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All Journal EKSAKTA: Journal of Sciences and Data Analysis Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Kreano, Jurnal Matematika Kreatif-Inovatif Jurnal Riset Pendidikan Matematika AJIE (Asian Journal of Innovation and Entrepreneurship) JURNAL PENGABDIAN KEPADA MASYARAKAT E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIV : International Journal on Informatics Visualization Jurnal Aplikasi Statistika & Komputasi Statistik Jurnal Abdimas Madani dan Lestari (JAMALI) Refleksi Pembelajaran Inovatif Jurnal Statistika dan Aplikasinya JAMBURA JOURNAL OF PROBABILITY AND STATISTICS JNPM (Jurnal Nasional Pendidikan Matematika) STATISTIKA
ACHMAD FAUZAN
Universitas Islam Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Social Sciences Other

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Journal : EKSAKTA: Journal of Sciences and Data Analysis

 1 
Study of Student Satisfaction Level in the Faculty Based on Performance Assessment and Interest Level Achmad Fauzan; Muhammad Hasan Sidiq Kurniawan; Jaka Nugraha
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 19, ISSUE 1, February 2019
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol19.iss1.art8

Abstract

One way to evaluate various services at the university is seen from the level of student satisfaction. The purpose of this study is to measure how much the level of student satisfaction in the university environment, especially in the Faculty of Mathematics and Natural Sciences, Universitas Islam Indonesia (FMIPA UII) and future expectations of students focusing on their respective study programs. 6 aspects were used to find out how much satisfaction the students had, namely: (1) Tangible, (2) Reliability, (3) Responsiveness, (4) Assurance, (5) Empathy, and (6) Information. The research method used is descriptive analysis method related to satisfaction represented by the Cartesian diagram. The study was conducted in a period of 3 months with the sample used being active students in the 2016 and 2017 FMIPA classes proportionally in each study program (study program). The data used are primary data consisting of 2 main assessments, namely performance assessment and importance assessment. The results of the level of satisfaction / suitability are classified into the Cartesian diagram which consists of 4 priorities, namely: top priority, achievement priority, low priority, and excessive. The results of the study obtained overall levels of satisfaction in Mathematics as much as 90% of students were satisfied with the level of performance provided. However, there are still 2 indicators that are included in the priority, namely problems in the key-in process and ease of communication for parents of students to consult. In addition to the contents of each indicator, an analysis of suggestions for improvement in the FMIPA environment using text mining based on barplot and wordcloud is associated with the dominant words appearing to describe the general expectations of students
Analysis of Factors Influencing The Decision to Choose The Department in The Natural Science Campus Muhammad Hasan Sidiq Kurniawan; Achmad Fauzan; Jaka Nugraha
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 1, ISSUE 1, February 2020
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol1.iss1.art12

Abstract

Education is very important thing for everyone. Parents tend to choose high-quality school or campus, to ensure their children’s education. One thing which determined parents to choose the campus for their children is the prospect for work. Faculty of Natural Science UII have high-quality department. Some of them already had highest accreditation level and even Internationally accredited. But some peoples in Indonesian often asked about what become of their children after graduated from the faculty of natural science or what is job that suit for their chlidren. The department of that faculty often not become the first choice when choosing campus. Therefore, the research to study about factors which determine people to choose their college department is needed. In this paper, the study is focused on factors which influence people’s decision score to choose the department in the faculty of natural science. We are using correlation and regression analysis. The result show that factors which influence the people’s decision are different between one department with another. Those factor consist of: product, promotion, and the price/cost.
Clustering Provinces in Indonesia based on Community Welfare Indicators Sekti Kartika Dini; Achmad Fauzan
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 1, ISSUE 1, February 2020
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol1.iss1.art9

Abstract

The Preamble of the 1945 Constitution of the Republic of Indonesia explicitly states that the main task of the government of the Republic of Indonesia is to advance general prosperity, to develop the nation's intellectual life, and to realize social justice for all Indonesian people. Social inequality is a problem that is still faced by Indonesian people today. To solve the problem required supporting data analysis as a basis for policy formulation. This research was conducted with the aim of clustering provinces in Indonesia based on community welfare indicators using K-Means cluster analysis. K-Means cluster analysis is chosen based on the variance value (0.101), which is smaller than the variance value in the average linkage cluster analysis (0.152). Based on data analysis, provinces in Indonesia are clustered into three where the first cluster consists of 21 provinces, the second cluster consists of 3 provinces, and the third cluster consists of 10 provinces. Each cluster has different characteristics that can be of concern to the parties concerned to overcome the social welfare gap. Besides, in order cluster results are more easily understood, visualization of results is added with a Geographic Information System (GIS) using Indonesian maps accompanied by differences in color gradations for each cluster
Impacts of Human Development Index and Percentage of Total Population on Poverty using OLS and GWR models in Central Java, Indonesia Duhania Oktasya Mahara; Achmad Fauzan
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 2, August 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss2.art8

Abstract

Central Java province is one of the provinces with the highest number of poor people on the island of Java, with the number of poor people in 2020 increasing by 0.44 million people from the previous year. Poverty is caused by several factors, one of which is the Human Development Index (HDI) and the Total Population level. Each region has different characteristics from other regions. These differences in characteristics cause more specific spatial effects, namely spatial heterogeneity. Geographically Weighted Regression (GWR) is a statistical method that can analyze spatial heterogeneity by assigning different weights and models to each observation location. This study aims to determine whether the HDI variable and percentage of total population significantly impact the number of poor people in Central Java Province in 2020 without eliminating the spatial effect. There are three groupings of variables that affect the Number of Poor People for GWR with the Adaptive Kernel Bisquare weighting function and four groups for the Adaptive Kernel Tricube weighting function. The Key Performance Indicators (KPI) used are Mean , Akaike Information Criterion (AIC), Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). Based on these KPIs, the GWR model with the Adaptive Kernel Bisquare weighting function provides better results when compared to the OLS model.
Analysis of Hotels Spatial Clustering in Bali: Density-Based Spatial Clustering of Application Noise (DBSCAN) Algorithm Approach Achmad Fauzan; Afdelia Novianti; Raden Rara Mentari Ayu Ramadhani; Marcelinus Alfafisurya Setya Adhiwibawa
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 3, ISSUE 1, February 2022
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol3.iss1.art4

Abstract

Bali is one of the hearts of tourism in Indonesia. The existence of the Covid-19 pandemic has made this tourist paradise also affected the wheels of the economy. Based on this, this study aims to determine the density clustering of one of the economic supporters in Bali, namely hospitality. The study began with the quadrant method and Ripley's K-Function to measure the distribution pattern of hospitality. From the results of the two methods, the distribution pattern of hotels in Bali is more towards clusters than random or regular distribution. If the point distribution pattern is more towards the cluster, it is continued with the Density-Based Spatial Clustering of Application Noise (DBSCAN) algorithm to form spatial clustering. In the DBSCAN algorithm, a combination of parameters, namely minimum points (MinPts) and epsilon (Eps), is carried out with evaluation using the silhouette average width value. From the results of the DBSCAN algorithm, the clustering results show that the distribution of hotels in Bali forms clusters and tends to approach the surrounding tourist attractions, such as near the beach, city market, and mountainous areas. It can help policymakers if they want to prioritize economic recovery after the Covid-19 pandemic.
Analisis Karakter Tertanggung oleh Pemegang Polis Perusahaan Asuransi Swasta di Indonesia dengan Metode Rough Set Ameilea Chealsea Ekaputrie; Achmad Fauzan
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 4, ISSUE 2, August 2023
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol4.iss2.art2

Abstract

Insurance provides services in the form of services in facilitating a disaster that may occur based on a history of problems that have occurred. One of the private insurance companies in Indonesia has provided an insurance service program to guarantee employee welfare for policy-holding companies. The purpose of this research is to find out the pattern of association rules from the character of the insured by the policyholder so that it is expected to be able to make valuable information as input or consideration for the policymakers of private insurance companies in Indonesia. This study uses the rough set method as one of the efficient data analysis methods or techniques in database mining or knowledge discovery in relational databases. Rough sets provide algorithms to quickly and easily find hidden patterns in data. The results of the pattern of association rules for the character of the insured by the policyholder have formed as many as 14 rules. The certainty value is intended as a proportionate evaluation amount in order to find out the record of insurance claims that can be chosen by the insured. At the same time, the coverage value is intended as an evaluation amount to produce a decision for the insured to submit a claim record. The probable percentage of all events that are most recommended is seen from the highest coverage value related to record indicators, namely for administration by 45.9%, inspection by 44.1%, others by 40.8%, operation by 48.8%, financing by 46.3%, maintenance by 42%, and compensation of 65.9%.
Comparison of Inverse Distance Weighted and Thin Plate Spline Interpolation Methods in Projecting the Strength of the West Sumatra Earthquake Nabila Azzahra Haris Putri; Fauzan, Achmad
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 2, October 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss2.art9

Abstract

The Indonesian archipelago is situated in a highly active geological zone, making it prone to frequent earthquakes. West Sumatra, located on the west coast of central Sumatra, comprises lowland coastal areas and volcanic plateaus formed by the Barisan Mountains, covering a land area of 42,297.30 km² (2.17% of Indonesia's territory). This research aims to determine which interpolation method—Inverse Distance Weighted (IDW) and Thin Plate Spline (TPS)—provides more accurate predictions of earthquake strength in West Sumatra. The dataset consists of 229 earthquake events, divided into 90% for training (206 points) and 10% for testing (23 points). The training data was further subdivided into 80% training data 2 (164 points) and 20% validation data (42 points). The interpolation processes using the IDW and TPS methods were repeated 100 times, with the training 2 and validation data randomly shuffled in each iteration. Visualization of the interpolation results indicated that the earthquake magnitudes ranged from 2.0 to 4.5. Although the Mean Absolute Percentage Error (MAPE) values for the TPS method on the test and validation datasets were 16.42 and 14.29, respectively—slightly lower than the MAPE values for the IDW method—the t-test results showed no statistically significant difference between the two methods. Statistically, there is no significant difference between IDW and TPS in terms of predictive accuracy. However, researchers prefer the IDW method due to its computational efficiency and simplicity. Therefore, IDW is considered the most suitable method for analyzing earthquake strength in the West Sumatra region
Co-Authors Abdullah Ahmad Dzikrullah Adriana, Hannura Afdelia Novianti Afdelia Novianti Ameilea Chealsea Ekaputrie Annisa Fitria Asyharul Muala Bariklana, Muhammad Daniar Wahyu Laraswati Dini, Sekti Kartika Duhania Oktasya Mahara Duhania Oktasya Mahara Edy Widodo Elita Nurfitriyani Sulistyo Farhatun Nissa Fitri Amalia Ganjar Fadillah, Ganjar IKA MEIZA MAHARANI Irwan Sutisna Jaka Nugraha Malecita Nur Atala Singgih Marcelinus Alfafisurya Setya Adhiwibawa Marcelinus Alfafisurya Setya Adhiwibawa Mega Luna Suliztia Muhammad Hasan Sidiq Kurniawan Muthia Citra Safira Muthia Citra Safira Muthia Dishanur Izzati Nabila Azzahra Haris Putri Nanda Lailatul Humairoh Novendri Isra Asriny Novendri Isra Asriny Novendri Isra Asriny Raden Rara Mentari Ayu Ramadhani Rahmi Novika Harahap Riefyal Arshyzha Mustain Rohmatul Fajriyah Sekti Kartika Dini Shazia Ayesha Azzahra Sheilta Alphenia Sheilta Alphenia Syifa Ayu Anjani Wiranti Nugrah Andini