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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Pengabdian Magister Pendidikan IPA Jurnal Aplikasi Statistika & Komputasi Statistik EIGEN MATHEMATICS JOURNAL Jurnal Matematika UNAND Jurnal Varian Jurnal Pengabdian Masyarakat Sains Indonesia (Indonesian Journal Of Science Community Services) Mandalika Mathematics and Educations Journal Fraction: Jurnal Teori dan Terapan Matematika Jurnal Karya Pengabdian Teknik Mesin Jurnal Pepadu Bakti Sekawan : Jurnal Pengabdian Masyarakat Jurnal Sains Natural Semeton Mathematics Journal IJASDS: Indonesian Journal of Applied Statistics and Data Science
Harsyiah, Lisa
Program Studi Matematika, FMIPA, Universitas Mataram
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Library & Information Science Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

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Journal : Jurnal Varian

 1 
Classification Of Perceptions Of The Covid-19 Vaccine Using Multivariate Adaptive Regression Spline Rizki Fitri Ananda; Lisa Harsyiah; Muhammad Rijal Alfian
Jurnal Varian Vol 6 No 2 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v6i2.2639

Abstract

Indonesia is one of the countries infected with the covid-19 virus. One of the government's efforts is the covid-19 vaccination. However, the covid-19 vaccination caused controversy for some people because many people refused to be vaccinated. Public perception of the covid-19 vaccine can be categorized into two, namely positive and negative, based on survey from Indonesia ministry of health about acceptance of covid-19 vaccine state that this can be influenced by many factors. These factors are important to know as an effort to increase acceptance of covid-19. Multivariate Adaptive Regression Splines (MARS). The purpose of this study is to determine the classification model of public perception of the covid-19 vaccine and the factors that influence it. The method used in this study is Multivariate Adaptive Regression Splines (MARS). This method is appropriate classification method to be applied to categorical response variable data, The outcomes demonstrate that the optimum mars model is produced by combining BF= 24, MI =3, MO= 1, and GCV=0.07340546. The resulting classification level is 91.5% with influencing factors yaitu gender (x_1), age (x_2), last education (x_4), willingness to vaccinate (x_6), education (x_8). Based on the results obtained, the government can consider these factors for socialization
Forecasting the Amount of Water Discharge Based on the VARIMA Model Meliyana, Hesti; Hadijati, Mustika; Harsyiah, Lisa
Jurnal Varian Vol. 8 No. 2 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i2.3278

Abstract

Water is an absolutely necessary substance for every living thing. Clean water is the main requirement for ensuring human health and the environment PT. Air Minum Giri Menang (Perseroda). The purpose of this study is to determine the model and then predict the water discharge of PT. Air Minum Giri Menang using the obtained model which will be useful for the community and agencies so that the management, distribution, and use of clean water are more optimal. The method used in this study is VARIMA (Vector Autoregressive Integrate Moving Average) which can process data for more than one variable. The data used in this study is water discharge data produced and distributed in the period January 2018 to December 2021. The results show that the best model obtained is VARIMA(0,1,1) with model accuracy for water discharge data that produced and distributed based on the MAPE value of 4% and 5% which states that the forecasting results can be categorized as very good. This means that the VARIMA (0,1,1) model has provided very accurate results in predicting water discharge with very small forecasting errors, thus indicating that the model is very effective. Suggestions for further research are look for the alternative forecasting method that are overcome non-stationarity data other than data transformation.
The Implementation of Fuzzy Time Series in Forecasting The Number of Tourist Visits Aziza, Istin Fitriana; Soraya, Siti; Sahdan, Sahdan; Husain, Husain; Hendayanti, Ni Putu Nanik; Harsyiah, Lisa
Jurnal Varian Vol. 8 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i3.4890

Abstract

The development of tourism in West Nusa Tenggara (NTB) Province is supported by its geographical conditions, including scattered small islands (gilis), a tropical climate, and the cultural peculiarities of the Sasak and Mbojo Tribes, thereby becoming an attraction in the development of global tourist destinations. Tourism development in NTB Province would be more attractive with the establishment of the Mandalika National Tourism Development Strategic Area (KSPPN). This research aims to predict the number of tourist visits. A method to forecast the number of tourist visits in NTB Province is needed to assist the government in preparing appropriate facilities and infrastructure in the event of a possible surge in tourist visits. The method used in this study is the Fuzzy Time Series to predict the number of tourist visits in NTB Province. The data used in this study were secondary data sourced from the NTB government tourism office. The result of this research was that the Fuzzy Time Series method was effective in predicting the number of tourist visits in NTB Province, with an accuracy of 90.29%. The forecast result, generated using the Fuzzy Time Series method, was not significantly different from the actual data; in other words, it was almost identical to the actual data. The forecast for tourist visits to the NTB province in the 48th period remains unchanged until the 53rd period, namely 80,739.7 people. The FTS method used in this study cannot be applied to data with long-term seasonal patterns. A suggestion for future researchers is to develop a classical FTS that captures additional long-term seasonal patterns. 
Co-Authors Abdurahim, Abdurahim Adis Tia Juli Agil Asri Adis Tia Juli Agil Asri Agus Kurnia Alfarez, Dzaki Ade Alimuddin, Muhammad Angelina Ardania, Azrianti Asri, Adis Tia Juli Agil Astuti, Lita Attina Ulansari Auladi, Muhammad Yuzaul Azrianti Ardania Baskara, Zulhan Dara Puspita Anggraeni Dede Saputra Desy Komalasari Dewa Nyoman Adi Paramartha Dina Eka Putri Dina Eka Putri Eka Putri, Dina Emmy Dyah Sulistiowati Emmy Dyah Sulistyowati Emmy Dyah Sulistyowati, Emmy Dyah Evita, Isma Fadhilah, Rifdah Fadillah, Muhammad Fara Fid Fariha, Mawaddatul Graha, Syifa Salsabila Satya Hafizah Ilma Halifatunnisa, Nur Helmina Andriani Hendayanti, Ni Putu Nanik Hidayatullah, Azka Fariz Hidayatullah, Azka Farris Hisan, Khairatun Husain Husain Inarah, Filzah Istin Fitriana Aziza Istiqamah, Istiqamah Jihan Melani Jurnal Pepadu Jurniati, Jurniati Lailatul Pahmi Lailia Awalushaumi, Lailia Lawwamah, Tamsilul Lilik Hidayati, Lilik Lingking, Fransiska Prisilia Lisa , Harsyiah Luzianawati, Luzianawati M. Naoval Husni M. Syahrul Maharani, Andika Ellena Saufika Hakim Marwan Marwan Meliyana, Hesti Muhammad Rijal Alfian Mustika Hadijati Navisah, Navisah Ningrum, Salsabila Hadi Putri Nirwanto Nirwanto, Nirwanto Nur Asmita Purnamasari Nurmaulia, Ananda Rizantia Nurul Fitriyani Nurul Fitriyani PURNAMASARI, NUR ASMITA Putri, Syaftirridho Qabul Dinanta Utama Qudsi, Jihadil Qurratul Aini Ramadhan, Hikmal Maulana Ramdhani, Triana Putri Ranti, Ketrin Jupina Rifdah Fadhilah Rio Satriyantara Rizki Fitri Ananda Robbaniyyah, Nuzla Af'idatur Robbaniyyah, Nuzla Af’idatur Sabina, Sabna Zulfaa Sahdan, Sahdan Salwa Salwa Salwa Salwa Saputra, Dede Saputri, Intan Editia Sari, Baiq Desi Nurma Sari, Kurnia Mahraini Kartika Setiawana, Ena Siti Soraya Sulpaiyah Sulpaiyah Syaftirridho Putri Syamsul Bahri Syamsul Bahri Tajalli, Halawatun Tri Maryono Rusadi Vidya Atika Ramdani Yarti, Suwindah Puji Yuliana Lestari Zindawi, M. Daffa Rizki Zulhan Widya Baskara