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All Journal Natural Science: Journal of Science and Technology JURNAL ILMIAH MATEMATIKA DAN TERAPAN Journal of Data Analysis BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Varian Inferensi DedikasiMU: Journal of Community Service Parameter: Journal of Statistics Indonesian Journal of Statistics and Its Applications
Mohammad Fajri
Department Of Statistics, Faculty Of Mathematics And Natural Sciences, Tadulako University, Indonesia
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PEMODELAN IPM DI KAWASAN TIMUR INDONESIA MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) Insany, Annisa Nur; Nur?eni, Nur?eni; Fajri, Mohammad
Natural Science: Journal of Science and Technology Vol 8, No 2 (2019): Volume 8 Number 2 (August 2019)
Publisher : Univ. Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (779.729 KB)

Abstract

Human Development Index (HDI) is an important issue in designing  and strategizing of sustainable development. Multivariate Adaptive Regression Spline (MARS) is a regression approach that produces models with continous character on knots. MARS models are determined based on trial and error for a combination of basis function (BF), maximum interaction (MI), and minimum observation (MO). The determination of knots is based on the minimum Generalized Cross Validation (GCV) value. The results of this study are the combination value of BF = 52, MI = 3, and MO = 2 with a minimum GCV of 0,00049. The factors that influence HDI are average school length (X2) per capita expenditure (X4), life expactancy (X3), persentage of poor woman aged 15-49 who use the birth control tool (X5).
Analisis Sensitivitas Model Regresi Linier Berganda Menggunakan Pendekatan Bayesian (Distribusi Prior Normal) Junaidi Junaidi; Mohammad Fajri; Yandi Ristawan
Journal of Data Analysis Volume 3, Number 1, June 2020
Publisher : Department of Statistics, Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jda.v3i1.18358

Abstract

Metode regresi linier berganda merupakan metode yang memodelkan hubungan antara peubah respon (y) dan beberapa peubah predictor (x). Pada metode Bayesian parameter yang digunakan merupakan variabel random yang dilkukan dengan mengalikan Likelihood dengan distribusi prior. Distribusi prior adalah distribusi subyektif berdasarkan pada keyakinan seseorang dan dirumuskan sebelum data sampel diambil. Tujuan penelitian ini adalah  untuk menganalisis sensitivitas dari parameter-paremeter pada model regresi linier berganda yang akan dilakukan dengan menggunakan prior berdistribusi Normal. Selanjutnya, penerapan model pada data aset bank di Indonesia dengan hasil estimasi parameter yaitu , , , , , dan , dengan selang kepercayaan 95%  untuk setiap parameter yang dihasilkan yaitu==       (-1,427 ; 3,594),  =(-5,07;0,3061), =(, , dan  = (-0,5955 ; 2,487). Nilai estimasi parameter yang diperoleh dengan pendekatan Bayesian mendekati nilai parameter yang diperoleh dengan Frequantis. Selang kepercayaan yang diperoleh juga mendekati dengan hasil frequentis yang memiliki interval lebih sempit dibandingkan nilai interval dengan metode OLS. Hal ini menunjukkan bahwa metode Bayesian merupakan suatu pendekatan yang dapat digunakan untuk mengestimasi parameter pada analisis regresi linier berganda. The multiple linear regression method is a method that models the relationship between the response variable (y) and several predictor variables (x). In the Bayesian method, the parameters used are random variables which are conducted by multiplying the likelihood with the prior distribution. The prior distribution is a subjective distribution based on a person's beliefs and is formulated before the sample data is taken. The purpose of this study is to analyze the sensitivity of the parameters in the multiple linear regression model that will be carried out using prior normal distribution. Furthermore, the application of the model to the data on bank assets in Indonesia with the results of parameter estimation is β0 = 23.06, β1 = 1.05, β2 = -2,379, β3 = -0,4786, β4 = -0.03796, and β5 = 0.9075, with a 95% confidence interval for each resulting parameter, namely β0 = (6,052; 40,200), β1 = (-1,427; 3,594), β2 = (- 5.07; 0, 3061), β3 = (0.9896; 0.03289), β4 = (- 1,224; 1.139), and β5 = (-0.5955; 2.487). The parameter estimate value obtained by the Bayesian approach is close to the parameter value obtained by Frequantis. The confidence interval obtained is also close to the frequentis result which has a narrower interval than the interval value with the OLS method. This shows that the Bayesian method is an approach that can be used to estimate parameters in multiple linear regression analysis.
SOSIALISASI SISTEM WEB UNTUK MENDIAGNOSA HAMA DAN PENYAKIT TANAMAN BAWANG MERAH LOKAL PALU PADA KELOMPOK PETANI BINAAN Junaidi Junaidi; Iman Setiawan; Mohammad Fajri; Hajra Rasmita Ngemba; Nurpati Nurpati
DedikasiMU : Journal of Community Service Vol 5 No 3 (2023): DedikasiMU September
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/dedikasimu.v5i3.6268

Abstract

Sistem guna mendiagnosa gejala awal serangan hama dan penyakit tanaman yang berbasis Web bagi petani bawang merah lokal Palu perlu disosialisasikan. Hal ini dilakukkan agar petani dapat dengan cepat mengetahui jenis hama dan penyakit apa yang menyerang tanaman tersebut. Sehingga hal ini dapat membantu para petani dengan cepat untuk memberikan penanganan dalam mengatasi serangan hama dan penyakit tersebut. Kemudahan dalam mengakses web yang berbasis pengambilan keputusan berdasarkan metode Bayesain dapat membantu para petani sehingga dapat lebih baik, ideal dan bijaksana dalam menentukan aktivitas prioritas yang akan dilakukan guna mendukung produksi tanaman bawang merah lokal Palu. Dengan demikian, tujuan dari kegiatan ini adalah membantu petani bawang merah lokal Palu sebagai mitra guna mengetahui dengan cepat gejala awal serangan hama dan penyakit pada tanaman bawang merah lokal Palu yang berbasis web. Hal ini berdampak pada produksi bawang yang dihasilkan lebih baik dan berkualitas. Adapun kegiatan sosialisasi yang dilakukan adalah dengan pemberian materi, pelatihan system web serta diskusi dengan mitra. Sosialisasi yang telah dilakukan sangat bermanfaat bagi para petani bawang merah untuk mengetahui dengan cepat dan tepat dalam mendeteksi jenis hama dan penyakit yang menyerang bawang merah melalui sistem web. Hal ini terbukti dengan ketercapaian hasil yang ditargetkan oleh tim pengabdi berupa pengaplikasian secara langsung penggunaan sistem web dengan baik. Kegiatan sosialisasi ini sangat menarik karena para petani sangat antusias mengikuti pelatihan web secara mandiri. Melalui kegiatan pengabdian ini, petani dapat memahami konsep dalam menentukan hama dan penyakit serta penanganannya.
Mapping of Village Population Profile with Schistosomiasis Cases Using Clustering Large Applications Mohammad Fajri; Rais Rais; Nurul Fiskia Gamayanti; Siti Natazha Dg Mabaji; Shalsa Yunita Rahman Jati; Rizwan Arisandi
Jurnal Varian Vol 7 No 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v7i2.3423

Abstract

Schistosomiasis is a tropical disease caused by Schistosoma mansoni (intestinal schistosomiasis) and Schistosoma haematobium (urogenital schistosomiasis). Schistosomiasis in Indonesia is endemic to Central Sulawesi and is commonly found in the Napu Valley and Bada Valley areas, which are administratively included in Poso District and Sigi District. One approach to obtain information on schistosomiasis endemic areas is by mapping the population profile of villages with schistosomiasis cases. This mapping is intended to provide an overview of the social and demographic conditions of villages with schistosomiasis cases. One of the many analysis methods that can be used is cluster analysis. Cluster analysis is a method for grouping data based on the extent of their similarities. Data with similar characteristics will be grouped together, while data with different characteristics will be placed in different groups. Among several types of methods in cluster analysis is Clustering Large Application (CLARA). CLARA is a clustering method which is more robust to unusual data and can be applied to handle large volumes of data. The results of this study are obtained two optimum clusters, each possessing distinct characteristics as determined by Schistosomiasis cases indicators. Cluster 1 with low schistosomiasis cases and cluster 2 with high schistosomiasis cases.
Analisis Komparasi Algoritma Clustering Berbasis Partisi Untuk Data Numerik Dan Data Kategorikal Lusiyanti, Desy; Fajri, Iman Al; Andri; Fajri, Mohammad
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 20 No. 2 (2023)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2023.v20.i2.16871

Abstract

Dalam prakteknya, tidak selalu semua fitur data bertipe numerik ataupun bertipe kategorik. Perbedaan fitur pada suatu data menjadi permasalahan dalam menentukan metode yang akan digunakan. Salah satu cara yang sering digunakan untuk mengatasi permasalahan tersebut yaitu mengubah salah-satu dari nilai fitur dengan menyesuaikan metode yang akan digunakan. Misalkan dalam analisis cluster, terdapat beberapa algoritma yang sering digunakan diantaranya adalah K-Means dan K-Modes. Kedua metode ini memiliki perbedaan dari fitur yang digunakan. K-Means menggunakan tipe data numerik sedangkan K-Modes menggunakan tipe data kategorik. Dalam penelitian ini dilakukan komprasi antara metode K-Means dan K-Modes untuk mengclusterkan pasien penyakit jantung. Dataset yang digunakan dalam penelitian ini adalah data rekam medis pasien penyakit jantung RSUD Undata palu. Hasil penelitian menunjukkan bahwa dari kedua metode yang dibandingkaan memiliki tingkat akurasi yang baik, yaitu 84.47% (untuk metode K-Means), dan 83.85% (untuk metode K-Modes).
Biserial Point Correlation to Measure The Relationship Between The Characteristics of Health Workers at Undata Palu Hospital with Antibody Levels Fadjriyani; Mohammad Fajri; Hartayuni Sain; Gamayanti, Nurul Fiskia; Rais
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 21 No. 1 (2024)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2024.v21.i1.17109

Abstract

Correlation analysis is a term in statistics commonly used to study the relationship between variables. The purpose of this analysis technique is to get a pattern of the closeness or strength of the relationship between two variables expressed by the correlation coefficient. The correlation coefficient is a value that indicates whether or not there is a strong linear relationship between two variables. This study aims to find the relationship between the characteristics of health workers at Undata Hospital Palu and antibody levels. The characteristics of health workers are nominal data with two categories while antibody levels are measured using ratio or interval data. This type of data is suitable to be analyzed using point biserial correlation technique. There are several variables of respondent characteristics that influence immune performance, namely gender, presence or absence of comorbidities, smoking habits, health conditions, exercise habits, close contact with patients and vaccine history. The results of the correlation analysis showed that all respondent characteristic variables had a very weak correlation with antibody levels. This is indicated by the correlation coefficient value of each variable of 0.034; 0.062; 0.063; 0.074; 0.020; 0.079 and 0.119. This means that the characteristics of respondents do not really affect the rise and fall of antibody levels. However, vaccine history has the highest correlation coefficient compared to other variables. This indicates that one of the prevention efforts against infectious diseases is the administration of vaccines.
Forecasting Tourist Visits During The Covid-19 Pandemic and MotoGP Events Using The Sarima Method Soraya, Siti; Rahima, Phyta; Primajati, Gilang; Nurhidayati, Maulida; Fajri, Mohammad
Inferensi Vol 7, No 3 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i3.20139

Abstract

The 5.0 era has made the tourism sector one of the measures of the economic welfare of a region, such as in West Nusa Tenggara (NTB). This is proven by the presence of various types of MSMEs and their innovations and the increasing number of tourist visits to NTB from year to year. The condition of the tourism sector certainly has a positive impact on increasing NTB's economic growth and indirectly on optimizing existing infrastructure. However, extraordinary events such as the earthquake in 2018 and the COVID-19 pandemic resulted in the decline of NTB tourism visits. Then tourist visits in NTB increased again with the holding of the MotoGP  Event. The purpose of this study is to forecast the number of tourist visits to NTB. This is very much needed in helping the government to prepare appropriate policies if there is a possibility of a surge in tourist visits in the following years. As well as anticipating if there are other extraordinary events such as earthquakes or global cases. The method used in this study is the Seasonal Autoregressive Integrated Moving Average (SARIMA) Method. The stages in this method are by describing data, preprocessing data, identifying stationary models, estimating models, selecting the best SARIMA model and forecasting with the obtained model to forecasting the next desired period. The results of research that have been conducted state that in 2023 to 2024 the number of tourists visiting NTB continues to increase both domestically and abroad. It is hoped that the results of this research will be able to provide information and contribute knowledge and consideration materials in policy making in the development of NTB government tourism.
PENINGKATAN KOMPETENSI GURU DALAM PENGGUNAAN APLIKASI STATISTIK VISUAL DALAM ANALISIS DATA PENELITIAN DI SDN INPRES 2 TALISE KOTA PALU Gamayanti, Nurul Fiskia; Fajri, Mohammad; Rais, Rais; Yunita, Silva; Margareth, Cecilia
DedikasiMU : Journal of Community Service Vol 7 No 1 (2025): Maret
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/dedikasimu.v7i1.8570

Abstract

Data merupakan bagian yang tidak akan pernah lepas dari sebuah instansi baik instansi pemerintah maupun instansi swasta. Guru sebagai pegawai pemerintahan di tuntut untu terus berkembang dalam dunia pendidikan. Salah satu tugas pokok guru adalah melakukan penelitian yang berkaitan dengan tupoksi guru disekolah. Penelitian dapat dibagi menjadi dua yaitu penelitian kuantitatif maupun kualitatif. Dari kedua jenis penelitiab ini tidak lepas dari yang namanya data, dimana data tersebut perlu di visualisasikan diawal agar dapat menjadi gambaran awal dari data penelitian yang akan dikerjakan. Berdasarkan diskusi awal dengan Kepala Sekolah SDN 2 Talise Kota Palu, beliau menyatakan bahwa sebanyak 40 guru di SDN 2 Talise Kota Palu dari 45 total guru yang ada, masih membutuhkan poin bantuan dalam penggunaan aplikasi dalam melakukan visualisasi data statistik. Oleh sebab itu mereka sangat membutuhkan pelatihan dan pendampingan dalam menggunakan aplikasi visualisasi statistika. Dengan adanya kegiatan pengabdian ini dapat berupaya untuk membantu guru-guru di SDN 2 Talise Kota Palu dalam meningkatkan kompetensi dan keahlian guru dalam menggunakan aplikasi Terlebih lagi hasil yang diharapkan dalam kegiatan pelatihan ini adalah tersedianya draft jurnal yang telah siap untuk disubmit pada jurnal ilmiah nasional maupun internasional yang berkualitas.
Comparison of C4.5 and C5.0 Algorithm Classification Tree Models for Analysis of Factors Affecting Auction: Perbandingan Model Pohon Klasifikasi Algoritma C4.5 dan C5.0 untuk Analisis Faktor yang Mempengaruhi Keberhasilan Lelang Mohammad Fajri; Iut Tri Utami; Muh. Maruf
Indonesian Journal of Statistics and Applications Vol 6 No 1 (2022)
Publisher : Departemen Statistika, IPB University dengan Forum Perguruan Tinggi Statistika (FORSTAT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v6i1p13-22

Abstract

Auction in Indonesia is carried out by the Office of State Assets and Auction Services (KPKNL). Goods auctioned at KPKNL are quite diverse including land, wood, inventory, vehicles, and other goods. However, not all of the items auctioned were sold. Because not a few items have been auctioned but no one has made an offer. The Purpose of this study is to compare two classification methods, C4.5 and C5.0 algorithm and to determine which items were successfully auctioned with those that did not and its factors. The methods that used were comparing the classification tree C4.5 algorithm and C5.0 algorithm with cross validation. From the results of the comparison of the two methods, it was found that the C5.0 Algorithm method was rated better than the C4.5 algorithm in classifying the auction results with an accuracy of 96.43% and 92.86% respectively. In this case, C5.0 has a higher precision than C4.5.
Spline Nonparametric Regression Model for Local Revenue in Central Sulawesi Fajri, Mohammad; Wulansari, Eka Rizky; Anggraeni, Ayu; Annisa, Mufitatul
Parameter: Journal of Statistics Vol. 1 No. 2 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (295.733 KB) | DOI: 10.22487/27765660.2021.v1.i2.15427

Abstract

Local Own-source Revenue (LOR) is all regional revenue that comes from the region's original economic resources. It is very important to identify it by researching and determining the Regional Local Own-source Revenue (LOR) by properly researching and managing the source of revenue so as to provide maximum results. Central Sulawesi Province itself has Local Own-source Revenue (LOR) in the Regional Revenue and Expenditure Budget of the 2018 Budget Year has reached Rp1 trillion. The increase or decrease in growth of local revenue is influenced by the amount and type of tax, levies collected by local governments and the lack of incentives for the management apparatus to carry out tax collection and levies. This study uses spline regression analysis because the data of the Local Own-source Revenue (LOR) in Central Sulawesi in 2018 does not have a pattern so that it fits perfectly with that method. Then after processing the data obtained the results of spline nonparametric regression modeling using the optimal knots point obtained from the minimum GCV value. The best spline nonparametric regression model is written as follow . It can be concluded that in Central Sulawesi in 2018 the lowest Local Own-source Revenue (LOR) value was Banggai Laut Regency with 21,776 billion rupiahs and the highest Local Own-source Revenue (LOR) value was Palu City at 267,402 billion rupiahs.
Co-Authors Andri Annisa, Mufitatul Ayu Anggraeni Desy Lusiyanti Fadjriyani Gamayanti, Nurul Fiskia Hajra Rasmita Ngemba Hartayuni Sain Iman Al Fajri Iman Setiawan Insany, Annisa Nur Iut Triutami Junaidi Junaidi Lilies Handayani Margareth, Cecilia Muh. Maruf Nur?Eni, Nur?Eni Nurhidayati, Maulida Nurpati Nurpati Nurul Fiskia Gamayanti Phyta Rahima Primajati, Gilang Rais Rais Rais Rais Rais Rizwan Arisandi Shalsa Yunita Rahman Jati Siti Natazha Dg Mabaji Siti Soraya Wulansari, Eka Rizky Yandi Ristawan Yunita, Silva