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All Journal Natural Science: Journal of Science and Technology JOIN (Jurnal Online Informatika) JURNAL ILMIAH MATEMATIKA DAN TERAPAN Journal of Data Analysis Jurnal Keteknikan dan Sains (JUTEKS) ESTIMASI: Journal of Statistics and Its Application Majalah Ilmiah Matematika dan Statistika (MIMS) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS DedikasiMU: Journal of Community Service Mitra Sains
Junaidi Junaidi
Program Studi Statistika Fakultas MIPA Universitas Tadulako
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Social Sciences

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PENERAPAN METODE BOOSTING PADA CART UNTUK MENGKLASIFIKASIKAN KORBAN KECELAKAAN LALU LINTAS DI KOTA PALU Susiana, Luluk; Utami, Iut Tri; Junaidi, Junaidi
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 (395.793 KB)

Abstract

Kota Palu sebagai ibu kota Provinsi Sulawesi Tengah dengan kecelakaan lalu lintas  yang cukup tinggi yang setiap tahunnya memiliki kematian sekitar 365 jiwa. Kecelakaan lalu lintas dipengaruhi oleh beberapa faktor, diantaranya jenis pelanggaran, jenis kecelakaan, dan lain-lain. Tujuan yang akan dicapai dalam penelitian ini adalah untuk menentukan ketepatan klasifikasi pada korban kecelakaan lalu lintas di Kota Palu dengan menggunakan metode boosting serta faktor-faktor yang mempengaruhinya. Hasil dari penelitian ini menunjukkan bahwa ketepatan klasifikasi metode boosting sebesar 82% dan  metode CART sebesar 77,9%. Hasil tersebut menunjukkan bahwa metode boosting dapat meningkatan tingkat akurasi. Sedangkan faktor-faktor yang mempengaruhi korban kecelakaan lalu lintas di Kota Palu adalah faktor jenis kecelakaan (X1), peran korban dalam kecelakaan (X4), jenis pelanggaran (X7) dan usia (X3) korban kecelakaan lalu lintas di Kota Palu.
PENERAPAN AUTOREGRESSIVE DISTRIBUTED LAG (ARDL) DALAM MEMODELKAN PENGARUH INDEKS HARGA KONSUMEN (IHK) KELOMPOK BAHAN MAKANAN DAN KELOMPOK MAKANAN JADI TERHADAP INFLASI DI KOTA PALU Tulak, Dewi Yuliastuti; Junaidi, Junaidi; Utami, Iut Tri
Natural Science: Journal of Science and Technology Vol 6, No 3 (2017): Volume 6 Number 3 (December 2017)
Publisher : Univ. Tadulako

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Abstract

Inflasi adalah suatu proses meningkatnya harga-harga secara umum dan terus-menerus berkaitan dengan mekanisme pasar. Inflasi merupakan salah satu indikator yang digunakan untuk mengukur stabilitas harga suatu barang di pasar. Indikator ini akan berdampak terhadap dinamika pertumbuhan ekonomi. Dalam penelitian ini, dilakukan analisis pengaruh indeks harga konsumen bahan makanan dan makanan jadi terhadap laju inflasi di kota Palu. Model yang digunakan adalah model Autoregressive Distributed Lag (ARDL) yaitu suatu model regresi dengan memasukkan nilai variabel yang menjelaskan nilai masa kini atau nilai masa lalu dari variable bebas sebagai salah satu variabel penjelas. Hasil penelitian ini menunjukkan bahwa tidak terdapat kointegrasi antar variabel dan model yang didapatkan yang menunjukkan bahwa harga bahan makanan berpengaruh terhadap inflasi di Kota Palu.
PENERAPAN SPATIAL DURBIN MODEL (SDM) PADA INDEKS PEMBANGUNAN GENDER DI PULAU SULAWESI Suaib, Tri Putri Andayani; Junaidi, Junaidi; Fadjryani, Fadjryani
Majalah Ilmiah Matematika dan Statistika Vol 22 No 1 (2022): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v22i1.29581

Abstract

The Gender Development Index (GDI) is a development index of the quality of human life that is more concerned with gender status. GDI can be used to determine human development between males and females. This study uses the Spatial Durbin Model (SDM) method. The SDM method was formed due to the spatial influence on the dependent and independent variables. The purpose of this study is to determine the GDI model in Sulawesi Island and the factors that influence it. The factors that have a significant effect on the Gender Development Index (GDI) in Sulawesi Island using the Spatial Durbin Model (SDM) are Life Expectancy, per capita contests, average years of schooling, and labor force participation.Keywords: GDI, AIC, SDMMSC2020: 62H11
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.
Penerapan Model Analisis Regresi Linier Berganda dengan Pendekatan Bayesian pada Data Aset Bank di Indonesia Ahmad Mursyid Ainul; Junaidi Junaidi; Iut Tri Utami
Jurnal Keteknikan dan Sains (JUTEKS) Vol. 1 No. 1 (2018): Jurnal Keteknikan dan Sains - Juni 2018
Publisher : LPPM Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (523.445 KB)

Abstract

Analisis regresi merupakan salah satu teknik analisis data yang seringkali digunakan untuk mengkaji hubungan antara beberapa variabel. Salah satu penerapan regresi dapat ditemukan pada bidang ekonomi yakni penentuan faktor-faktor yang mempengaruhiaset bergantung pada Suku Bunga Dasar Kredit (SBDK). Tujuan penelitian ini adalah mengestimasi parameter dan menentukan faktor-faktor yang mempengaruhi aset bankmenggunakan metode regresi linier berganda dengan pendekatan Bayesian. Aplikasi WinBUGSdigunakan dalam iterasi algoritma. Variabel bebas yang digunakan dalam penelitian adalah        Aset (Y), Kredit korporasi (X1), Kredit ritel (X2), Kredit mikro (X3), Kredit komsumsi KPR (X4), Kredit konsumsi non KPR (X5). Sebanyak 5000 iterasidengan penerapan metode MCMC dan hasil estimasi parameter yaitu :yˆ = 2,836+0,2836x +0,2634x +0,1953x +0,2718x +0,2617x 1i 2i 3i 4i 5i dengan selang kepercayaan 95% untuk masing-masing penduga parameter berturut-turut adalah(1.383;4.791), (0,135;0,479), (0,123;0,447), (0,092;0,333), (0,13;0,468)dan (0,126;0,439).Kata Kunci :Bayesian, MCMC, suku bunga, WinBUGSABSTRACT Regression analysis is a technique of statistical data analysis to investigate the relationship between several variables. One of the application of the regression can be found in the economic field to determine factors that affect the asset which depends on the Basic Interest Rate of Credit (SBDK). The purpose of this study is to estimate the parameters and determining factors that affect bank assets using multiple linear regression method with Bayesian approach. The WinBUGS is used in algorithm iteration. The independent variables used in the research are Assets (Y), Corporate Credit (X1), Retail Credit (X2), Micro Credit (X3), KPR Consumption Loan (X4), Non-KPR Consumption Loans (X5). A total of 5000 iterations with the application of the MCMC method and parameters estimation showing that the regression equations are: yˆ =2,836+0,2836x +0,2634x +0,1953x +0,2718x +0,2617x 1i 2i 3i 4i 5i with 95% confidence intervals for each parameterized predictor are (1,383,4,791), (0,135; 0,479), (0,123; 0,447), (0,092; 0,333), (0,13; 0,468) and (0,126; 0.439). Our research reveals that the 5 independent variables affect the asset Keywords : Bank Asset, Bayesian, MCMC, Regression Analysis, WinBUGS  
Automatic Plant Watering System for Local Red Onion Palu using Arduino Iman Setiawan; Junaidi Junaidi; Fadjryani Fadjryani; Fika Reski Amaliah
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.813

Abstract

Central Sulawesi Province in Indonesia has great potential for horticultural commodities, namely local red onion Palu. In the current climate change, local farmers are still watering plants in the conventional way. The automatic watering system simplifies the work of local farmers. This device uses a soil moisture sensor as a soil moisture detector and Arduino as a program brain. This study aims to determine the position of soil moisture sensor, the optimal length of watering time and analyze the quality of data stored. The experiment was carried out using a Completely Randomized Design (CRD). The position of the soil moisture sensor was analyzed by Profile Analysis. The optimal length of watering time was determined by Analysis of Variance (ANOVA) and Least Significant Difference (LSD). The quality of data stored was determined by a number of missing values and frequency of watering. The results showed that in soil planting media the position of soil moisture sensor had no significant effect, while in others planting media (water and combination of water and soil) the position of the sensor had a significant effect. The optimal watering time was 3 seconds. The stored data has low quality in terms of missing values and lack of consistency.
ANALISIS SPASIAL PENYEBARAN PENYAKIT SCHISTOSOMIASIS MENGGUNAKAN INDEKS MORAN UNTUK MENDUKUNG ERADIKASI SCHISTOSOMIASIS DI PROVINSI SULAWESI TENGAH BERBASIS WEB DASHBOARD Nur Sakinah; Wawan Saputra; Nurfitra Nurfitra; Satriani Satriani; Junaidi Junaidi
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.16580

Abstract

 Schistosomiasis is a parasitic disease which is caused by worm infection with worms from the Schistosoma class. This disease is zoonotic, consequently the source of transmission is not only infected on mammals but also on humans. The method used in this study is spatial autocorrelation. This is conducted to determine the presence or absence of global or local spatial autocorrelation as well as the pattern distribution of Schistosomiasis cases in Poso Regency by using Moran's I. The result in this study showed that the p-value of positive global autocorrelation is 2,2 × 10-16. This result is smaller than the 5% of significance level and also smaller than the Moran's I value (0,66).  The Moran’s I value lies in the interval  indicating that each adjacent area has the same number of Schistosomiasis cases. Meanwhile, the local spatial autocorrelation test (LISA) for Schistosomiasis cases in Poso Regency, such as villages at Lore Utara, Lore Timur and Lore Peore has the LISA value 1 determining the correlation is strong and positive. The distribution pattern of Schistosomiasis cases in Poso Regency forms a group pattern, namely disease prone areas (HH), disease spread areas (HL), disease alert areas (LH) and disease safe areas (LL) 
Tranformasi Calanthe Triplicata untuk Branding Unik Motif Batik Sulawesi Tengah Ikram, Ikram; Abdi; Mutmainna, N; Khasmawati, J; Wahyuli, D; Sudarsana, I W; Junaidi; Fadjriyani; Setiawan, I; Hendra, S
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 19 No. 2 (2022)
Publisher : Program Studi Matematika, Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/2540766X.2022.v19.i2.16156

Abstract

Batik merupakan salah satu warisan seni budaya bangsa Indonesia yang ada untuk terus dipertahankan dan dikembangkan. Upaya ini dilakukan dengan memperbanyak motif--motif baru yang salah satunya dengan mengekplorasi keunikan alam yang ada. Alam Sulawesi Tengah dengan keunikan flora-nya, yaitu bunga anggrek dengan nama Latin Calanthe Triplicata merupakan jenis tanaman endemic yang diekplorasi guna mendapatkan motif baru untuk menambah keragaman Batik di Indonesia. Etnomatematika merupakan salah satu cabang ilmu matematika untuk membahas hubungan antara matematika dan budaya yang dapat digunakan untuk membentuk pola Batik, khususnya bentuk fraktal. Bentuk fraktal adalah suatu objek yang tampak memiliki kemiripan diri yang simetris satu sama lain jika dilihat pada skala tertentu dan merupakan bagian terkecil dari keseluruhan struktur objek. Di dalam penelitian ini dilakukan pembuatan bentuk fraktal dengan mentransformasi tanaman anggrek sebagai branding unik untuk motif batik Sulawesi Tengah. Adapun hasil yang diperoleh berupa metif-motif baru yang unik, menarik dan elegan yang kita sebut dengan motif Sambuang, Rekang, Kecrek dan Angkan.
Internet of Things (IoT) for Soil Moisture Detection Using Time Series Model Iman Setiawan; Junaidi Junaidi; Fadjryani Fadjryani; Fika Reski Amaliah
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i2.951

Abstract

Technology in agriculture has been widely and massively applied. One of them is automation technology and the use of big data through the Internet of Things (IoT). The use of IoT allows a process to run automatically without human intervention. Extreme weather changes and narrow land use are one of the main problems in agriculture. The development of IoT devices has been widely developed regarding this subject. One of them is a soil moisture detection system. This study aims to build an IoT soil moisture detection system. The system will use a sensor as input which is then processed in a microcontroller device and the prediction results are sent to the IoT cloud platform. Prediction results are obtained using a time series model and then its performance is evaluated using RMSE. This model was chosen because the structure of the observed soil moisture data is based on time. The results of this study indicate that the soil moisture IoT system can work well. This is supported by the results of the prediction evaluation value of the RMSE = 1.175682x10-5 model which is very small.
Pemodelan Topik pada Judul Berita Online Detikcom Menggunakan Latent Dirichlet Allocation Yayang Matira; Junaidi; Iman Setiawan
ESTIMASI: Journal of Statistics and Its Application Vol. 4, No. 1, Januari, 2023 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.24843

Abstract

Detikcom is a very popular news portal today. The news on the portal continues to grow time to time, causing the existing news data to pile up. As a result, this is necessary to utilize this large amount of data. One of the ways that can be used is to extract topics from news text data through topic modeling using the Latent dirichlet allocation (LDA) method. This method is very popular because it can perform analysis on very large documents. This research aims to find certain patterns in a document by generating several different topics so that it does not specifically divide documents into a particular topic. This research has three topics obtained, with a coherence score is 0,7586. The first topic discusses conflicts and crises within a country, the second topic discusses issues related to humanitarian, and the third topic discusses the issues of corruption committed by state officials.
Co-Authors Abdi Ahmad Mursyid Ainul Bahrudin Bahrudin Fadjriyani Fadjryani, Fadjryani Fika Reski Amaliah Hajra Rasmita Ngemba Hendra, S Ikram Ikram Iman Setiawan Iskandar Lapanjang Iut Tri Utami Iut Tri Utami Khasmawati, J Mohammad Fajri Mutmainna, N Nur Sakinah Nurfitra Nurfitra Nurpati Nurpati Satriani Satriani Setiawan, I Suaib, Tri Putri Andayani Sudarsana, I W Susiana, Luluk Tulak, Dewi Yuliastuti Wahyuli, D Wawan Saputra Yandi Ristawan Yayang Matira