menggunakan food diary. Hasil penelitian ini menunjukkan tidak terdapatnya penurunan yang signifikan (p=0.48) pada Indeks Massa Tubuh partisipan di kelompok intervensi dan kontrol. Sedangkan asupan energi dan karbohidrat pada kelompok intervensi mengalami peningkatan yang signifikan (p<0.05). Pemberian edukasi akan memberikan efek positif dan efektif jika dilakukan bersama dengan peningkatan aktivitas fisik. Efek dari pemberian edukasi gizi akan nampak bila durasi monitoring dan evaluasi diperpanjang. Kata kunci: edukasi gizi, sirosis hati, status gizi, asupan zat gizi, antropometri giziABSTRACT Malnutrition is a common problem among liver cirrhosis patients. Lack of knowledge about nutrition causes unnecessary dietary restrictions and leads to the incidence of malnutrition. This study aimed to determine the effect of nutrition education on intake and nutritional status of patients with liver cirrhosis at the Gastroenterohepatology Department, dr. Saiful Anwar General Hospital, Malang. The design used was an experimental study with a pre-post test control group. The intervention group is the group given nutrition education, while the control group is the group without nutrition education. The data taken in this study were anthropometric, intake data when taking initial and final data, and participants' daily food intake monitored for a month using a food diary. The study results showed no significant decrease (p = 0.48) in the body mass index of participants in the intervention and control groups. However, the energy and carbohydrate intake in the intervention group experienced a significant increase (p <0.05). Providing nutrition education will have a positive and effective effect if done together with increased physical activity. The duration of monitoring and evaluation should be extended to see the effectiveness of the nutrition educationKeywords: nutritional education, liver cirrhosis, nutritional status, nutrient intake, nutritional anthropometry
Spatio-Temporal Using Geographically Weighted Panel Regression for Modeling Environmental Quality Index Mar'ah, Zakiyah; Ruliana, Ruliana; Fikriani, Nurul Azurah; Ikhwana, Nur
Jurnal Varian Vol. 8 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i3.5416

Abstract

The Environmental Quality Index (EQI) represents a numerical measure used to assess Indonesia’s environmental conditions and is published annually by the Ministry of Environment and Forestry. In 2019, the EQI was recorded at 66.55, reflecting a decline of 5.12 points from 71.67 in 2018. This study aimed to analyze EQI across 34 Indonesian provinces during the 2018–2022 period using the Geographically Weighted Panel Regression (GWPR) approach. Data were obtained from the official Statistics Indonesia website. The purpose of employing GWPR was to capture both spatial and temporal variations in the factors influencing EQI, recognizing that environmental dynamics differ by region. Model selection tests for panel data indicated that the Fixed Effects Model (FEM) was the most appropriate specification. Therefore, GWPR was applied in combination with FEM to improve estimation accuracy. The results showed that the significant determinants of EQI varied across provinces, highlighting the heterogeneous nature of environmental challenges. The GWPR with Fixed Effect Model achieved a global R² of 84.38%, a substantial improvement compared to the 42.52% R2 from the conventional global Fixed Effect panel regression. This finding confirmed that GWPR provided stronger explanatory power by incorporating local variations into the analysis. The study concluded that adopting GWPR is essential for more precise modeling of environmental quality. Furthermore, the results highlighted the importance of region-specific environmental policies tailored to each province’s unique conditions in Indonesia 
Co-Authors Adiyanty, Tri Amelia Ahmar, Ansari Saleh Aidid, Muhammad Kasim Anggraeny Putri, Nur Arief Agoestanto Aswi, Aswi Aswi, Aswi Botto-Tobar, Miguel Dian Handayani Fahmuddin S, Muhammad Fikriani, Nurul Azurah Harahap, Muhammad Ikhsan Hasnita, Hasnita Ida Ayu Putu Sri Widnyani Ikhwana, Nur Irwan Irwan Maddatuang Maddatuang Magfirah Septiana Mangkona, Andi Ilham Azhar Mar'ah, Zakiyah Marni Marni, Marni Muhammad Arif Tiro, Muhammad Arif Mustika M, Sitti Sri Nasrul Nasrul Nurmalita, Shafira Nusrang, Muhammad Putri, Fildzah Karunia Putriaji Hendikawati Rais, Zulkifli Rosmini Maru Samichah Samichah Sembiring, Frinny Sitti Masyitah Meliyana R. Sudarmin Sudarmin Susiyanti, Susiyanti Suwardi Annas Syifa Mustika Taufiq Hidayat Yulianingrum, Chintya Zakiyah Mar'ah Zulkifli Rais