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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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Perbandingan Regresi Ridge dan Partial Least Square Dalam Mengatasi Multikolinearitas Pada Faktor-faktor Yang Mempengaruhi Kemiskinan di Nusa Tenggara Barat Sari, Baiq Desi Nurma; Harsyiah, Lisa; Baskara, Zulhan Widya
Indonesian Journal of Applied Statistics and Data Science Vol. 2 No. 2 (2025): November
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v2i2.8051

Abstract

Poverty is one of the most serious problems and must be addressed immediately. One of the steps to overcome poverty is to identify the factors that influence it. One of the statistical techniques used to examine the relationship between predictor variables and the response variable is regression analysis. An important assumption that must be met in regression analysis is the absence of multicollinearity. Multicollinearity refers to a condition where two or more predictor variables are highly correlated, which can reduce the accuracy of the regression model. Therefore, addressing multicollinearity is essential to obtain a reliable and valid model. Inthis study, two methods were employed Ridge regression and Partial Least Square (PLS) with the aim of overcoming the multicollinearity problem. The  R2adj value was used as a comparison criterion to evaluate model performance. Both methods were applied to poverty-related data that exhibited signs of multicollinearity. The R2adj value obtained from the ridge regression model was  68.57%, while the PLS model yielded a higher  R2adj value of 75.1% . Based on this comparison, it can be concluded that the PLS model produced more optimal results than ridge regression in addressing multicollinearity in the context of modeling factors that influence poverty levels in West Nusa Tenggara Province.
Pengembangan Media Edukasi Berbasis Vidio Untuk Peningkatan Kompetensi Kader Posyandu dalam Mendukung Desa Cantik di Lembar Selatan Istiqamah, Istiqamah; Baskara, Zulhan Widya; Harsyiah, Lisa; Putri, Dina Eka; Andriani, Helmina; Qudsi, Jihadil; Saputri, Intan Editia
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2025): Desember
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v5i2.894

Abstract

The integrated health posts (posyandu) in South Lembar Village, West Lombok Regency, face challenges in recording and reporting health data due to the low level of digital literacy among community health cadres, which slows down decision-making for village-level health programs. This community service initiative aims to enhance the competencies of cadres from 13 posyandu through the development of educational media in the form of Microsoft Excel tutorial videos, combined with in-person training sessions and field mentoring.The implementation methods included outreach activities, intensive training, the application of technology through short video tutorials on the TikTok platform, and evaluation using paired t-test analysis. The evaluation results indicated a significant improvement in cadre competencies, with the average pre-test score increasing from 62.00 to 90.00 in the post-test. Furthermore, the paired t-test results (p-value 0.045 < 0.05) demonstrate that the training had a positive impact on cadre skills.This improvement reflects the effectiveness of combining self-directed video learning with direct mentoring in accelerating mastery of basic Excel functions for managing nutrition, immunization, and maternal visit data. Overall, the program succeeded in strengthening the digital reporting system of the posyandu.
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. 
Klasifikasi Kegagalan Pengobatan Penyakit Tuberkulosis (TB) di Kota Mataram Menggunakan Metode Multivariate Adaptive Regression Splines (MARS) Lisa Harsyiah; Zulhan Widya Baskara; Jihadil Qudsi; Helmina Andriani; Dina Eka Putri
Mandalika Mathematics and Educations Journal Vol 8 No 2 (2026): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v8i2.11798

Abstract

Tuberculosis (TB) is an infectious disease that affects the lungs and can spread through the air. Indonesia ranks second globally, contributing approximately 10% of the total TB cases worldwide. The Province of Nusa Tenggara Barat (NTB) has been recorded as having a high number of TB cases, with the City of Mataram being one of the areas with the highest incidence. Although TB can be cured through anti-tuberculosis drug (OAT) treatment for six months, the success rate of this treatment has declined since 2016. Several factors such as age, gender, education level, and other health conditions may influence treatment success. Therefore, evaluating treatment outcomes is very important, including monitoring the results of treatment to determine whether the treatment is successful or unsuccessful. In order to classify TB treatment failure, an effective statistical method that can be used is Multivariate Adaptive Regression Splines (MARS). MARS is a flexible nonparametric regression method capable of handling high-dimensional data, making it very useful for classifying data with many predictor variables. This study aims to classify TB treatment failure in the City of Mataram using the MARS method, with the expectation of improving treatment success in the region. Based on the analysis using the MARS method, the type of TB (X₅) was found to be the main determining variable of treatment outcomes, with a fairly good overall classification accuracy of 80%.
Pemodelan Tingkat Pengangguran Terbuka di Indonesia Menggunakan Analisis Regresi Data Panel Ena Setiawana; Nurul Fitriyani; Lisa Harsyiah
Eigen Mathematics Journal Vol 7 No 1 (2024): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i1.184

Abstract

Indonesia has entered the peak of the demographic bonus which can provide positive and negative impacts for various fields. One of them is in the economic field, namely the increasing number of productive population who are unabsorbed in the world of work and is referred to as an open unemployment. This research was conducted to build a model and to analyze the Open Unemployment Rate, Economic Growth, Provincial Minimum Wage, Level of education, Population growth, Labor Force Participation Rate, Employment, Human Development Index, Poor Residents, Illiterate Population, Average Length of School, Domestic Investment, Foreign Investment, and School Participation Rate, that influence the open unemployment rate in Indonesia using panel data regression analysis with data 2015-2021 from 34 provinces. A fixed effect model with different intercept values for every participant is the best panel data regression model (Fixed Effect Model) that could be found. Based on simultaneously research, it was discovered that every component of the model significantly effect the open unemployment rate. Partially, it was discovered that the following factors significantly effect the open unemployment rate in Indonesia: Employment, Labor Force Participation Rate, Economic Growth, Population Growth, Human Development Index, Poor Population, and Average years of Schooling.
Co-Authors Abdurahim, Abdurahim Adis Tia Juli Agil Asri Adis Tia Juli Agil Asri Agus Kurnia Alfarez, Dzaki Ade 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 Dina Eka Putri Eka Putri, Dina Emmy Dyah Sulistiowati Emmy Dyah Sulistyowati, Emmy Dyah Ena Setiawana Evita, Isma 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 Jihadil Qudsi 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 Sabina, Sabna Zulfaa Sahdan, Sahdan Salwa Salwa Saputra, Dede Saputri, Intan Editia Sari, Baiq Desi Nurma Sari, Kurnia Mahraini Kartika Siti Soraya Sulpaiyah Sulpaiyah Syaftirridho Putri Syamsul Bahri Syamsul Bahri Tajalli, Halawatun Tri Maryono Rusadi Yarti, Suwindah Puji Yuliana Lestari Zindawi, M. Daffa Rizki Zulhan Widya Baskara