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Pelatihan Teknik Sampling Dan Survey Untuk Meningkatkan Kinerja Karyawan PT Mustika Jaya Lestari Semarang Yulianto, Safaat; Khikmah, Laelatul; Ambarwati, Atika Nurani; Wijayaningrum, Taswati Nova; Sulistijanti, Wellie
Intimas Vol 4 No 1 (2024)
Publisher : Fakultas Teknologi Informasi dan Industri Unisbank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/intimas.v4i1.9785

Abstract

Survey is a very important step in supporting decision making in various fields. In conducting surveys, surveyors are required to collect data that must be approached by statistical methods. To be able to understand and conduct surveys correctly, an understanding of statistical analysis is needed, especially on quantitative data. The low understanding and analysis of data and the use of statistical methods make survey results with quantitative data cannot be completed correctly. To be able to conduct surveys correctly, surveyors are also required to understand sampling techniques and statistical analysis in accordance with statistical rules. Community service in the form of training on Sampling and Survey Techniques can provide the benefits of understanding statistics and skills in using statistical methods and software to support quantitative surveys, especially in the field of animal husbandry. In addition, community service in the form of training can also provide significant benefits for employees of PT Mustika Jaya Semarang in conducting surveys of farmers and analyzing the resulting survey results.
Ordinal Logistic Regression Approach for Probability Analysis of Student Stress Levels Khikmah, Laelatul; Ratnasari, Elis Meida
Journal of Intelligent Computing & Health Informatics Vol 3, No 1 (2022): March
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v3i1.11793

Abstract

Stress is a condition or condition where a person feels pressured because of the many demands, both from within and from outside the individual that must be met. Stress is an uncomfortable stressful event for someone that can cause negative effects such as dizziness, emotional instability, irritability, loss of appetite, difficulty concentrating, and difficulty sleeping. One of the factors that cause stress is doing the Final Project. Someone who is experiencing stress can be seen from the level of stress, namely the level of mild, moderate and severe stress. To see a person's stress level, several variables can be used, namely physiological, emotional, cognitive, supervisory, and knowledge variables. This study aims to find out what variables affect stress levels in students. The analysis used is Ordinal Logistic Regression analysis which is one of the statistical analyzes used to determine the probability of events that are affected by the independent variable, where the response variable is a categorical scale. Variables that affect stress levels are emotional, cognitive and knowledge variables. The results showed that the higher a person's emotion, cognitive and knowledge, the smaller the chance for someone to experience severe levels of stress.
Modeling Spatial Error Model (SEM) On Human Development Index (IPM) In Central Java 2018 Wati, Aprilia Dwi Anggara; Khikmah, Laelatul
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6341

Abstract

The Human Development Index (HDI) is a human development index that is used to achieve the development outcomes of a region. HDI is formed by 3 basic dimensions, namely the health dimension as seen from the indicator of life expectancy at birth, the dimension of knowledge seen from a combination of indicators of average length of schooling and expectation of school years and dimensions of decent living standards as seen from the indicator of average per capita expenditure has been adjusted. The development of HDI in Central Java shows an increase every year. In 2018 the HDI figure for Central Java Province reached 71.12% and increased by 0.6% from the previous year. This is because the large HDI figures in an area are influenced by the large HDI numbers in adjacent areas. The location / area factor is thought to have a spatial dependence effect on the HDI figure. This problem can be overcome by using spatial regression by including the relationship between regions into the model. The spatial regression approach used in this study is the Spatial Error Model (SEM). The weighting matrix used in this study is Queen Contiguity (intersection between sides and corners). This study provides results that the variables that significantly influence HDI are poverty and school enrollment rates.
Modeling of Tuberculosis Case In Central Java 2018 With Three Knot Point Hapsari, Dina Fristantiningtyas Wiliyani; Khikmah, Laelatul
Journal of Intelligent Computing & Health Informatics Vol 1, No 2 (2020): September
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i2.6348

Abstract

Tuberculosis is a contagious disease caused by infection with the bacteria Mycobacterium Tuberculosis or known as Acid-Resistant Bacteria (BTA). Central Java is one of the provinces that has a high number of tubuerculosis cases in Indonesia. In 2018, Central Java was in second place after West Java in the highest number of Tuberculosis cases in Indonesia with the number of Tuberculosis cases of all types of 67,941 cases. Many variables can affect the number of TB cases. Therefore, a study was conducted in the form of modeling to determine the variables that affect the number of tuberculosis cases in Central Java. Based on data obtained from the Central Java Provincial Health Office in 2018, it shows that the pattern between the number of tuberculosis cases and the variables that are thought to influence it is not linearly related, then a spline regression approach is carried out. The results of this study indicate that the best spline regression model is to use three point knots with significant variables, namely population density and malnutrition. The value of ????2 obtained is 54.6%.
Binary Logistic Regression Analysis of Variables That Influence Poverty in Central Java Nurdiansah, Sendi Nugraha; Khikmah, Laelatul
Journal of Intelligent Computing & Health Informatics Vol 1, No 1 (2020): March
Publisher : Universitas Muhammadiyah Semarang Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jichi.v1i1.5381

Abstract

The phenomenon of poverty is a serious problem faced by almost every country in the world. This is because poverty can affect various aspects of people's lives. One of the causes of poverty is due to lack of income and assets to meet basic needs such as food, clothing, housing, health level and acceptable education. In addition, poverty occurs because of the powerlessness of society to get out of the problems it faces. The Central Java regional government incorporated poverty issues into the Regional Medium-Term Development Plan (RPJMD) because Central Java has a high number of poor people. This was done as an effort by the Central Java government to reduce poverty. Therefore, research is needed to find out the variables that most influence poverty in order to assist the government in developing the RPJMD. To find out what factors influence poverty in Central Java with the dichotomous categorical response variable, binary logistic regression analysis was used. The results showed that based on the analysis conducted did not obtain a logistic regression equation model because there were no significant parameters because there were no variables that had a sig value <0.05. Existing variables are Number of Population, Female Head of Household, Number of Children not in School, Number of Disabled Individuals, Number of Chronic Disease Individuals, Unemployment, Non-Electricity Lighting Sources, Unprotected Drinking Water Sources, Kerosene and Wood Cooking Fuels, Location Facilities Defecation (BAB) Not Available, so there are no variables that affect the level of poverty in Central Java Province.
Panel Data Regression Modeling of the GRDP of Banten Province for the Years 2016-2020 Alfa Puspita Swasti Anggraini; Khikmah, Laelatul
Journal of Applied Statistics and Data Mining Vol. 4 No. 2 (2023): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v4i2.30

Abstract

Banten is one of the provinces on the island of Java. Banten's Economy in 2020 decreased by 3.38 percent, even though in 2019 it still grew to 5.29 percent. This decline was also deeper than the National which only decreased 2.07 percent. Gross Regional Domestic Product (GDP) is one of the important indicators to determine the economic condition in an area or province in a certain period. Panel data is a combination of time data series and cross sections. Panel data regression is a regression by combining data cross section and time series in an equation. In this study, analysis was carried out panel data regression to determine the variables that affect the GRDP of Banten Province. The results of the analysis show that the best panel data regression model is Random Effect Model (REM). Variables that affect the GRDP of Banten Province are Total Residents and Domestic Investment.
SMALL AREA ESTIMATION TERHADAP PRODUK DOMESTIK REGIONAL BRUTO PER KAPITA ATAS DASAR HARGA KONSTAN PROVINSI JAWA BARAT DENGAN PENDEKATAN KERNEL Fida Fariha Amatullah; Khikmah, Laelatul
Journal of Applied Statistics and Data Mining Vol. 2 No. 2 (2021): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v2i2.40

Abstract

Jawa Barat merupakan salah satu provinsi di Pulau Jawa. Pertumbuhan Ekonomi Jawa Barat tahun 2019 tumbuh 5,07% melambat dibanding tahun 2018 sebesar 5,66%. PDRB perkapita merupakan indikator yang banyak digunakan untuk mengukur pertumbuhan ekonomi. Small Area Estimation (SAE) atau pendugaan area kecil yaitu suatu teknik statistika untuk menduga parameter-parameter subpopulasi dengan ukuran sampel kecil. Pada penelitian ini dilakukan pendugaan area kecil dengan pendekatan nonparametrik yaitu kernel. Variabel penyerta yang digunakan yaitu, pengeluaran pemerintah Kota/Kabubapaten Provinsi Jawa Barat tahun 2019. Berdasarkan penduga langsung Kota Bandung memiliki nilai PDRB perkapita tertinggi sebesar Rp. 78.808.426 dan Kabupaten Tasikmalaya memiliki nilai PDRB perkapita terendah sebesar Rp. 14.016.644. Hasil penduga tak langsung meunjukkan Kota Bandung memiliki nilai PDRB perkapita tertinggi sebesar Rp. 78.747.914 dan Kabupaten Tasikmalaya memiliki nilai PDRB perkapita terendah sebesar Rp. 14.002.015. Penduga tak langsung menghasilkan nilai varians lebih kecil yaitu sebesar 3,330054 dibanding penduga langsung sebesar 3,331698. Oleh karena itu, penduga tak langsung menunjukkan hasil yang lebih baik.
Analysis of Online Learning Satisfaction of Students at the Muhammadiyah Semarang Institute of Statistics and Business Technology Using Ordinal Logistic Regression Rahmania Novandra; Khikmah, Laelatul
Journal of Applied Statistics and Data Mining Vol. 4 No. 1 (2023): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v4i1.31

Abstract

Pada Desember 2019, kasus pneumonia misterius pertama kali dilaporkan di Wuhan, Provinsi Hubei, sampel yang diteliti menunjukkan etiologi coronavirus baru yaitu Corona Virus Disease 2019 (COVID-19) virus ini dapat ditularkan dari manusia ke manusia pemerintah memiliki kebijakan, salah satu kebijakannya dikeluarkan oleh Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi Republik Indonesia, menghimbau kepada semua mahasiswa agar dapat mengikuti pembelajaran secara jarak jauh dari rumah yaitu pembelajaran online. Pembelajaran online dilakukan juga oleh Program Studi Diploma Tiga Statistika Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang. Banyak kendala yang dialami oleh mahasiswa selama pembelajaran online, sehingga mahasiswa belum merasa puas terhadap pembelajaran online. Penelitian ini bertujuan untuk mengukur kepuasaan seorang mahasiswa terhadap pembelajaran online yang sudah dilakukan. Dengan pendekatan regresi logistik ordinal diperoleh 2 model dimana variabel yang berpengaruh terhadap kepuasan adalah variabel X₃ (Pengetahuan) dengan kategori 3 (Cukup), kategori 4 (Baik), dan kategori 5 (Sangat baik).
Analisis Variabel Yang Berpengaruh Pada Indeks Pembangunan Manusia (Ipm) Dengan Pendekatan Regresi Linier Berganda Aulia Fadhli Boer; Khikmah, Laelatul
Journal of Applied Statistics and Data Mining Vol. 3 No. 1 (2022): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v3i1.42

Abstract

Pembangunan ekonomi adalah suatu proses kenaikan pendapatan total dan pendapatan perkapita dengan mempertimbangkan adanya pertambahan penduduk dan disertai dengan perubahan fundamental dalam struktur ekonomi suatu daerah dan pemerataan pendapatan bagi suatu penduduk disuatu daerah. Pertumbuhan ekonomi yang stabil sangat diharapkan dapat mendongkrak pembangunan disuatu Negara yang sedang mengalami perkembangan seperti Indonesia, karena dapat mengatasi permasalahan ekonomi yang sering dialami oleh Negara kita ini diantaranya: kemiskinan, pengangguran, buta huruf (rendahnya angka Pendidikan), meningkatkan kesejahteraan masyarakat, dan memberikan perhatian lebih dibidang kesehatan dan Pendidikan. Kualitas sumber daya manusia dapat dilihat dari indeks kualitas hidup atau indek pembangunan manusia (IPM). Rendahnya IPM akan berakibat pada rendahnya produktivitas kerja dari penduduk. Produktivitas yang rendah bereakibat pada rendahnya perolehan pendapatan. Data yang digunakan adalah data Indeks Pembangunan Manusia (IPM) di Provinsi Jawa Tengah Pada Priode 2014-2018. Variabel yang digunakan dalam penelitian adalah Pembangunan Manusia (IPM) sebagai variabel dependen (Y), dan data Angka Harapan Hidup (X1), Angka Melek Huruf (X2), serta Pengeluaran Perkapita (X3) sebagai variabel independent. Kemudian analisis yang digunakan adalah metode analisi regresi linier berganda. Diperoleh hasil variabel yang berpengarauh terhadap IPM adalah variabel x1, dan x2. . Untuk variabel Angka Harapan Hidup (AHH) bertambah satu tahun maka nilai IPM akan naik sebesar 0,622 begitu juga dengan variabel Angka Melek Huruf bertambah satu tahun maka nilai IPM akan naik sebesar 3,640 dan variabel pengeluaran perkapita -0,00000001 yang berarti tidak berperngaruh signifikan terhadap kenaikan ataupun penurunan dari Indeks Pembangunan Manusia (IPM).
Binary Logistic Regression Analysis on Variables That Influence Early Marriage in East Java Province Radhyana Dwi Cahyaning Risdianti; Khikmah, Laelatul
Journal of Applied Statistics and Data Mining Vol. 5 No. 1 (2024): Journal Applied Statistics and Data Mining
Publisher : Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63229/jasdm.v5i1.66

Abstract

Pernikahan dini merugikan masyarakat, khususnya bagi perempuan, karena dapat menimbulkan kesenjangan yang tidak proporsional. Pernikahan yang terjadi sebelum usia 19 tahun disebut dengan pernikahan dini. Menemukan faktor-faktor yang mungkin mempengaruhi pernikahan dini di Provinsi Jawa Timur menjadi tujuan penelitian ini. Variabel terikat (Y) yang bersifat kategorikal dan variabel bebas (X) yang bersifat numerik atau kategorikal dihubungkan melalui metode regresi logistik biner. Data yang digunakan adalah data SDKI 2017 Provinsi Jawa Timur. Akses internet, jenis tempat tinggal, pendidikan perempuan, pendidikan pasangan, pekerjaan pasangan, dan indeks kekayaan merupakan variabel independen yang digunakan dalam penelitian ini. Temuan analisis menunjukkan bahwa model signifikan terakhir adalah perempuan yang tinggal di pedesaan yang memiliki tingkat pendidikan terakhir tidak sekolah, rendah dan menengah serta memiliki pasangan yang memiliki tingkat pendidikan terakhir rendah dan menengah