scholarly journals Revisiting Socio- economic impact of Villagization, In the Case Assosa Zone , Ethiopia

2021 ◽  
Vol 9 (1) ◽  
pp. 01-11
Author(s):  
Tadele Tesfaye Labiso
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Qualitative Methods ◽  
Sample Size ◽  
Social Services ◽  
Research Method ◽  
Binary Logistic Regression ◽  
Survey Study ◽  
Exploratory Research ◽  
Socio Economic Impact

The overall objective of this study is to explore the  practice and challenges of villagization; in the selected woredas of the Assosa zone  Beninshangul Gumuz regional state. To achieve goals of the survey study mixed research method was employed. Generally. the Sample size of 168 sample households were determined by using S = X2NP(1-P) ÷ d2 (N-1) + X2P (1-P), The research employed exploratory research design on the challenges and implementation of the program, and it applied mainly qualitative methods. On the basis and types of data gathered and the instrument used, both quantitative and qualitative techniques of data analysis or binary logistic regression supported by SPSS was employed. The only good thing about this life was farming since people had fertile lands. But, when villagization was implemented the lives of the villagers improved because they started to have better access to social services. The study showed that villagization was implemented voluntarily and based on the consent of the local people. However, it is possible to conclude that villagization has significantly improved the lives of the villagers by bringing positive changes that did not exist before. people.

scholarly journals ANALYSIS OF FARM CASSAVA PARTNERSHIP IN THE VILLAGE OF GREAT PUDDING BESAR DISTRICT OF BANGKA

2020 ◽  
Vol 2 (2) ◽  
pp. 91-104
Author(s):  
Yansah Yansah ◽  
Iwan Setiawan ◽  
Yudi Sapta Pranoto
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Binary Logistic Regression ◽  
T Test ◽  
Survey Method ◽  
Real Difference ◽  
Average Income ◽  
The Difference ◽  
Quota Sampling ◽  
The Village

This study aims to describe the implementation of the partnership farming Cassava Village Pudding Besar District of pudding Big Bangka, analyze the differences in average income that is obtained by farmers from various partnership schemes cassava in the village Pudding Besar District of pudding Big Bangka, analyzed the factors - factors that influence farmers' decision in choosing partners and not partner with partnership cassava farm in the village of Great pudding pudding Large District of Bangka. This study was conducted in January 2019 until January 2020 in the village of Great Pudding Pudding Large District of Bangka. The method used is survey method. Penrikan method used example is a method of quota sampling with a sample of two groups of 40 people and the partnering farmers do not partner 40 people. Methods of data analysis using descriptive qualitative, quantitative analsisis (independent sample t-test, binary logistic regression). The results showed the implementation of partnership farming patterns occurring in the village of Great Pudding is a partnership with the name intiplasma KSR Program (Cassava People's Gardens). There is a real difference but not significant, the average income of Rp 32,384,718 partner farmers, while the non- partner farmers Rp 36,751,056 with the difference in the average income of farmers partner and non- partner Rp 4,366,388 per year. Factors that significantly affect farmers' decisions in partnering and partnering as age and availability of capital.

scholarly journals Predictive Performance of Logistic Regression for Imbalanced Data with Categorical Covariate

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Hezlin Aryani Abd Rahman ◽  
Yap Bee Wah ◽  
Ong Seng Huat
Keyword(s):  
Logistic Regression ◽  
Sample Size ◽  
Imbalanced Data ◽  
Binary Logistic Regression ◽  
Predictive Performance ◽  
Parameter Estimate ◽  
Classification Performance ◽  
Parameter Estimates ◽  
Binary Dependent Variable ◽  
Simulation Results

Logistic regression is often used for the classification of a binary categorical dependent variable using various types of covariates (continuous or categorical). Imbalanced data will lead to biased parameter estimates and classification performance of the logistic regression model. Imbalanced data occurs when the number of cases in one category of the binary dependent variable is very much smaller than the other category. This simulation study investigates the effect of imbalanced data measured by imbalanced ratio on the parameter estimate of the binary logistic regression with a categorical covariate. Datasets were simulated with controlled different percentages of imbalance ratio (IR), from 1% to 50%, and for various sample sizes. The simulated datasets were then modeled using binary logistic regression. The bias in the estimates was measured using MSE (Mean Square Error). The simulation results provided evidence that the effect of imbalance ratio on the parameter estimate of the covariate decreased as sample size increased. The bias of the estimates depended on sample size whereby for sample size 100, 500, 1000 – 2000 and 2500 – 3500, the estimates were biased for IR below 30%, 10%, 5% and 2% respectively. Results also showed that parameter estimates were all biased at IR 1% for all sample size. An application using a real dataset supported the simulation results.

scholarly journals PENGARUH YOUTUBE ADVERTISING TERHADAP RESPONS KONSUMEN

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Arief Pratama
Keyword(s):  
Data Analysis ◽  
Sample Size ◽  
Research Method ◽  
Consumer Response ◽  
Advertising Research ◽  
Response Theory ◽  
Literature Study ◽  
Consumer Responses ◽  
Processing Data ◽  
Analysis Technique

The purpose of this research is to study YouTube advertising research on consumer responses. The theory used is the theory of advertising value (informativeness, credibility, entertainment, irritation) and consumer response theory (awareness, knowledge, preferences, preferences, beliefs, purchases). This research is quantitative, while the research method is a survey with a type of explanatory research. The population in this study 344 people were students of STIKOM Interstudi year 2016-2017. To determine the sample size using the Slovin formula, collecting 100 respondents. The technique of answering data is done by closed question questionnaire, observation, literature, and literature study. While the data analysis technique is done by processing data using SPSS, analyzing data with statistical formulas and interpreting them. The results of this study are among YouTube advertisements on consumer responses showing strong results.

scholarly journals Consumer Willingness to Pay for The Purchase of Spicy Acid Catfish at Pondok Gurih Restaurant, Pekanbaru

2020 ◽  
Vol 008 (01) ◽  
pp. 82-96
Author(s):  
Fitri Yuliasma ◽  
◽  
Trisla Warningsih ◽  
Darwis AN ◽  
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Willingness To Pay ◽  
Product Quality ◽  
Research Method ◽  
Secondary Data ◽  
Primary Data ◽  
Survey Method ◽  
Improve Product Quality ◽  
Analysis Method

This research was conducted at Pondok Gurih Restaurant, Pekanbaru which aims to calculate the value of the willingness to pay of consumers and to analyze the factors that affect the willingness to pay of consumers for the purchase of catfish spicy acid. This research can be used as information material for the restaurant to improve the quality and facilities for consumer demand. The research method used is a survey method that used primary data and secondary data. The data collection techniques through interviews. The sample in this study are consumers who eat at the restaurant and are willing to be interviewed. The number of respondents used in this study was 100 people. The data analysis method used in this research is logistic regression. The results showed that the average cost to be paid by consumers was IDR 87,410 with the lowest WTP value of IDR 40,000 and the highest was IDR 150,000. Then the variables that significantly affect the consumer's desire to pay are age, income, education, and product quality. The variables that did not have a significant effect were gender, service quality, and occupation. Suggestions for businesses are to continue to improve product quality.

scholarly journals INFLUENCE OF PHARMACISTS’ INTERVENTION ON DRUG-RELATED PROBLEMS RELATED TO CHANGE IN HEMOGLOBIN LEVELS OF HEMODIALYSIS PATIENTS AT ADJIDARMO HOSPITAL, LEBAK, BANTEN

2017 ◽  
Vol 10 (17) ◽  
pp. 124
Author(s):  
Ai Yeni Herlinawati ◽  
Rani Saurisari ◽  
Retnosariandrajati Retnosariandrajati
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Data Analysis ◽  
Odds Ratio ◽  
Multivariate Data Analysis ◽  
Binary Logistic Regression ◽  
Hemodialysis Patients ◽  
Binary Logistic Regression Analysis ◽  
Average Increase ◽  
Drug Related Problems

  Objective: This study aims to evaluate the intervention of pharmacists for drug-related problems (DRPs) related to hemoglobin (Hb) level.Methods: This study uses a prospective pre-experimental and pre-post design. The study sample included 85 patients. All patients were interviewed, and their prescriptions were identified. Then, interventions were given to doctors and patients based on the identified DRPs. Univariate, bivariate, and multivariate data analysis with binary logistic regression analysis were used.Results: There was a significant decrease (p<0.05) in the number of DRPs before (2.85±1.82) and after (0.74±0.86) the intervention. There was also a significant increase (p<0.05) in the average Hb level before (9.29±1.39) and after (9.68±1.41) the intervention; the average increase in Hb level after the intervention was 0.39 g/dl. DRP significantly influences the changes in Hb level after the intervention. Hb level increased by 0.145 times after intervention (odds ratio=0.145, p=0.015).Conclusions: Pharmacists’ intervention for DRPs can increase the success of anemia therapy of hemodialysis patients at Adjidarmo Hospital, Lebak, Banten.

Character education in schools implementing national curriculum and international baccalaureate

10.26539/1387 ◽  
2018 ◽  
Vol 1 (3) ◽  
pp. 192
Author(s):  
Hotmaulina Sihotang ◽  
Stevanie Datrix
Keyword(s):  
High School ◽  
Data Analysis ◽  
Character Education ◽  
Social Services ◽  
Research Method ◽  
International Baccalaureate ◽  
National Curriculum ◽  
Self Concept ◽  
Self Management ◽  
Learner Profile

The purpose of the study was to evaluate the implementation of the character education program of Junior and Senior High School Victory Plus School using the national curriculum and International Baccalaureate. The research method used is mix method. The result of data analysis showed that the average self-concept score was 2.65 (less good); self-management is 2.73 (good); and social services is 2.73 (good) in the implementation of courageous, honest, active, mindful, innovative, open minded, and nobel (champion) value. The value of champion is relevant to the value of the national curriculum character but the value of hard work, religion, democracy, the spirit of nationality, and the love of the homeland have not yet appeared. The balanced and reflective values in the learner profile are not yet visible.

scholarly journals AKTIVITAS PENGHIMPUNAN DANA PADA PT. BANK PEMBANGUNAN DAERAH SUMATERA BARAT CABANG PAINAN

2020 ◽  
Author(s):  
Romi Susanto ◽  
Yaumil Ratna Sari
Keyword(s):  
Data Analysis ◽  
Qualitative Methods ◽  
Regional Development ◽  
Research Method ◽  
Qualitative Data ◽  
Development Bank ◽  
Qualitative Data Analysis ◽  
West Sumatra ◽  
Regional Development Bank ◽  
Data Analysis Methods

This study aims to find out how the activities of raising funds at PT Bank of West Sumatra Regional Development Painan Branch of this study uses qualitative data analysis methods as a research method, where qualitative methods describe, understand and explain the data studied during the research took place at PT. West Sumatra Regional Development Bank Painan Branch. PT. West Sumatra Regional Development Bank Painan Branch is an institution engaged in the field of banking, by choosing bank products. Can be seen in the development of customers in collecting funds where most interested are in deposit products.

scholarly journals Diagnosing Multicollinearity of Logistic Regression Model

2019 ◽  
pp. 1-9 ◽  
Author(s):  
N. A. M. R. Senaviratna ◽  
T. M. J. A. Cooray
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Sample Size ◽  
Logistic Regression Model ◽  
Secondary Data ◽  
Binary Logistic Regression ◽  
Condition Index ◽  
Binary Logistic Regression Model ◽  
Correlated Variables ◽  
Explanatory Variables

One of the key problems arises in binary logistic regression model is that explanatory variables being considered for the logistic regression model are highly correlated among themselves. Multicollinearity will cause unstable estimates and inaccurate variances that affects confidence intervals and hypothesis tests. Aim of this was to discuss some diagnostic measurements to detect multicollinearity namely tolerance, Variance Inflation Factor (VIF), condition index and variance proportions. The adapted diagnostics are illustrated with data based on a study of road accidents. Secondary data used from 2014 to 2016 in this study were acquired from the Traffic Police headquarters, Colombo in Sri Lanka. The response variable is accident severity that consists of two levels particularly grievous and non-grievous. Multicolinearity is identified by correlation matrix, tolerance and VIF values and confirmed by condition index and variance proportions. The range of solutions available for logistic regression such as increasing sample size, dropping one of the correlated variables and combining variables into an index. It is safely concluded that without increasing sample size, to omit one of the correlated variables can reduce multicollinearity considerably.

scholarly journals Μέθοδοι πρόβλεψης εκλογικών αποτελεσμάτων

2014 ◽  
Author(s):  
Γεωργία Παναγιωτίδου
Keyword(s):  
Cluster Analysis ◽  
Logistic Regression ◽  
Data Analysis ◽  
Discriminant Analysis ◽  
Binary Logistic Regression ◽  
Fuzzy Cluster ◽  
Fuzzy Cluster Analysis ◽  
Exit Poll

Θέμα της διατριβής με τίτλο «Μέθοδοι Πρόβλεψης Εκλογικών Αποτελεσμάτων. Συγκριτική Μελέτη Εργαλείων του Διαδικτύου» είναι η μελέτη των υφιστάμενων μεθόδων ανάλυσης πρόβλεψης των εκλογικών αποτελεσμάτων. Η εργασία έχει ως στόχο την συγκριτική μελέτη των μεθόδων που εφαρμόζονται στην εκλογική έρευνα για την ανάλυση της συμπεριφοράς των ψηφοφόρων και συγκεκριμένα την πρόβλεψη της εκλογικής τους στάσης. Η μελέτη επικεντρώνεται στις τρεις σημαντικότερες μεθόδους πρόβλεψης εκλογικού αποτελέσματος, που έχουν χρησιμοποιηθεί κατά τα τελευταία χρόνια στην Ελλάδα και επεκτείνεται στην ανάλυση μιας νέας καινοτόμου μεθόδου όπως προκύπτει από την ανάλυση των δεδομένων του Ηλεκτρονικού Συμβούλου Ψήφου (helpmevote): 1) τη δημοσκόπηση εξόδου (Exit Poll), 2) τη δημοσκόπηση πρόθεσης ψήφου με στάθμιση των δεδομένων, 3) την ανάλυση χρονοσειρών σε σχέση με την πρόθεση ψήφου για την εκτίμηση της εκλογικής επιρροής των κομμάτων. Επιπρόσθετα, εκτός από την περιγραφή των κυριότερων τεχνικών, αναλύεται η αποτελεσματικότητα αυτών των μεθόδων, όσον αφορά την εγγύτητα των προβλέψεων τους ως προς τα πραγματικά εκλογικά αποτελέσματα. Ταυτόχρονα, διερευνώνται επί μέρους ζητήματα που δημιουργούν προβλήματα στην εγκυρότητα των μεθόδων, όπως η στάθμιση των δεδομένων, η αντιμετώπιση της αδιευκρίνιστης ψήφου και πολλά τεχνικά ζητήματα, που αφορούν την εφαρμογή των μεθόδων αυτών, ιδιαίτερα στο υφιστάμενο εκλογικό περιβάλλον της Ελλάδας, όπου τα τελευταία χρόνια παρατηρούνται δομικές μεταβολές στο κομματικό σύστημα, καθώς επίσης στην εκλογική συμπεριφορά των ψηφοφόρων και στη στάση των ερωτώμενων στις δημοσκοπήσεις, καθιστώντας τις έως τώρα χρησιμοποιούμενες μεθοδολογίες πρόβλεψης της ψήφου προβληματικές. Επιπρόσθετα, επιχειρείται η δημιουργία ενός αποτελεσματικότερου μοντέλου πρόβλεψης με τη χρήση εργαλείων του διαδικτύου και συγκεκριμένα τον ηλεκτρονικό σύμβουλο ψήφου. Στο πλαίσιο διεξαγωγής της έρευνας έγινε ανάλυση των δεδομένων από την εφαρμογή helpmevote στις περιφερειακές εκλογές του 2010. Στο πρώτο σκέλος της ανάλυσης διερευνώνται τρία κυρίως ερωτήματα: 1) o εντοπισμός ομάδων ψηφοφόρων οι οποίοι παρουσιάζουν παρόμοιες απόψεις με τους υποψηφίους της περιφέρειάς τους και η συσχέτιση των ομάδων αυτών με συγκεκριμένα θέματα και εκλογικές προτιμήσεις, 2) η πρόβλεψη της επιλογής ψήφου όσων δηλώνουν αναποφάσιστοι ή όσων αρνούνται να δηλώσουν πρόθεση ψήφου, με βάση το βαθμό ταύτισής τους με τα πρόσωπα, τα κόμματα και με τα θέματα, 3) το ποσοστό στο οποίο συμμετέχει ο παράγοντας θέματα, στην τελική επιλογή ψήφου και η δημιουργία μοντέλου πρόβλεψης στη βάση αυτών. Στο δεύτερο σκέλος της ανάλυσης επιχειρείται η κατασκευή γραμμικού μοντέλου με στόχο την πρόβλεψη της πρόθεσης ψήφου, χρησιμοποιώντας ως κύριες μεταβλητές την τοποθέτηση των ψηφοφόρων ως προς τα θέματα και τον βαθμό ταύτισής τους με τους υποψηφίους. Ως ανεξάρτητες μεταβλητές της συνάρτησης επιλέγονται η δηλωμένη πρόθεση ψήφου και σε αναζήτηση ενός εναλλακτικού μοντέλου η προβλεπόμενη πρόθεση ψήφου όπως προέκυψε από το πρώτο σκέλος της ανάλυσης. Ως μέθοδοι ανάλυσης προτείνονται η Discriminant Analysis, η Fuzzy Cluster Analysis, η ανάλυση κατά στοιβάδες (Stacked Data Analysis) και η Binary Logistic Regression.

Sign in / Sign up

Export Citation Format

Share Document