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All Journal Natural Science: Journal of Science and Technology JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI CESS (Journal of Computer Engineering, System and Science) Prosiding Seminar Nasional IPTEK Terapan (SENIT) 2016 Pengembangan Sumber Daya Lokal Berbasis IPTEK JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Varian DedikasiMU: Journal of Community Service KREATIF: Jurnal Pengabdian Masyarakat Nusantara

Rais Rais

Department Of Statistics, Faculty Of Mathematics And Natural Sciences, Tadulako University, Indonesia

Author-ID : 356586

Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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PEMODELAN TIME SERIES DENGAN PROSES ARIMA UNTUK PREDIKSI INDEKS HARGA KONSUMEN (IHK) DI PALU â€“ SULAWESI TENGAH Wigati, Y; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 12 No. 2 (2015)
Publisher : Program Studi Matematika, Universitas Tadulako

PEMODELAN TIME SERIES DENGAN PROSES ARIMA UNTUK PREDIKSI INDEKS HARGA KONSUMEN (IHK) DI PALU â€“ SULAWESI TENGAH

ANALISIS KORESPONDENSI UNTUK MELIHAT POLA HUBUNGAN FAKTOR â€“ FAKTOR ALASAN MAHASISWA TERHADAP PEMILIHAN JURUSAN MATEMATIKA DI FMIPA UNTAD Rahmayani, R; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 1 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

ANALISIS KORESPONDENSI UNTUK MELIHAT POLA HUBUNGANFAKTOR â€“ FAKTOR ALASAN MAHASISWA TERHADAPPEMILIHAN JURUSAN MATEMATIKA DI FMIPA UNTAD

PERBANDINGAN ANTARA METODE CART (CLASSIFICATION AND EGRESSION TREE) DAN REGRESI LOGISTIK (LOGISTIC REGRESSION) DALAM MENGKLASIFIKASIKAN PASIEN PENDERITA DBD (DEMAM BERDARAH DENGUE) Lestawati, R; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 1 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

Classification is one of statistical methods in grouping the data compiled systematically. The classification of an object can be done by two approaches, namely classification methods parametric and non-parametric methods. Non-parametric methods is used in this study is the method of CART to be compared to the classification result of the logistic regression as one of a parametric method. From accuracy classification table of CART method to classify the status of DHF patient into category of severe and non-severe exactly 76.3%, whereas the percentage of truth logistic regression was 76.7%, CART method to classify the status of DHF patient into categories of severe and non-severe exactly 76.3%, CART method yielded 4 significant variables that hepatomegaly, epitaksis, melena and diarrhea as well as the classification is divided into several segmens into a more accurate whereas the logistic regression produces only 1 significant variables that hepatomegaly

APLIKASI REGRESI KUANTIL PADA KASUS DBD DI KOTA PALU SULAWESI TENGAH Idris, N; Rais, Rais; Utami, I T
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 1 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

Palu city is one of the cities with unstable changes of natural conditions. The natural conditions such as the frequency of rainy day, temperature and humidity which are always changeable bring bad impacts and will cause of diseases especially dengue hemorrhagic fever (DBD). Therefore, it needs an action to recognise whether or not the natural condition factor influences the spread of DBD and determines what factors of the natural condition can influence the spread of DBD. This research applied quantile regression in the case of DBD in Palu city. Quantile regression is an analysis technique regarding to the functional relationship between one dependent variable with one or more independent variables which can provide accurate and stable results even though there will be outliers. Based on the result of the research, it is obtained that the natural condition factor affected the spread of DBD. This is because from 3 natural conditions only 11 significant or influential quantiles on the tested data, the quantiles are 0,30; 0,35; 0,40; 0,45; 0,50; 0,55; 0,60; 0,65; 0,70; 0,75 and 0,80. Meanwhile the most influential factor of natural conditions in spreading DBD isÂ the frequency of rainy day because it has positive which means that 1 progress of percentage will increase the quantity of DBD case.

SIMULASI PENANGANAN PENCILAN PADA ANALISIS REGRESI MENGGUNAKAN METODE LEAST MEDIAN SQUARE (LMS) Tusilowati, Tusilowati; Handayani, L; Rais, Rais
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 2 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

The simulation of handling of outliers on regression analysis used the method which was commonly used to predict the parameter in regression analysis, namely Least Median Square (LMS) due to the simple calculation it had. The data with outliers would result in unbiased parameter estimate. Hence, it was necessary to draw up the robust regression to overcome the outliers. The data used were simulation data of the number of data pairs ( X,Y) by 25 and 100 respectively. The result of the simulation was divided into 5 subsets of data cluster of parameter regression prediction by Ordinary Least Square (OLS) and Least Median Square (LMS) methods. The prediction result of the parameter of each method on each subset of data cluster was tested with both method to discover the which better one. Based on the research findings, it was found that The Least Median Square (LMS) method was known better than Ordinary Least Square (OLS) method in predicting the regression parameter on the data which had up to 3% of the percentage of the outlier.

ANALISIS KLASTER PAUTAN LENGKAP UNTUK MENGELOMPOKKAN KABUPATEN/KOTA DI PROVINSI SULAWESI TENGAH BERDASARKAN INDIKATOR KRIMINALITAS Utami, I T; Rais, Rais; Seftiani, W
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 16 No. 1 (2019)
Publisher : Program Studi Matematika, Universitas Tadulako

Criminality is all kinds of actions and deeds which is economically and psychologically harmful. The statistical method could be used to classify the crime is cluster analysis. Cluster analysis is a multivariate method which aims to classify a sample of subjects (or objects) on the basis of a set of measured variables into a number of different groups such that similar subjects are placed in to the same group. The objective of this research is to classify Regency/City in Central Sulawesi Province based on the criminality indicator and to discover the profile of each cluster which had been formed. The results of the study shows that those are two clusters formed: Cluster 1 consists of Buol, Banggai, Morowali, Toli-Toli, Donggala, and Tojo Una-Una Regency; Cluster 2 consists of Regency/Palu City, and Parigi Moutong. The profile of each cluster is: Cluster 1 with low crime rate on average and Cluster 2 with high crime rate on average.Keywords : Cluster Analysis, Complete Linkage, Criminality, Hierarchy Method.

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

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.

MODELING THE IDX30 STOCK INDEX USING STEP FUNCTION INTERVENTION ANALYSIS Rais, Rais; Afriza, Dini Aprilia; Setiawan, Iman; Sain, Hartayuni; Fadjryani, Fadjryani; Junaidi, Junaidi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp2057-2068

The significant decline in the IDX30 stock index occurred due to an intervention, namely the COVID-19 pandemic, which affected market stability and investment decisions. This study aims to model and forecast the IDX30 stock index using intervention analysis with a step function, which is very suitable for capturing long-term external shocks. The methodology used includes the ARIMA (AutoRegressive Integrated Moving Average) model combined with step function intervention analysis to account for structural changes due to external disturbances. The data used is sourced from investing.com, consisting of weekly IDX30 stock index prices from January 2019 to December 2023. The results show that the COVID-19 pandemic significantly impacted the IDX30 index, causing a drastic decline. The best model identified is ARIMA (1,2,1) with intervention parameters b = 0, s = 0, and r = 1. The forecasting results range from Rp. 488 to Rp. 505, with a Mean Absolute Percentage Error (MAPE) of 1.9404%, which shows the forecasting results are very good, indicating high forecasting accuracy. These findings highlight the effectiveness of intervention analysis in modeling financial time series data affected by external disturbances.

REGIONS GROUPING IN CENTRAL SULAWESI PROVINCE BY TRANSMITTED DISEASE USING FUZZY GUSTAFSON KESSEL Fajri, Mohammad; Rais, Rais; Handayani, Lilies
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Health is one of the main indicators in determining the human development index. This is in contradiction with the situation in several areas in Indonesia where infectious diseases are the cause of death and have become extraordinary events. It was recorded in Central Sulawesi that in 2020 there were 8 extraordinary events due to infectious diseases which made this province become relatively high infectious diseases. One of the efforts that can be made to identify infectious diseases in an area is to form a grouping of locations into a group that has similarities and same characteristics. This is intended to provide information related to health in each region. Cluster analysis is one of method that can be used to grouping the data. Cluster analysis is the process of dividing data into a group based on the degree of similarity. Data with similar characteristics will be gathered in one group. One of the algorithms in cluster analysis is Fuzzy Gustafson Kessel which can produce relatively better groupings compared to the basic algorithms in cluster analysis. This study will use data on infectious diseases in Central Sulawesi Province with several recorded infectious diseases. From 13 regions, 5 clusters were formed. Clusters 1, 2 and 3 each consist of 3 regions, while clusters 4 and 5 each consist of 2 regions.

Mapping of Village Population Profile with Schistosomiasis Cases Using Clustering Large Applications Fajri, Mohammad; Rais, Rais; Gamayanti, Nurul Fiskia; Dg Mabaji, Siti Natazha; Rahman Jati, Shalsa Yunita; Arisandi, Rizwan
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

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.

Co-Authors . Eko Budiraharjo A Amelia Afriza, Dini Aprilia Agung Firmansyah Agung Firmansyah Agusman Sahari Ahmad Maulana Arif Rahman Arif Rahman David Bani Adam Dg Mabaji, Siti Natazha Dg. Pagiling, R K Eko Budihartono, Eko Eliani Eliani Fadjryani, Fadjryani Fandi, Ahmad Fitri, Yuhelni Gamayanti, Nurul Fiskia Haeril Haeril Handayani, L Handayani, Putu Wuri Harmila, D Hartayuni Sain Ida Afriliana Ida Ayu Putu Sri Widnyani Idris, N Iman Setiawan Islami, Mira Bela Iut Tri Utami Junaidi Junaidi Kadoena, Faldi Christiawan Lestawati, R Lilies Handayani Lukmanul Khakim Margareth, Cecilia Moh. Jusman Mohammad Fajri Muafiah Basir Muhamad Bakhar Muhammad Ilman Akbar Muhammad Ilman Akbar Mustafa Kamal Nureni, Nureni Nurfajri Nurfajri, Nurfajri Nurokhim Nurokhim Nurul Fiskia Gamayanti Rahman Jati, Shalsa Yunita Rahmayani, R Rizwan Arisandi Rizwan Arisandi, Rizwan Safar Dwi Kurniawan Sahari, A Seftiani, W Shalsa Yunita Rahman Jati Sinaga, Novita Damayanti Siti Natazha Dg Mabaji Tri Utami, I Tusilowati, Tusilowati Utami, I T Vitasari, V R Wigati, Y Winarti Winarti Yunita, Silva ZK Abdurahman Baizal

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