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All Journal FORUM STATISTIKA DAN KOMPUTASI Jurnal Sains dan Seni ITS Gudang Jurnal Multidisiplin Ilmu Triwikrama: Jurnal Ilmu Sosial Kohesi: Jurnal Sains dan Teknologi Mutiara : Jurnal Ilmiah Multidisiplin Indonesia Perspektif: Jurnal Pendidikan dan Ilmu Bahasa Jurnal Penelitian Teknologi Informasi dan Sains Neraca Manajemen, Akuntansi, dan Ekonomi Cendikia Pendidikan Ebisnis Manajemen Trigonometri: Jurnal Matematika dan Ilmu Pengetahuan Alam ARIMA : Jurnal Sosial Dan Humaniora Jurnal Pendidikan dan Pengajaran Zoologi: Jurnal Ilmu Peternakan, Ilmu Perikanan, Ilmu Kedokteran Hewan Switch: Jurnal Sains dan Teknologi Informasi Pentagon: Jurnal Matematika dan Ilmu Pengetahuan Alam Bilangan: Jurnal Ilmiah Matematika, Kebumian dan Angkasa Algoritma: Jurnal Matematika, Ilmu Pengetahuan Alam, Kebumian dan Angkasa Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Jurnal Pustaka Cendekia Pendidikan IPSSJ Konstanta : Jurnal Matematika dan Ilmu Pengelatuan Alam
Sri Pingit Wulandari
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Analisis Cluster Kabupaten/Kota di Jawa Timur Berdasarkan Faktor Kesejahteraan Masyarakat Tahun 2023 Rindy Retno Prihastari; Salsabila Aulia Azizah; Sri Pingit Wulandari
Mutiara: Jurnal Ilmiah Multidisiplin Indonesia Vol. 2 No. 4 (2024): JIMI - OKTOBER
Publisher : PT. PENERBIT TIGA MUTIARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61404/jimi.v2i4.329

Abstract

East Java Province is a region with significant economic contribution in Indonesia, occupying the third position nationally with a contribution of 14.26%. However, despite its rapid economic growth, East Java still faces welfare challenges, especially in terms of poverty which is still relatively high compared to other provinces on the island of Java. The poverty rate in East Java is on a downward trend, but it still remains above the national average. This condition indicates an imbalance in the welfare of the community in the East Java region. Welfare is measured based on the ability of the community to meet decent, healthy, and productive basic needs, with the Human Development Index (HDI) as one of the main indicators. HDI can measure human development achievements based on several basic components of quality of life, including the education dimension, the age and health dimension, and the standard of decent living. Therefore, the government needs to group regions with appropriate characteristics to make it easier to make policies. One of the statistical analyses that can be used in this study is cluster analysis. The results of this study are that East Java Province in 2023 shows a diversity of welfare indicators, such as TPT, HDI, and AHH, reflecting differences in economic, educational, and health conditions between regions. The cluster method with the best assessment in this study is the K-Means method with five clusters. The characteristics in clusters I and II tend to have low welfare, while clusters III, IV, and V show better welfare. The results of this study show a change in the number of clusters compared to previous research conducted by Muhammad Fikry Al Farizi et al. in 2022. The previous study produced four clusters using the average linkage method.
Pengelompokan Provinsi berdasarkan Aspek Pembangunan Pendidikan di Indonesia Tahun 2023 menggunakan Analisis Cluster Nurfajriyani Nurfajriyani; Dentina Dewi Amaliana; Sri Pingit Wulandari
Pentagon : Jurnal Matematika dan Ilmu Pengetahuan Alam Vol. 2 No. 4 (2024): Desember: Pentagon : Jurnal Matematika dan Ilmu Pengetahuan Alam
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/pentagon.v2i4.309

Abstract

Improving the quality of Human Resources (HR) is a major challenge in facing global competition. Education as the main means of improving the quality of HR in Indonesia is still faced with the problem of inequality of access and quality between regions. This inequality causes disparities in educational development between urban and remote areas. This study focuses on grouping provinces in Indonesia based on aspects of educational development in 2023, using cluster analysis. Secondary data from the Central Statistics Agency (BPS) is used as the basis for analysis, including variables of average length of schooling, Gross Participation Rate (APK), Pure Participation Rate (APM), number of senior high schools, and community literacy development index. This study uses hierarchical and non-hierarchical cluster analysis methods to group provinces in Indonesia. The results of the hierarchical cluster analysis using the average linkage method show the most optimal cluster with the formation of three clusters. The first cluster consists of 31 provinces, the second cluster consists of 2 provinces, and the third cluster consists of 1 province. Data characteristics show large variations in the number of senior high schools and relative homogeneity in the average length of schooling between provinces.
Analisis Faktor Pembangunan Berkelanjutan Di Provinsi Sumatera Utara Tahun 2023 Menggunakan Metode Analisis Faktor Anjani Lestari Hartanty; Ovi Wahyu Adriani; Sri Pingit Wulandari
ARIMA : Jurnal Sosial Dan Humaniora Vol. 2 No. 2 (2024): November
Publisher : Publikasi Inspirasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62017/arima.v2i2.2654

Abstract

Konsep pembangunan berkelanjutan berkembang seiring pengingkatan populasi dari generasi ke generasi sampai sekarang, mendorong manusia untuk mengevaluasi perannya dalam berfokus pada tiga pilar yaitu lingkungan, sosial dan ekonomi serta melanjutkan aktivitas tanpa mengurangi sumber daya. Beragamnya dugaan dari berbagai pilar lingkungan, sosial, dan ekonomi, maka penelitian ini menggunakan analisis faktor untuk mengetahui faktor-faktor utama yang berkontribusi terhadap pembangunan berkelanjutan di Provinsi Sumatera Utara tahun 2023. Faktor yang diduga memengaruhi pembangunan berkelanjutan atau varaibel prediktor pada penelitian ini yaitu TPAK, akses sanitasi layak, RLS, laju pertumbuhan penduduk, UHH. Didapatkan data memiliki keragaman yang kecil dan disertai persebaran yang tidak merata, berdistribusi normal multivariat analisis faktor menyatakan bahwa terbentuk 2 komponen utama penyusun faktor pembangunan berkelanjutan Provinsi Sumatera tahun 2023, komponen yang terbentuk terdiri dari faktor ketenagakerjaan dan sosial demografis yang memiliki kemampuan menjelakan variabilitas dengan baik.
PENGARUH TINGKAT GAJI TERHADAP RATA-RATA JAM KERJA PER BULAN DAN JUMLAH PROYEK YANG DIKERJAKAN MENGGUNAKAN ANALISIS MANOVA Nur Fitri Mustika Ayu; Feny Ulil Amrina; Sri Pingit Wulandari
ARIMA : Jurnal Sosial Dan Humaniora Vol. 2 No. 2 (2024): November
Publisher : Publikasi Inspirasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62017/arima.v2i2.2700

Abstract

Pada lingkungan kerja yang semakin kompetitif, perusahaan menghadapi tantangan dalam menetapkan tingkat gaji yang tidak hanya mampu menarik karyawan tetapi juga meningkatkan kinerja mereka. Penelitian sebelumnya menunjukkan bahwa tingkat gaji berkorelasi dengan beberapa indikator kinerja, seperti rata-rata jam kerja per bulan dan jumlah proyek yang diselesaikan. Hubungan antara tingkat gaji, rata-rata jam kerja per bulan, dan jumlah proyek yang diselesaikan adalah kompleks, karena faktor-faktor seperti beban kerja, kompleksitas proyek, dan tuntutan manajemen ikut mempengaruhi. Untuk menganalisis hubungan ini secara komprehensif, diperlukan metode statistik yang dapat menangani lebih dari satu variabel dependen. Dalam konteks praktikum ini, analisis MANOVA akan dilakukan untuk menjawab pertanyaan mengenai pengaruh signifikan tingkat gaji terhadap rata-rata jam kerja per bulan dan jumlah proyek yang dikerjakan. Hasil dari praktikum ini menunjukkan pada karakteristik data rata-rata jam kerja per bulan dan karakteristik data jumlah proyek yang dikerjakan secara keseluruhan pada tingkat gaji 3 memiliki nilai rata-rata dan variasi yang paling kecil. Hasil pengujian asumsi pada data telah memenuhi asumsi distribusi normal multivariat, merupakan data yang dependen, dan memenuhi asumsi homogenitas varians. Hasil analisis uji MANOVA menunjukkan bahwa tingkat gaji tidak memberikan pengaruh signifikan terhadap rata-rata jam kerja per bulan dan jumlah proyek yang dikerjakan. Pada hasil evaluasi pengelompokkan menunjukkan bahwa tingkat gaji medium memberikan pengaruh yang paling besar terhadap rata-rata jam kerja per bulan dan jumlah proyek yang dikerjakan.
Analisis Faktor dan Komponen Utama yang Mempengaruhi Kesejahteraan Masyarakat Provinsi Jawa Timur Tahun 2023 Damayanti Zulvita Aisyah; Khurotaayun Subagja; Sri Pingit Wulandari
Gudang Jurnal Multidisiplin Ilmu Vol. 2 No. 12 (2024): GJMI - DESEMBER
Publisher : PT. Gudang Pustaka Cendekia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/gjmi.v2i12.1140

Abstract

Tingkat kesejahteraan masyarakat dapat menggambarkan sebuah kebahagiaan dan kualitas hidup rakyat. Akan tetapi, terjadinya ketimpangan tingkat kesejahteraan pada masing-masing provinsi dibuktikan dengan perbedaan nilai indeks pengembangan manusia pada masing-masing provinsi di Indonesia. Pemilihan subjek penelitian di Provinsi Jawa Timur disebabkan karena Provinsi Jawa Timur memiliki sumber daya yang baik yang dapat mendorong potensi pertumbuhan ekonomi dan sektor lainnya, sehingga dapat meningkatkan tingkat kesejahteraan masyarakat di Provinsi Jawa Timur. Penelitian ini bertujuan untuk mengetahui karakteristik data faktor-faktor yang diduga memengaruhi kesejahteraan masyarakat di Provinsi Jawa Timur tahun 2023. Adapun hasil dari penelitian ini adalah pada karakteristik data variabel AHH, IPM, persentase penduduk berpendidikan, persentase penerima KKS, dan jumlah tenaga kesehatan memiliki boxplot yang tidak simetris, sedangkan pada variabel persentase penduduk miskin memiliki boxplot yang simetris. Selain itu, terdapat outlier pada variabel persentase penduduk miskin terdapat pada Kabupaten Sampang, pada variabel persentase penduduk berpendidikan terdapat pada Kota Malang dan Kota Surabaya. Serta pada variabel jumlah tenaga kesehatan terdapat pada Kabupaten Sidioarjo dan Kota Surabaya. Pada pengujian asumsi menunjukkan bahwa data faktor-faktor yang diduga memengaruhi kesejahteraan masyarakat di Provinsi Jawa Timur tahun 2023 memenuhi asumsi. Pada analisis faktor terbentuk menjadi dua komponen. Komponen pertama mampu menjelaskan sebagan besar variabilitas data. Pada komponen pertama terdiri dari variabel AHH, persentase penduduk miskin, IPM, dan persentase pengeluaran makanan. Komponen kedua terdiri dari variabel persentase penduduk berpendidikan, persentase penerima KKS, dan jumlah tenaga kesehatan. Faktor pertama diberi nama kemiskinan dan kerentanan sosial dan pada faktor kedua akses terhadap layanan dasar. Serta, korelasi yang tinggi pada komponen pertama menunjukkan bahwa faktor ini layak untuk merangkum ketujuh variabel yang dianalisis. Kata Kunci: Analisis Komponen Utama, Analisis Faktor, Kesejahteraan Masyarakat
Pengelompokkan Faktor yang Memengaruhi Kemiskinan di Jawa Timur Tahun 2023 Menggunakan Analisis Cluster Abghaza Bayu Kusuma Wardhana; Rakha Maheswara; Sri Pingit Wulandari
Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa Vol. 2 No. 6 (2024): Algoritma : Jurnal Matematika, Ilmu pengetahuan Alam, Kebumian dan Angkasa
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/algoritma.v2i6.304

Abstract

Poverty means the inability to fulfill the basic needs of family members, both food and non-food. In this study, we will analyze several indicators that are assumed to be factors that influence poverty in East Java in 2023, including East Java in 2023, including the percentage of poor people, life expectancy, average years of schooling, and unemployment rate. life expectancy, average years of schooling, and open unemployment rate using cluster analysis to group kabupatens. cluster analysis to group districts/cities into clusters based on the factors that influence poverty. factors that influence poverty. The data used is secondary data obtained through the Central Bureau of Statistics (BPS) website as much as 38 data. Then the data obtained were analyzed for data characteristics, multivariate normal distribution assumption test, independent assumption test, and cluster analysis. assumption test, multivariate normal distribution, independent assumption test, cluster analysis hierarchical, and non-hierarchical cluster analysis, and selection of the best method to determine the optimum cluster. optimum cluster. So that the results obtained data characteristics tend not to be equal, fulfill the multivariate normal distribution assumption test, dependent data. At Hierarchical clustering results obtained the grouping of districts/cities in East Java based on the factors that influence poverty into 5 based on factors that influence poverty into 5 clusters, with 7 districts/municipalities in cluster 1, 16 districts/municipalities in cluster 2, 10 districts/municipalities in cluster 3, 4 districts/municipalities in cluster 4. districts/municipalities in cluster 3, 4 districts/municipalities in cluster 4, and 1 district/municipality in cluster 5. Based on these results, differences in characteristics between clusters indicates that there are significant variations in poverty factors in each region. The results of the non-hierarchical clustering resulted in the grouping of districts/municipalities in East Java based on the factors affecting poverty into 2 clusters, with 13 clusters. factors that influence poverty as many as 2 clusters, with 13 cluster 1, 25 districts/cities in cluster 2. Also, the results of the ANOVA test results obtained the results of all variables of the factors that influencing poverty in districts/municipalities in East Java Province significantly on poverty.
Analisis Faktor yang Mempengaruhi Kemiskinan Provinsi Jawa Timur Tahun 2023 dengan Metode Principal Component Analysis Bintang Amirul Mukminin; Muhammad Hasan Alwi Abu Sifa; Sri Pingit Wulandari
Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 2 No. 4 (2024): Desember: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v2i4.494

Abstract

Poverty is one of the main issues in Indonesia although many policies have been implemented by the government to overcome this problem. With this problem, a study was conducted which aims to identify factors that affect poverty in East Java in 2023 using the principal component analysis (PCA) method. PCA is a multivariate analysis technique used to extract information from correlated data, so as to summarize several variables into principal components. In this study, the variables used include the number of poor people, percentage of poor people, poverty severity index, open unemployment rate, labor force participation rate, and life expectancy from 38 districts/cities in East Java. It was found that the data characteristics had low variance with the exception of one variable, and met the assumptions of multivariate normal distribution, interrelationship between variables, data sufficiency, and correlation between variables suitable for PCA. Factor analysis with PCA produces two main components, namely community living conditions and labor conditions, which can represent the original variables in their influence on poverty in East Java. Suggestions from this study are expected to be a reference for policy makers in improving community welfare and labor conditions in East Java. Future research is expected to add related variables to obtain more detailed results.
Analisis Faktor Tingkat Perkembangan Demokrasi di Indonesia Menurut Provinsi Tahun 2023 Siti Nabila; Latifah Sekar Hanin; Sri Pingit Wulandari
Jurnal Pustaka Cendekia Pendidikan Vol. 2 No. 3 (2025): Jurnal Pustaka Cendekia Pendidikan, Volume 2 Nomor 3, Januari - April 2025
Publisher : PT PUSTAKA CENDEKIA GROUP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70292/jpcp.v2i3.82

Abstract

Democracy is an important benchmark for assessing the progress of a country, especially in relation to the absence of social, economic, and political development. In Indonesia, variations in the level of democracy between regions reflect the influence of diverse social and economic aspects. The study of democracy in 2023 is very relevant in efforts to strengthen empowered communities and responsive governance. A comprehensive approach is needed to measure the level of democracy at the provincial level, with related variables such as community literacy index, open poverty rate, freedom, equality, and institutional capacity. This study uses principal component analysis (PCA) and factor analysis to identify the main components and spread the relationship between variables. The KMO test, Bartlett's test, and multivariate normality test were conducted to ensure the feasibility of the data. The results of the analysis show that the data meets the assumption of multivariate normal distribution as well as the criteria for independence and correlation between variables. Based on PCA, it was found that two main components were able to explain the variability of the data. The first component, namely social capacity building, includes four variables: literacy index, freedom, equality, and institutional capacity. The second component includes employment conditions as measured by the open poverty rate.
PENGARUH TINGKAT MOTIVASI SISWA TERHADAP JAM TIDUR DAN NILAI UJIAN MENGGUNAKAN METODE MANOVA Amelia Kurnia Fitri; Hanni Putria Hartanti; Sri Pingit Wulandari
Integrative Perspectives of Social and Science Journal Vol. 1 No. 02 November (2024): Integrative Perspectives of Social and Science Journal
Publisher : PT Wahana Global Education

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Background: High motivation encourages students to study harder but often reduces their sleep duration, which can negatively impact their concentration and exam performance. Conversely, students with low motivation may have more regular sleep patterns but are less focused on academic activities, which affects their performance. Purpose: This study aims to examine the influence of students' motivation levels on their sleep duration and exam scores using MANOVA analysis. MANOVA (Multivariate Analysis of Variance) is a statistical technique used to simultaneously test the significance of mean differences among groups for two or more dependent variables. Methods: The study involves several analytical steps, including testing the multivariate normal distribution assumption, Bartlett’s test (independence) to assess the homogeneity of variance-covariance, simultaneous testing to identify differences among categories of student motivation levels, multiple comparison testing using LSD (Least Significant Difference) to determine specific categories with differences, and evaluating the grouping results to identify the most significant influence of motivation levels on sleep duration and exam scores. Results: The analysis revealed that most students have moderate motivation levels. In the MANOVA assumption test, the data showed a normal distribution among dependent variables, but the assumption of homogeneity of variance was not met. The analysis indicated that high motivation levels had the most significant influence, whereas moderate and low motivation levels did not have a significant impact on students’ sleep duration and exam scores. Conclusion: Multiple comparison testing with LSD revealed that the average sleep duration was similar across low, moderate, and high motivation levels. However, there were differences in the average exam scores among students with low, moderate, and high motivation levels.  
Analisis Faktor-Faktor Tingkat Inflasi Di Indonesia Tahun 2022-2023 Menggunakan Analisis Faktor Rifda Maulidya; Shafa Fariha Tsuraya; Sri Pingit Wulandari
Gudang Jurnal Multidisiplin Ilmu Vol. 2 No. 11 (2024): GJMI - NOVEMBER
Publisher : PT. Gudang Pustaka Cendekia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/gjmi.v2i11.1087

Abstract

Inflasi merupakan tantangan besar bagi perekonomian Indonesia karena dampaknya yang signifikan terhadap daya beli masyarakat, stabilitas harga dan kesejahteraan ekonomi, terutama di negara berkembang. Ketidakstabilan inflasi seperti lonjakan dari 1,87% pada 2021 menjadi 5,51% pada 2022, meskipun sempat turun pada 2023, menunjukkan perlunya identifikasi faktor-faktor penyebab inflasi. Inflasi yang tinggi dapat memicu kenaikan harga barang dan jasa, kemiskinan dan menekan stabilitas ekonomi. Oleh karena itu, perlu dilakukan analisis terhadap faktor-faktor yang memengaruhi tingkat inflasi di Indonesia tahun 2022-2023 menggunakan metode analisis faktor. Hasil analisis menunjukkan karakteristik data faktor-faktor yang memengaruhi tingkat inflasi di Indonesia tahun 2022-2023 memiliki keragaman data yang besar. Adapun hasil pemeriksaan dan pengujian asumsi menunjukkan bahwa data berdistribusi normal multivariat, antar variabel dependen, kecukupan data terpenuhi dan terdapat korelasi antar variabel. Berdasarkan hasil analisis faktor terbentuk 2 faktor yang memengaruhi tingkat inflasi. Faktor pertama adalah kebijakan moneter dan perdagangan global yang meliputi BI Rate, nilai neraca perdagangan dan harga minyak mentah. Faktor kedua adalah stabilitas ekonomi dan pasar modal yang meliputi nilai ekspor, tingkat inflasi harga konsumen (TIHK) dan indeks harga saham gabungan (IHSG).
Co-Authors Abghaza Bayu Kusuma Wardhana Aisyatul Kamilah Ramadina Albertus Eka Amelia Kurnia Fitri Amelya Putri, Veronica Ammaar Razaan Yahya Anindya Putri Noliza Anjani Lestari Hartanty Annisa’ Riskika Hayyu Arindah Maharani Saputri Arsa Saladine Arum Antika Bintang Amirul Mukminin Brodjol Sutijo Byrlianty Tsabita El Haqq Damayanti Zulvita Aisyah Daniel Wicaksono Nugroho Dentina Dewi Amaliana Elsa Amelia Nur Arimba Endita Prastyansyach Famita Wibi Wulandari Farhan Bramhatchi Fauzi Dwi Aryasatyawan Feny Ulil Amrina Hanni Putria Hartanti Helvy Tiana Rosa Nabila Hikmah Deviani Ika Rahmawati Insania Firdausy Khurotaayun Subagja Latifah Sekar Hanin Marcella Pramesti Putri Maziyah Mufidah Wahyudiono Melita Handayani Melynda Isaura Monica Putri Natalia Muhammad Hasan Alwi Abu Sifa Naomi Gloria Pasaribu Natasya Liana Putri Naufalia Alfi Fuadah Nisrina Aulia Salsabila Nur Fitri Mustika Ayu Nurfajriyani Nurfajriyani Ovi Wahyu Adriani Purhadi Purhadi Puspa Damai Kukuh Hati Putri Buana, Avinda Lutfi Anggraini Putri Dita Prameswari Rakha Maheswara Rida Dwi Lestari Rifda Maulidya Rindy Retno Prihastari Riska Aisyah Widyaningsari Salsabila Aulia Azizah Sa’diyyah Divamia Amanda Shafa Fariha Tsuraya Siti Nabila Sri Mumpuni Retnaningsih Syefa Ilmi Beandita Putri Vira Angelina Virda Wulandari Zahra Afifah Nafisah _ Haryono