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ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PENYERAPAN TENAGA KERJA PADA SEKTOR PERHOTELAN DI PROVINSI MALUKU DENGAN MENGGUNAKAN METODE REGRESI DATA PANEL Muhammad Yahya Matdoan; Mozart W Talakua
Jurnal Matematika Sains dan Teknologi Vol. 22 No. 2 (2021)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v22i2.1572.2021

Abstract

The hotel sector is one of the sectors that has made a major contribution to employment and economic development in Maluku Province. The more the population, the more difficult it is to find work. The purpose of this study is to analyze the effect of the variable number of accommodation, number of occupancy, number of available beds and minimum wage of employees on labor absorption in the hotel sector in Maluku Province. One method that can be used to solve this problem is the Panel Data Regression method. Panel data regression is a combination of time series data and cross section data. This method can be used to determine the relationship between two or more variables that are quantitative in nature, so that one variable can be predicted from the other variables. The Panel Data Regression model used in this study is the Fixed Effect Model (FEM) with the results obtained, namely that there are three variables that affect labor absorption in the hotel sector in Maluku Province, namely the number of accommodation, the number of occupancy and the minimum wage of employees. Meanwhile, the number of available beds has no effect on labor absorption in the hotel sector in Maluku Province.
Pemodelan Spatial Error Model (SEM) Untuk Mengidentifikasi Indeks Pembangunan Manusia di Provinsi Maluku Tahun 2016 Fauzan Samallo; Yopi Andry Lesnussa; Abraham Z. Wattimena; Muhammad Yahya Matdoan
Jurnal Matematika Vol 8 No 1 (2018)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2018.v08.i01.p99

Abstract

Human Development Index (HDI) is a quality measure that can be used to determine the quality of human development that has been achieved. HDI is a composite index that composed of 3 components, such as: Length of life measured by life expectancy at birth, Education measured by average school duration and expectations school duration and standard of living measured by Purchasing Power Parity (PPP) in rupiah. The model used in this research is Spatial Error Model (SEM) to identify Influence of Variables X on IPM value and pattern of HDI distribution in a region with Ordinary Linear Square (OLS) parameter estimates. From the map thematic data that obtained, it can be seen that the pattern of the spread of Human Development Index (HDI) in Maluku Province has no effect on the distance of a region. There is a correlation between the components of HDI compilers to the HDI value in Maluku Province, because there is a spatial dependency on the dependent variable. Lambda value coefficient which is negative and significant at ? = 10% indicates that there is no correlation of HDI value in a region with other adjacent area. Also indicated by spatial residuals in adjacent areas do not have the same characteristics.
Pelatihan Aplikasi SPSS untuk Pemecahan Masalah Perhitungan pada Statistika Deskriptif di SMA Negeri 1 Maluku Tengah Muhammad Yahya Matdoan; Muhidin Jariyah; Irfandy Walli
Mitra Mahajana: Jurnal Pengabdian Masyarakat Vol. 2 No. 2 (2021): Volume 2 Nomor 2 Tahun 2021
Publisher : LPPM Universitas Flores

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37478/mahajana.v2i2.897

Abstract

Statistics is a very difficult material, especially in the process of calculating and analyzing data which tends to be complicated because it requires accuracy and accuracy in its calculations. However, along with the rapid advancement in technology, various computer applications that are specifically designed to help calculate statistical data have emerged, one of which is SPSS. The method of activities held in community service (PKM) is in the form of SPSS training. Participants in this activity were students of SMA Negeri 1 Maluku Tengah. The conclusion obtained in this service is the results of the evaluation given at the end of the activity, of the 28 training participants, all students who took part in the training were able to complete the assigned tasks very well. In addition, teachers must equip students with programming skills, especially statistical and mathematical applications, so that they can arouse students' enthusiasm and interest in learning mathematics and statistics. The necessary follow-up is that it is necessary to carry out further training to hone the interests and abilities of teachers more deeply.
PEMODELAN REGRESI QUANTIL DENGAN KERNEL SMOOTHING PADA FAKTOR-FAKTOR YANG MEMPENGARUHI PENYEBARAN API MALARIA DI INDONESIA: (Quantile Regression Modeling with Kernel Smoothing on Factors Affecting the Spread of Malaria Fire in Indonesia) Muhammad Yahya Matdoan; Mozart Wiston Talakua; Ronald John Djami
Uniqbu Journal of Exact Sciences Vol. 1 No. 2 (2020): Uniqbu Journal of Exact Sciences (UJES)
Publisher : LPPM UNIQBU

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (983.769 KB) | DOI: 10.47323/ujes.v1i2.24

Abstract

Regression analysis method is one of the statistical methods used to describe the relationship between two or more variables, so that a variable can be predicted from another variable. In regression analysis there are two types of approaches, namely parametric and nonparametric approaches. Estimates used to estimate the parameters in the regression analysis using the OLS method. This method is based on the mean distribution, so it is not appropriate to analyze a number of data that are not symmetrical or contain outliers. Therefore, a quantile regression method and kernel smoothing were developed that were not affected by data containing outliers and could also be used as an alternative to solving fluctuating data problems. This study uses quantile regression with kernel smoothing in the case of factors affecting malaria in Indonesia. The results show that the main factors causing the spread of malaria in Indonesia are access to proper sanitation, household factors that behave in a clean and healthy life, and the number of puskesmas and the percentage of medical personnel.  
Structural Equation Modeling (SEM) untuk Mengukur Pengaruh Pelayanan, Harga, dan Keselamatan terhadap Tingkat Kepuasan Pengguna Jasa Angkutan Umum Selama Pandemi Covid-19 di Kota Ambon Zakheus Putlely; Yopi Andry Lesnussa; Abraham Z Wattimena; Muhammad Yahya Matdoan
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.45784

Abstract

Structural Equation Modeling (SEM) is a statistical analysis technique used to build and test statistical models in the form of causal models. Large-Scale Social Restrictions (PSBB) are government policies to break the chain of spreading the corona virus (Covid-19). This policy certainly has an impact on drivers of public transport services. This research shows that the passengers are very satisfied with the travel safety factor. Meanwhile, service factors and passenger public transport fares are in the satisfied category. Furthermore, the variable service quality (MP), the price of public transportation (H), and passenger safety (KP) have an influence on passenger satisfaction. Because the t-value is greater than 1.96 (for the real level of 5%). The influence of service quality, price and safety variables on passenger satisfaction is 78.1%, the remaining 21.9% is influenced by other variables outside the research.Keywords: covid-19, structural equation modeling, satisfaction.
Pemanfaatan Microsoft Office Excell untuk Meningkatkan Kapasitas Guru dalam Mewujudkan Program Satu Data Marlon Stivo Noya Van Delsen; Muhammad Yahya Matdoan; Yonlib W. A. Nanlohy
Archive: Jurnal Pengabdian Kepada Masyarakat Vol. 1 No. 1 (2021): Desember 2021
Publisher : Asosiasi Pengelola Publikasi Ilmiah Perguruan Tinggi PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (260.456 KB) | DOI: 10.55506/arch.v1i1.11

Abstract

Data merupakan informasi yang sangat penting dalam memanage suatu instansi, baik instansi pemerintah maupun swasta. Sekolah sebagai salah satu instansi pemerintah yang bergerak di bidang pendidikan juga memerlukan manajemen data yang sangat baik. Manajemen data yang baik mempermudah untuk proses pengolahan data. SMA Negeri 6 Maluku Tengah merupakan salah SMA Negeri yang ada pada Kabupaten Maluku Tengah di Provinsi Maluku. Namun SMA Negeri 6 terletak berbeda pulau dengan Ibu Kota Kabupaten Maluku Tengah. Pengabdian ini diperoleh hasil bahwa Para guru mampu memahami dan memanfaatkan berbagai formula pada Microsoft Office Excell sehingga mampu membuat daftar nilai rapot siswa otomatis menggunakan Microsoft Office Excell. Para guru mampu memahami dan memanfaatkan berbagai formula pada Microsoft Office Excell sehingga mampu membuat manajemen data pegawai dan guru menggunakan Microsoft Office Excell.
Klasifikasi Hasil Seleksi Kompotensi Dasar CPNS Menggunakan Metode Decision Tree Ravensky T. Silangen; Muhammad Yahya Matdoan
Inferensi Vol 5, No 2 (2022)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v5i2.12353

Abstract

Civil Servants (PNS) are one of the jobs that are of interest to various groups of people in Indonesia. The need for qualified and competitive human resources in this era of globalization requires the government to be more serious in recruiting prospective civil servants so that the realization of good service and organizational needs for existing position qualifications can be met. The implementation of the 2021 civil servant candidate selection at Pattimura University is carried out based on the regulations of the State Civil Service Agency with several stages of selection, one of which is the Basic Competence Selection with a predetermined value standard. This study aims to classify the test results of Candidates for Civil Servants at Pattimura University. The data used in this study is secondary data obtained from the State Civil Service Agency in 2021. The method used in this study is the Decision Tree method. The results show that there are 4 classes (classification) with an Accuracy value of 75%, Classification Error of 25%, Kappa of 0.947, Recall of 97.14%, and Precision of 93.94%.
Penerapan Metode K-Nearest Neighbor untuk Mengklasifikasi Penyebaran Kasus Demam Berdarah Dengue (DBD) di Kabupaten Maluku Tenggara Muhammad Yahya Matdoan
Square : Journal of Mathematics and Mathematics Education Vol 4, No 2 (2022)
Publisher : UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/square.2022.4.2.13056

Abstract

Demam Berdarah Dengue (DBD) merupakan penyakit yang disebabkan oleh virus dengue yang ditularkan melalui gigitan nyamuk Aedes Aegypti dan masuk ke peredaran darah manusia. Penyakit ini merupakan penyakit berbahaya yang sering menimbulkan kekhawatiran masyarakat karena perjalanan penyakitnya cepat dan dapat meyebabkan kematian dalam waktu singkat. Oleh karena itu, perlu dilakukan kajian tentang penyebarannya sehingga dapat diambil tindakan cepat dalam mencegah kasus tersebut, Salah satu metode yang dapat digunakan yaitu metode K-Nearest Neighbor (KNN). K-NN merupakan suatu bentuk model pendukung keputusan yang dapat megklasifikasikan data berdasarkan jarak terdekat. Data yang digunakan dalam penelitian ini bersumber dari BPS Kabupaten Maluku Tenggara tahun 2021. Penelitian ini diperoleh hasil bahwa terdapat 2 kelompok penyebaran DBD di Kabupaten Maluku Tenggara yaitu Kecamatan yang berpotensi DBD tinggi yaitu terdiri dari Kecamatan Kei Besar, Kecamatan Kei Kecil dan Kecamatan Kei Besar Selatan Barat. Selanjutnya kecamatan yang berpotensi penyebaran DBD rendah yaitu Kecamatan Kei Besar Utara Barat, Kecamatan Kei Besar Selatan, Kecamatan Kei Besar Timur Selatan, Kecamatan Kei Besar Utara Timur, Kecamatan Hoat Sorbay, Kecamatan Kei Kecil Barat, Kecamatan Kei Kecil Timur dan Kecamatan Manyeuw.Kata Kunci: Demam Berdarah Dengue, K-Nearest Neighbor, Maluku Tenggara.
PENDEKATAN GEOGRAPHICALLY WEIGHTED POISSON REGRESSION DENGAN PEMBOBOT FUNGSI KERNEL GAUSS UNTUK MENGANALISIS JUMLAH KEMATIAN BAYI DI PROVINSI MALUKU Salmon Notje Aulele; Norisca Lewaherilla; Muhammad Yahya Matdoan
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 14 No 2 (2022): Journal of Statistical Application and Computational Statistics
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v14i2.371

Abstract

Pembangunan kesehatan pada hakekatnya merupakan penyelenggaraan upaya kesehatan untuk mencapai kemampuan hidup sehat secara mandiri dengan upaya peningkatan derajat kesehatan masyarakat yang optimal, peningkatan sumber daya manusia dan pemerataan jangkauan pelayanan kesehatan. Analisis regresi merupakan analisis statistik yang bertujuan untuk memodelkan hubungan antara variabel respon dengan variabel prediktor. Model Geographically Weighted Poisson Regression (GWPR) adalah bentuk lokal dari regresi Poisson dimana lokasi diperhatikan yang berasumsi bahwa data berdistribusi Poisson. Model GWPR ini banyak dipakai oleh peneliti dalam menganalisa data spasial diberbagai bidang. Tujuan dalam penelitian ini adalah menentukan faktor-faktor yang signifikan mempengaruhi jumlah kematian bayi di Provinsi Maluku dengan menggunakan model GWPR dengan pembobot Fungsi Kernel Gauss. Hasil penelitian menunjukan bahwa Rata-rata jumlah kematian bayi di Provinsi Maluku pada tahun 2019 adalah sebesar 32 bayi. Jumlah kematian bayi tertinggi berada pada Kabupaten Maluku Tengah yaitu sebesar 59 bayi, sedangkan untuk Kabupaten/Kota yang memiliki jumlah kematian bayi terendah adalah Kota Tual sebesar 15 bayi. Hasil pemetaan Kabupaten/Kota berdasarkan faktor-faktor yang signifikan mempengaruhi jumlah kematian bayi adalah Persentase Pemberian ASI Ekslusif Pada Bayi (5 Kab/Kota), Jumlah Tenaga Kesehatan (10 Kab/Kota), Jumlah Sarana Kesehatan (11 Kab/Kota), Persentase Bayi Berat Badan Lahir Rendah (10 Kab/Kota), dan Persentase Cakupan Imunisasi TT2 Pada Ibu Hamil (9 Kab/Kota). Hasil penelitian ini diharapkan dapat menjadi acuan bagi Pemerintah Pusat maupun Daerah dalam mengambil kebijakan untuk menurunkan jumlah kematian bayi di Provinsi Maluku.
Application of the K-Means Cluster for the Classification of Disadvantaged Districts/Cities in Maluku Province Muhammad Yahya Matdoan; Faraniena Yunaeni Risdiana; Gabriella Haumahu
JRST (Jurnal Riset Sains dan Teknologi) Volume 6 No. 1 Maret 2022: JRST
Publisher : Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (756.5 KB) | DOI: 10.30595/jrst.v6i1.11637

Abstract

Maluku Province is still the 4th poorest province in Indonesia. This is due to the disparity in development between the provincial and district centers, cities and villages as well as government work programs that are not implemented evenly. To overcome and evaluate these problems, it is necessary to plan or study the classification of underdeveloped regions, namely by grouping districts/cities based on indicators of nderdeveloped areas. This research was conducted using secondary data obtained from the Central Statistics Agency (BPS) of Maluku Province. The method used in this study is to use the K-Means Cluster analysis method. The results of the study indicate that there are 2 classifications of underdeveloped and undeveloped areas in Maluku Province. Cluster 1 consists of Tanimbar Islands Regency, Southeast Maluku Regency, Central Maluku Regency, Buru Regency, Aru Islands Regency, West Seram Regency, Eastern Seram Regency, Southwest Maluku Regency, South Buru Regency and Tual City. In Cluster 2 there is only one area, namely Ambon City.