Garuda - Garba Rujukan Digital

p-Index From 2020 - 2025

9.784

P-Index

This Author published in this journals

All Journal IQTISHODUNA Jurnal Ekonomi Modernisasi The Asian Journal of Technology Management (AJTM) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Studi Komunikasi Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jurnal Varian Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Journal of Applied Science, Engineering, Technology, and Education Variansi : Journal of Statistics and Its Application on Teaching and Research Mattawang: Jurnal Pengabdian Masyarakat JINAV: Journal of Information and Visualization Quantitative Economics and Management Studies LOSARI: Jurnal Pengabdian Kepada Masyarakat Jurnal Riset dan Inovasi Pembelajaran Panrannuangku Jurnal Pengabdian Masyarakat EduLine: Journal of Education and Learning Innovation Daengku: Journal of Humanities and Social Sciences Innovation ARRUS Journal of Social Sciences and Humanities ARRUS Journal of Mathematics and Applied Science al-fikrah: Jurnal Manajemen Pendidikan Seminar Nasional Pengabdian Kepada Masyarakat VARIANSI: Journal of Statistics and Its Application on Teaching and Research Seminar Nasional Hasil Penelitian LP2M UNM ARRUS Jurnal Pengabdian Kepada Masyarakat

Ahmar, Ansari Saleh

Department Of Statistics, Universitas Negeri Makassar, 90223, Makassar, Indonesia

Author-ID : 592968

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

Published : 87 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4 5

Will Covid-19 cases in the World reach 4 million? a forecasting approach using SutteARIMA Ansari Saleh Ahmar; R. Rusli
JOIV : International Journal on Informatics Visualization Vol 4, No 3 (2020)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.3.389

The objective of this study was to determine whether Covid-19 cases in the world would have reached 4 million cases with the SutteARIMA method forecasting approach. Data from this study were obtained from the Worldometer from 1 March 2020 to 05 May 2020. Data were used for data fitting from 1 March 2020 to 28 April 2020 (29 April 2020 â€“ 05 May 2020). The data fitting is used to see the extent of the accuracy of the SutteARIMA method when predicting data. The MAPE method is used to see the level of data accuracy. Results of forecasting data for the period from 29 April 2020 to 05 May 2020: 72,731; 84,666; 92,297; 100,797; 84,312; 81,517; 74845. The accuracy of SutteARIMA for the period 30 April 2020 â€“ 06 May 2020 shall be 0.069%. Forecast results for as many as 4 million cases, namely from 08 May 2020 to 10 May 2020: 3,966,786; 4,047,328 and 4,127,747. The SutteARIMA method predicts that 4 million cases of Covid-19 in the world will be reported on the WHO situation report on the day 110/111 or 09 May 2020/10 May 2020.

Application of Neural Network Time Series (NNAR) and ARIMA to Forecast Infection Fatality Rate (IFR) of COVID-19 in Brazil Ansari Saleh Ahmar; Eva Boj
JOIV : International Journal on Informatics Visualization Vol 5, No 1 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.1.372

Forecasting is a method that is often used to view future events using past time data. Past time data have useful information to use in obtaining the future. The aim of this study was to forecast infection fatality rate (IFR) of COVID-19 in Brazil using NNAR and ARIMA. ARIMA and NNAR are used because (1) ARIMA is a simple stochastic time series method that can be used to train and predict future time points and ARIMA also capable of capturing dynamic interactions when it uses error terms and observations of lagged terms; (2) the Artificial Neural Network (ANN) is a technique capable of analyzing certain non-linear interactions between input regressor and responses, and Neural Network Time Series (NNAR) is one method of ANN in which lagged time series values were used as inputs to a neural network. Data included in this study were derived from the total data of confirmed cases and the total data of death of COVID-19. The data of COVID-19 in Brazil from February 15, 2020 to April 30, 2020 were collected from the Worldometer (https://www.worldometers.info/coronavirus/) and Microsoft Excel 2013 was used to build a time-series table. Forecasting was accomplished by means of a time series package (forecast package) in R Software. Neural Network Time Series and ARIMA models were applied to a dataset consisting of 76 days. The accuracy of forecasting was examined by means of an MSE. The forecast of IFR of COVID-19 in Brazil from May 01, 2020 to May 10, 2020 with NNAR (1,1) model was around in 6,85% and ARIMA (0,2,1) was around in 7.11%.

The Use of Excel Statistics for Research Data Processing for Teachers of SMAN 3 Barru, Barru Regency, Indonesia: Penggunaan Statistika Excel Untuk Pengolahan Data Penelitian Bagi Guru SMAN 3 Barru Kabupaten Barru, Indonesia R. Rusli; Abdul Rahman; Hamzah Upu; Ansari Saleh Ahmar; H. Hastuty
Mattawang: Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

This activity was carried out with the aim of: (1) Increasing teacher knowledge in processing and analyzing research data; (2) Developing teacher awareness and knowledge about the importance of data management in research data analysis; (3) Improving the insight, ability and skills of teachers in utilizing data to make it more informative by analyzing data using excel software; and (4) Reducing the number of teachers who perform data processing and analysis intuitively and manually in the computing era. The results of the implementation of this activity were: (1) The knowledge of teachers in processing and analyzing research data was increased; (2) The awareness and knowledge of teachers about the importance of processing and analyzing research data were developed; (3) The insight, ability and skills of teachers in utilizing data to be more informative with proper data processing and analysis were improved; and (4) The number of teachers who perform data processing and analysis intuitively and manually in the computing era was reduced. Abstrak Pengolahan data menggunakan Anaysis Toolspack dilakukan dalam bentuk pelatihan bagi guru-guru di Kab. Barru bekerjasama dengan UPT SMA Negeri 1 Barru Kabupaten Takalar. Pelatihan bertempat di SMA Negeri 1 Barru Kabupaten Barru dan dilaksanakan secara daring dengan menggunakan Zoom. Tujuan dari pelatihan ini adalah agar guru terampil dalam menggunakan paket statistik yang dimiliki Excel untuk mengolah data dan mengolah data menjadi satu informasi. Hasil pelatihan menunjukkan bahwa rata-rata kemampuan guru dalam menggunakan statistika pada paket excel analysis tools pack dalam mengolah dan mengolah data setelah pelatihan lebih baik (meningkatkan) daripada sebelum pelatihan.

Correlation between Covid-19 and weather/climate indicators: A Response Ansari Saleh Ahmar
JINAV: Journal of Information and Visualization Vol. 1 No. 1 (2020)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav158

This is a response to article by Dr. Ramadhan Tosepu and his colleagues entitled: “Correlation between the weather and the Covid-19 pandemic in Jakarta, Indonesia” in Science of The Total Environment, Vol. 725; and Dr. Muhammad Farhan Bashir and his colleagues entitled: “Correlation between the climate indicators and the Covid-19 pandemics in New York, USA.” in Science of The Total Environment, Vol. 728. We agree with the results of their research, but there are things that need to be clarified in relation to the selection of the Spearman-rank correlation as an analytical tool, because the selection of this analysis is without the normality test of the data. Spearman-rank correlation is useful for non-normally distributed continuous data; can be used for ordinal data; and is relatively robust for outliers.

The date predicted 200.000 cases of Covid-19 in Spain Ansari Saleh Ahmar; Eva Boj
Journal of Applied Science, Engineering, Technology, and Education Vol. 2 No. 2 (2020)
Publisher : Yayasan Ahmar Cendekia Indonesia

The aim of this study is to predict 200.000 cases of Covid-19 in Spain. Covid-19 Spanish confirmed data obtained from Worldometer from 01 March 2020 – 17 April 2020. The data from 01 March 2020 – 10 April 2020 using to fitting with data from 11 April – 17 April 2020. For the evaluation of the forecasting accuracy measures, we use the mean absolute percentage error (MAPE). Based on the results of SutteARIMA fitting data, the accuracy of SutteARIMA for the period 11 April 2020 - 17 April 2020 is 0.61% and we forecast 20.000 confirmed cases of Spain by the WHO situation report day 90/91 which is 19 April 2020 / 20 April 2020.

Eksplorasi Metode Triple Exponential Smoothing Pada Peramalan Jumlah Penggunaan Air Bersih di PDAM Kota Makassar Suci Lestari; Ansari Saleh Ahmar; R. Ruliana
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 2, No 3 (2020)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm14641

Abstrak. Ketersediaan air bersih sangat penting dikarenakan hampir seluruh aktivitas manusia sangat bergantung terhadap ketersediaan air bersih. Hal ini membuat faktor produksi dan ketersediaan air bersih selalu menjadi prioritas dalam pelayanan penyaluran air bersih sehingga penulis tertarik untuk mengkaji tentang peramalan jumlah penggunaan air bersih di PDAM Kota Makassar. Salah satu metode yang cocok untuk menangani kasus tersebut adalah metode Time Series. Metode Triple Exponential Smoothing atau biasa disebut dengan Winter Exponential Smoothing merupakan salah satu metode Time Series yang cocok untuk menangani data yang bersifat musiman seperti jumlah penggunaan air bersih di Kota Makassar. Adapun Langkah analisis dari metode Triple Exponential Smoothing adalah identifikasi model, estimasi parameter dengan trial and error, selanjutnya adalah perhitungan nilai awal dari pemulusan data, trend, dan musiman dengan panjang satu musim L=12 dan yang terakhir adalah menghitung nilai error dengan menggunakan MAPE dan RMSE. Model terbaik diperoleh dari kombinasi parameter α = 0,1; β = 0,1; dan γ=0,6 yang menghasilkan kesalahan peramalan terkecil menggunakan RMSE dengan nilai sebesar 168,175 dan MAPE dengan nilai sebesar 4,736. Dengan meggunakan model maka diperoleh peramalan jumlah penggunaan air bersih di PDAM Kota Makassar dari bulan januari – desember 2019 sebagai berikut: 2779,10; 2788,94; 2728,61; 2797,48; 2787,97; 2752,66; 2742,18; 2708,50; 2644,55; 2521,50; 2537,74; 2732,55. Dari hasil peramalan tersebut terlihat mendekati dan tidak terlalu jauh menyimpang dari data tahun sebelumnya sehingga dapat dijadikan acuan produktivitas air bersih di PDAM Kota Makassar agar produktivitas air dapat mencukupi semua kebutuhan masyarakat di Kota Makassar.Kata kunci: air, triple exponential smoothing, time series, peramalan.

Metode Vector Autoregressive dalam Menganalisis Pengaruh Kurs Mata Uang, Inflasi, dan Suku Bunga Terhadap Indeks Harga Saham Gabungan Alief Imron Juliodinata; Muhammad Arif Tiro; Ansari Saleh Ahmar
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 1, No 2 (2019)
Publisher : Universitas Negeri Makassar

Metode Vector Autoregressive adalah salah satu analisis yang digunakan untuk menganalisis data deret waktu (time series). Data deret waktu dapat dinyatakan dalam tahun, bulan, minggu, atau hari. Salah satu tujuan penelitian adalah untuk mengetahui pengaruh antara indeks perekonomian suatu negara khususnya pengaruh Kurs, Inflasi dan Suku Bunga terhadap Indeks Harga Saham Gabungan. Data yang digunakan dalam penelitian ini adalah data Kurs, Inflasi, Suku Bunga dan Indeks Harga Saham Gabungan dari bulan juli 2005 hingga juni 2016. Karena data tidak stasioner pada level maka dilakukan differencing terhadap data. Setelah stasioner selanjutnya dilakukan uji kointegrasi untuk mencaritau apakah terdapat kointegrasi antara peubah. Dengan karakteristik data yang Stasioner pada difference dan terdapat kointegrasi, sehingga memenuhi asumsi analisis VECM. Setelah dilakukan analisis VECM dilakukan analisis IRF dan VD. Adapun hasil analisisnya menunjukkan bahwa hanya Kurs yang secara signifikan berpengaruh lansung terhadap Indeks Harga Saham Gabungan.Kata Kunci: Analisis Time Series, VAR, Kurs, Suku Bunga, Inflasi, IHSG

Metode Analisis Diskriminan dalam Pengelompokan Kabupaten/Kota di Provinsi Sulawesi Selatan Berdasarkan Indikator Indeks Pembangunan Manusia Novi Afryanthi S.; Muhammad Arif Tiro; Ansari Saleh Ahmar
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 2, No 1 (2020)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm14978

Abstract. Discriminant analysis is a method in multivariat statistic analysis that related with object which have separated into the defined group defined and see the accuracy of the formed group. In this research, clustera analysis is used for the first grouping, cluster analysis is a statistical analysis which aims to classify some objects based on the characteristics similarity among the object. Data for this study is HDI (Human Development Index) of indicator in south sulawesi in 2016. The result of this research are 1st cluster (lower HDI indicator) which have 21 city/ distric and the 2nd cluster (higher HDI indicator) which have 3 city/distric as the closeness value between the cluster that formed is 0.902 which shows the closeness between the cluster is high . Furthermore, the discriminant function that have formed explains that if the life expectancy increase, the HDI indicator in city/distric in south sulawesi province will decrease but if school expectation duration in school , average of duration in school, and parity of pur hasing power is increasing, the HDI indicator in city/distric in aouth sulawesi will also increase.Keywords: Cluster analysis, Discriminant analysis , Human development index indicator.

Model Spasial Autoregresif (SAR) Durbin pada Anak Putus Sekolah (APS) yang Mengikuti Ujian Paket C Jenjang SMA Sederajat di Kota Makassar N. Nurahdawati; R. Ruliana; Ansari Saleh Ahmar
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 2, No 2 (2020)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm14630

Abstrak. Penelitian ini adalah penelitian statistika terapan yang bertujuan (i) Untuk mengetahui jumlah rata-rata Anak Putus Sekolah (APS) yang mengikuti paket C di Kota Makassar; (ii) Untuk mengetahui Model SAR Durbin pada Anak Putus Sekolah (APS) yang mengikuti paket C di Kota Makassar; dan (iii) Untuk mengetahui faktor-faktor apa saja yang mempengaruhi Anak Putus Sekolah (APS) yang mengambil paket C pada jenjang SMA sederajat di Kota Makassar. Penelitian ini menggunakan metode SAR Durbin (Spasial Autoregresif Durbin). Hasil penelitian ini menunjukkan bahwa : (i) APS yang mengikuti ujian Paket C tingkat SMA di Kota Makassar terdapat dependensi spasial antar kecamatan satu dengan kecamatan satuan lainnya; (ii) APS yang mengikuti ujian Paket C tingkat SMA sederajat di Kota Makassar, dan (iii) APS yang mengikuti ujian Paket C dengan hasil analisis Model SAR Durbin didapatkan variabel predictor yaitu Rasio Guru Sekolah (X2) dan Jumlah Sekolah (X5). Sedangkan parameter Lag spasial yang didapatkan variabel prediktor yaitu Lag Rasio Murid Sekolah (X1), Lag Tingkat Kemiskinan (X4) dan Lag Jumlah Sekolah (X5).Kata kunci: Anak Putus Sekolah,Model Autoregresif Spasial Durbin

Analisis Penyebaran Hunian dengan Menggunakan Metode Nearest Neighbor Analysis Ahmad Rifad Riadhi; Muhammad Kasim Aidid; Ansari Saleh Ahmar
VARIANSI: Journal of Statistics and Its application on Teaching and Research Vol 2, No 1 (2020)
Publisher : Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/variansiunm12901

Abstrak Nearest neighbor analysis merupakan sebuah metode analisis yang dapat digunakan untuk menentukan suatu pola penyebaran, apakah berpola seragam (uniform), acak (random), atau mengelompok (cluster). Nearest neighbor analysis dalam perhitungannya mempertimbangkan jarak, jumlah titik lokasi penyebaran, dadn luas wilayah, hasil akhir analisis ini berupa indeks tetangga terdekat (T) yang nilainya berkisar antara 0 sampai 2.15. Untuk menentukan faktor-faktor yang mempengaruhi pola penyebaran hunian, pada penelitian ini menggunakan analisis korelasi (r). Hasil dari penelitian ini berdasarkan perhitungan nearest neighbor analysis yaitu pola penyebaran hunian di Kota Kendari secara keseluruhan memiliki pola penyebaran yang cenderung berpola acak artinya jarak antara titik-titik penyebaran hunian tidak memiliki jarak yang sama, dan hasil dari perhitungan korelasi diperoleh faktor-faktor yang mempengaruhi pola penyebaran hunian yang cenderung berpola acak. Faktor yang paling berpengaruh dengan hubungan positif yaitu faktor pertumbuhan penduduk, hal ini dapat dilihat pada hasil korelasi dimana faktor pertumbuhan penduduk memiliki nilai korelasi tertinggi yaitu 0.618 dan faktor yang paling berengaruh dengan hubungan negatif yaitu faktor fasilitas Pendidikan hal ini dapat dilihat pada hasil korelasi dimana faktor fasilitas Pendidikan memiliki nilai korelasi negatif tertinggi yaitu -0.526.Keywords: Nearest Neighbor Analysis, Pola Penyebaran.

Co-Authors Abdul Rahman Abdul Rahman Abdussakir Abdussakir Absussakir Abdussakir Achmad Sani Supriyanto Agus Nasir Ahmad Rifad Riadhi Ahmad Talib Akbar Iskandar Akbar Iskandar Alfairus, Muh. Qodri Ali Mokhtar Alief Imron Juliodinata Alok Kumar Panday Alsa, Yudhistira Ananda Andika Isma ANDIKA SAPUTRA Angela Diaz Cadena Asfar Asfar Asmar Asmar, Asmar Astuti, Niken Probondani Aswi, Aswi Ayu Rahayu Azzajjad, Muhammad Fath Boj del Val, Eva Boj, Eva Bustan, M Nadjib Dary Mochamad Rifqie Della Fadhilatunisa Dewi Fatmarani Surianto Dewi Satria Ahmar Djawad, Yasser Abd. Ersa Karwingsi Eva Boj Faizal Arya Samman Fathahillah Fathahillah Hamzah Upu Hardianti Hafid Hastuty Hastuty Hastuty Hastuty Hastuty Musa Herman Herman Hidayat M., Wahyu Ifriana Ifriana Ilimu, Edi Irwan Irwan Irwan Irwan Isma Muthahharah Jamaluddin Jamaluddin Kamaluddin Kamaluddin Kasmudin Mustapa Khadijah Khaeruddin Khaeruddin Lince, Ranak M. Miftach Fakhri Maemunah Magfirah Manalu, Yessi Febianti Mansyur Mansyur Marni Marni, Marni Meliyana R, Sitti Masyitah Miguel Botto-Tobar Misriani Suardin Mohd. Rizal Mohd. Isa Muhammad Abdy Muhammad Arif Tiro Muhammad Arif Tiro Muhammad Farhan Muhammad Kasim Aidid Muhammad Kasim Aidid Muhammad Nadjib Bustan Muhammad Nadjib Bustan Muhammad Nusrang Muliadi Muliadi N. Nurahdawati Nachnoer Arss Nasrul Ihsan Niken Probondani Astuti Niken Probondani Astuti Novi Afryanthi S. Nur Anisa Nurdin Arsyad, Nurdin Nurhikmawati, Nurhikmawati Nurul Khofifah Salsabila Parkhimenko Vladimir Anatolievich Patmasari, Andi Poerwanto, Bobby R. Ruliana R. Rusli R. Rusli R. Rusli Rahman, Abdul Rahman, Muhammad Fatur Rahmat Hidayat Rahmat Hidayat Rais, Zulkifli Rajesh Kumar Ramli Umar Riny Jefri Rizal Bakri Robbi Rahim Rosidah Rosidah Rosidah Rosidah Ruliana Ruliana Ruliana, Ruliana Rusli Rusli Rusli Rusli Rusli Rusli Rusli Rusli Rustam, Sitti Nailah Sahid Sahid Salim Al Idrus Salim Al Idrus Sapto Haryoko Sarinah Emilia Tonio Shofiyah Al Idrus Singh, Pawan Kumar Siti Nurazizah Auliah Sitti Masyitah Meliyana R. Sitti Rahmawati Sobirov, Bobur Sri Hastuti Virgianti Pulukadang Sri Muliani Sriwahyuni, Andi Ayu Suci Lestari Sutamrin, Sutamrin Suwardi Annas Suwardi Annas Suwardi Annas Syafruddin Side Tabash, Mosab Tri Santoso Triutomo, Agung wahyuni wahyuni Yunus, Asmar Zakiyah Mar'ah Zakiyah Mar'ah Zamil Wahab Zulkifli Rais

Title

Found 87 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 87 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 87 Documents
Search