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Analisis Cluster Untuk Pengelompokan Provinsi Di Indonesia Berdasarkan Tingkat Kemiskinan Menggunakan Metode Average Linkage Dede Saputra; Azrianti Ardania; Syaftirridho Putri; Adis Tia Juli Agil Asri; Lisa Harsyiah
Indonesian Journal of Applied Statistics and Data Science Vol. 1 No. 1 (2024): November
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v1i1.5446

Abstract

Poverty is a major economic and social issue in Indonesia because it is a serious problem that can affect social welfare. Poverty is influenced by many factors including school enrollment rate, life expectancy, gross regional domestic product, human development index and open unemployment rate. Cluster analysis is a technique in multivariate statistics where objects are grouped based on proximity or similarity of properties so that objects that have close proximity (similar properties) will be in the same group (cluster). The purpose of this study is to cluster provinces in Indonesia based on poverty levels using the average linkage method. The results of this study obtained 5 clusters, where cluster 1 consists of Nanggroe Aceh Darussalam, North Sumatra, West Sumatra, Riau, Jambi, South Sumatra, Bengkulu, Lampung, Bangka Belitung Islands, Central Java, East Java, Bali, West Nusa Tenggara, East Nusa Tenggara, West Kalimantan, Central Kalimantan, South Kalimantan, North Kalimantan, Central Sulawesi, South Sulawesi, Southeast Sulawesi, Gorontalo, West Sulawesi, Maluku, North Maluku and West Papua. Cluster 2 consists of Riau Islands, West Java, Banten and North Sulawesi. Cluster 3 consists of DKI Jakarta and East Kalimantan. Cluster 4 consists of DI Yogyakarta and the last cluster consists of Papua.
Pengendalian Kualitas Produk Spon Kasur Menggunakan Exponentially Weighted Moving Average (Ewma) pada UD. Celcius Gegutu Timur Lingking, Fransiska Prisilia; Harsyiah, Lisa; Sulistyowati, Emmy Dyah; Asri, Adis Tia Juli Agil
Semeton Mathematics Journal Vol 2 No 1 (2025): April
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/smj.v2i1.273

Abstract

Problems that arise at UD. Celsius, one of the manufacturers of sponge mattress products in the East Gegutu area, said that differences in product weight will cause a decrease in product quality. Consequently, here, quality is of primary concern. Because the Exponentially Weighted Moving Average (EWMA) control chart can detect small average changes, this study aims to examine the quality control of mattress sponge products using this chart. The information used relates to the mass of a mattress sponge product measuring 160×120×25 cm, with four variables, namely X_1,X_2,X_3 and X_4, Quality control in this research uses a weighting factor value of  = 0.4. Based on the research results, the assumption that is not fulfilled is the assumption of data randomness, so that the EWMA control chart pattern formed shows that the data is not statistically controlled. However, there is no data that is out of control, so in this study the Average Run Length (ARL) value of 27,204 indicates that there will be data that is first out of control, namely the 27th or 28th data. And the results of the capability analysis of the process show that the production process is not capable because the values of Cp=0.3432 and Cpk=0.3373 where the values of Cp,Cpk<1, this is due to the influencing factors, namely man, machine, material and method factors.
Analysis of Factors that Influence Poverty in West Nusa Tenggara Using Principal Component Regression Harsyiah, Lisa; Baskara, Zulhan Widya; Putri, Dina Eka; Fadhilah, Rifdah
Eigen Mathematics Journal Vol 8 No 1 (2025): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i1.229

Abstract

West Nusa Tenggara (NTB) is one of the provinces in Indonesia with a percentage of poor people according to the March-September period in 2019, namely 14.56% -13.88%, while in 2020 it was 13.97% -14.23% and in 2021 the percentage was 14.14% -13.83%. The factors suspected of influencing poverty in each province have different conditions each year, so repeated observations are needed on poverty data and the factors that influence it. If the data contains multicollinearity, then one of the classic assumptions of multiple linear regression is not met so that the problem of multicollinearity needs to be addressed. The Principal Component Regression (PCR) method is the most consistent compared to the ridge and least square regression methods in solving multicollinearity problems. This study aims to analyze poverty in NTB using the PCR method. The data used in this study are the number of poor people and factors influencing poverty based on districts in NTB in 2020-2022. Based on the calculation results, it was obtained that Component 1 with an eigenvalue of 4.008 explained 57.2% of the variance, while Component 2 with an eigenvalue of 1.740 explained 82.1% of the variance. Both components significantly affect poverty according to the results of simultaneous and partial tests. This model has an R^2 value of 0.302 or 30.2% and the remaining 69.8% is influenced by external factors (error). The R^2 value is classified as a weak category and it is recommended to add other factors that affect poverty including access to electricity, access to sanitation, access to clean drinking water, and government spending.
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.
COMPARATIVE ANALYSIS OF FUZZY TIME SERIES CHEN AND MARKOV CHAIN METHODS FOR FORECASTING ELECTRICITY CONSUMPTION IN MATARAM CITY Nirwanto, Nirwanto; Bahri, Syamsul; Harsyiah, Lisa
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2375-2386

Abstract

The consumption of electrical energy continues to experience fluctuations every month, and these fluctuations cannot be accurately predicted. This uncertainty can become a problem if not projected and planned effectively. Therefore, PT PLN (Persero) needs to be able to provide and distribute electricity supply in an appropriate amount. This research aims to forecast electricity consumption based on historical data from January 2016 to April 2023 using the Fuzzy Time Series Chen (FTSC) method and the Fuzzy Time Series Markov Chain (FTSMC) method. The results of this research show that the forecast for May 2023 using the FTSC and FTSMC methods are 136.878.489 kWh and 143.498.523 kWh, respectively, with MAPE values of 11.61739% and 4.85428%, respectively. Therefore, forecasting in May 2023 using the FTSMC method is better than the FTSC method because the MAPE value is smaller.
Klasifikasi Status Penerima Bantuan Program Keluarga Harapan di Provinsi NTB Menggunakan Metode Regresi Probit Harsyiah, Lisa; Widya Baskara, Zulhan; Eka Putri, Dina; Jurniati, Jurniati
Mandalika Mathematics and Educations Journal Vol 7 No 3 (2025): Edisi September
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i3.9776

Abstract

The Indonesian government's effort to accelerate the achievement of comprehensive social welfare involves adopting strategic policies in the form of distributing social assistance to economically vulnerable communities. One concrete example of this policy is the Family Hope Program (Program Keluarga Harapan/PKH). However, its implementation in the field still faces challenges, particularly in the form of unequal distribution, which has the potential to hinder the program’s effectiveness. To address this issue, a rigorous verification system is required to ensure that prospective beneficiaries truly meet the official criteria set by the government. Therefore, classifying households eligible for PKH is a crucial step. The probit regression approach is employed as a method to analyze and determine the household eligibility status. This method yields an accuracy rate of 76.25%, which is considered valid and reliable based on the Press’s Q statistic
Pelatihan Pembuatan Media Pembelajaran Matematika Interaktif Berbasis Microsoft Powerpoint di MA Attamimy Lombok Tengah Fitriyani, Nurul; Hadijati, Mustika; Harsyiah, Lisa; Baskara, Zulhan Widya
Jurnal Pengabdian Masyarakat Sains Indonesia (Indonesian Journal Of Science Community Services) Vol. 3 No. 2 (2021)
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmsi.v3i2.147

Abstract

Madrasah Aliyah (MA) Attamimy adalah yang berada di bawah naungan Yayasan Pondok Pesantren Attamimy. MA Attamimy ini memiliki visi dan misi untuk melahirkan manusia-manusia yang berimtaq, berakhlak mulia, serta mampu bersaing menghadapi tantangan zaman global. Pada dasarnya, MA Attamimy ini telah memilki fasilitas komputer beserta akses internet yang cukup memadai, namun penggunaannya belum digunakan secara maksimal. Masalah lain yang juga terjadi adalah munculnya istilah mathematics phobia di kalangan siswa di MA Attamimy. Beberapa kesan negatif mengenai ilmu sains dan matematika ini mengharuskan penyampaian materi dan proses pembelajaran di kelas harus dikemas semenarik mungkin. Tujuan dilakukannya kegiatan Pengabdian kepada Masyarakat ini adalah dalam rangka pemanfaatan internet dan Microsoft PowerPoint dalam membuat media pembelajaran yang interaktif. Berdasarkan kegiatan Pengabdian kepada Masyarakat yang dilakukan di MA Attamimy, perlu untuk dilakukan kegiatan lanjutan sebagai bentuk kesinambungan kegiatan. Microsoft PowerPoint sendiri telah dimanfaatkan dalam membuat media pembelajaran interaktif oleh peserta kegiatan Pengabdian kepada Masyarakat, hanya saja perlu ditingkatkan pemanfaatan fitur-fitur, salah satunya fitur hyperlink, sehingga dapat meningkatkan kualitas pembelajaran.