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Harsyiah, Lisa
Program Studi Matematika, FMIPA, Universitas Mataram
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Pengendalian Kualitas Produksi Air Minum Dalam Kemasan Menggunakan Peta Kendali Zulhan Widya Baskara; Halifatunnisa, Nur; Baskara, Zulhan Widya; Harsyiah, Lisa
Semeton Mathematics Journal Vol 1 No 2 (2024): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v1i2.239

Abstract

The most popular drinking water product produced by PT.X is the 220 ml glass packaging product. This product experienced the most production defects at 0.086% of total production. Based on observations that have been made, there are several problems that cause defective products, such as damaged packaging and poor water quality. So PT.X in maintaining production quality must improve the process of maintaining quality control. The aim of this research is in line with the problems faced by PT.X, namely controlling the quality of bottled drinking water using a decision on belief control chart. Control charts are used to monitor whether product defect data is statistically controlled or not. One of the control charts used to monitor whether product defect data is statistically controlled or not is the Decision on Belief control chart, because the Decision on Belief control chart is more sensitive to data shifts so that faster in detecting data that goes outside control limits or is out of control. Based on the graph of the results of the decision on belief control chart, of the 25 data there are 24 data that are out of the upper control limit and the lower control limit, meaning that the decision on belief control chart is sensitive to data shifts in detecting out of control data. Based on the results of the average run length calculation, it is concluded that the decision on belief control chart is weak in detecting out of control data because the shift value obtained is getting bigger.
Pemodelan Angka Kematian Ibu (AKI) Di Indonesia Menggunakan Mixed Geographically Weighted Regression (MGWR) Lawwamah, Tamsilul; Harsyiah, Lisa; Aini, Qurratul
Semeton Mathematics Journal Vol 1 No 2 (2024): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v1i2.241

Abstract

Maternal Mortality Rate (MMR) is on of the targets for a  achieving the Sustainable Development Goals (SDGs). The aim of this research is to find the right model for estimating MMR and to look at the factors that influence MMR in Indonesia. Estimation were carried out using the Mixed Geographically Weigthed Regression (MGWR) model. The MGWR model is a combination of GWR and linear regression with variables that  having influence locally and some globally. The results obtained are that the MGWR model is superior the GWR model, because  the smallest AIC value for MGWR is 463,0564. Factors that have significant influence using the adaptive Gaussian kernel weighting are postpartum mothers (x4) , postpartum mothers receiving vitamin A (x5), giving Fe3 tablets to pregnant women (x6) ,  and handling obstetric complications (x7).
Peramalan Produksi Kedelai di Provinsi Nusa Tenggara Barat menggunakan Model Grey-Markov (1,1) Nurmaulia, Ananda Rizantia; Harsyiah, Lisa; Purnamasari, Nur Asmita; Jurniati, Jurniati
Semeton Mathematics Journal Vol 2 No 2 (2025): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i2.314

Abstract

The continuously increasing soybean imports are caused by the imblance in domestic soybean produstion. This indicates that nationalsoybean self-sufficiensy has not yet been achieved, as many soybean farmlands have now been converted to other commodities. This condition occurs in West Nusa Tenggara, Which is one of Indonesia’s nationalsoybean production centers. To understand future soybean production conditions, forecasting future soybean production in West Nusa Tenggara province using the grey_markov (1, 1) model. This model only requires minimal data for forecasting, which aligns with the limites research data available. The data used in this study is soybean production data from West Nusa Tenggara province. The research results show that in 2022, soybean production in West Nusa Tenggara province will decline, with the prediction demonstrating good accuracy as indicated by a MAPE value of 15.75%.
Pengendalian Kualitas Produksi Air Minum dalam Kemasan (AMDK) Menggunakan Diagram Kendali MCUSUM dan MEWMA Zulhan Widya Baskara; Sari, Kurnia Mahraini Kartika; Harsyiah, Lisa; Baskara, Zulhan Widya
Semeton Mathematics Journal Vol 2 No 2 (2025): Oktober
Publisher : Program Studi Matematika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/semeton.v2i2.324

Abstract

Quality control in the water production process at PT. X is an essential activity to ensure the quality of packaged drinking water (AMDK) is fit for consumption. Therefore, the water quality of PT. X production must always be closely monitored. To guarantee the safety of drinking water, it must meet microbiological, radioactive, Physical, and chemical requirements according to the regulations stipulated in the Indonesian Ministry of Health Regulation Number 2 of 2023. Quality control is performed using MEWMA and MCUSUM control charts since these control charts can detect shifts in the process mean. The results of applying MCUSUM and MEWMA control charts indicate that the water production quality is statistically out of control. After monitoring, it was found that PH is the most influential variable causing out-of-control situations. An ARL test was conducted to obtain a control chart with the best performance, where a smaller ARL value indicates better sensitivity in detecting shifts in the process mean. The MCUSUM control chart outperforms the MEWMA control chart, with an ARL value of  and parameters  and , compared to ARL MEWMA of with weighting parameter  and .
Pengklasifikasian 10 Kabupaten/Kota di Provinsi Nusa Tenggara Barat untuk Kasus Kemiskinan Tahun 2022 Menggunakan Analisis Cluster Metode K-Means Sabina, Sabna Zulfaa; Alfarez, Dzaki Ade; Graha, Syifa Salsabila Satya; Auladi, Muhammad Yuzaul; Lisa , Harsyiah; 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.v1i1.5415

Abstract

Poverty is a very serious problem for countries in the world, especially for developing countries like Indonesia. Poverty will have a big impact if it occurs in the long term with different factors. One province that is still in the spotlight for high levels of poverty is West Nusa Tenggara Province. Even though the number of poor people in West Nusa Tenggara Province has decreased, conditions of the ground show that there are still many people whose lives are far from decent. Therefore, the government must immediately find a solution to overcome the problem of poverty. To overcome cases of poverty in a region, we can group the characteristics of these regions based on poverty indicators into several clusters. Grouping in this case is carried out with data that will be analyzed using the K-Means cluster analysis method. So the results obtained by analysis using the K-Means cluster method for grouping 10 regencies/cities in West Nusa Tenggara Province based on poverty in 2022 formed 3 clusters, namely cluster 1 consisting of West Sumbawa Regency, Bima City and Mataram City, cluster 2 consisting of Bima Regency, Dompu Regency, West Lombok Regency, Central Lombok Regency, East Lombok Regency, and Sumbawa Regency, and cluster 3 consists of North Lombok Regency. Apart from that, the characteristics of each cluster were also obtained, namely cluster 1 containing the districts/cities with the highest PPM values. While RLS, AHH, and TPT have very high numbers in 2022, cluster 2 contains districts/cities that have quite low PPM, RLS, AHH, and TPT numbers in 2022, and cluster 3 contains a group of districts/cities with RLS, AHH, and TPT has quite low numbers compared to the high PPM in 2022.
Analisis Cluster Untuk Pengelompokan Provinsi Di Indonesia Berdasarkan Tingkat Kemiskinan Menggunakan Metode Average Linkage Saputra, Dede; Ardania, Azrianti; Putri, Syaftirridho; Asri, Adis Tia Juli Agil; Harsyiah, Lisa
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.
Regresi Komponen Utama dalam Mengatasi Multikolinieritas pada Faktor-Faktor yang Mempengaruhi Inflasi di Indonesia Ningrum, Salsabila Hadi Putri; Hisan, Khairatun; Ramdhani, Triana Putri; Luzianawati, Luzianawati; Zindawi, M. Daffa Rizki; Harsyiah, Lisa
Indonesian Journal of Applied Statistics and Data Science Vol. 2 No. 1 (2025): Mei
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v2i1.5827

Abstract

Inflation is a significant concern for a developing country like Indonesia. To effectively anticipate inflationary trends, it is essential to conduct statistical analysis to determine what factors can influence inflation. This study utilized Principal Component Regression (PCR) to address multicollinearity in the regression model linking inflation to various factors. The results revealed that transportation, food, electricity and household fuel factors positively correlate with inflation, while health, education and clothing show negative correlations. However, the resulting regression model proved to be inadequate, as evidenced by a very low R-square value. This highlights the necessity for further refinement of the model to provide better information in the context of inflation management in Indonesia.
Analisis Tren Sosial di Indonesia dengan Peta Kendali CUSUM (Studi Kasus: Perceraian, Kemiskinan, Pernikahan Dini, dan Tingkat Pendidikan) Navisah, Navisah; Fariha, Mawaddatul; Ranti, Ketrin Jupina; Astuti, Lita; Yarti, Suwindah Puji; Harsyiah, Lisa; Qudsi, Jihadil
Indonesian Journal of Applied Statistics and Data Science Vol. 2 No. 1 (2025): Mei
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijasds.v2i1.6909

Abstract

Social changes in Indonesia, in the last ten years, have attracted the attention of researchers, especially related to the problems of divorce, early marriage, education levels, and poverty. For example, early marriage is still a major problem in some places. BPS, in 2022, reported that the rate of early marriage in Indonesia was very high, from 16.23% in 2022 to 17.32% in 2023. Several studies have shown a correlation between poverty levels, education levels, and early marriage rates. One effective statistical approach to monitoring changes in trends in time data is the Cumulative Sum Control Chart (CUSUM). The CUSUM control chart method, social data trends can be analyzed longitudinally, detecting significant changes, and mapping the time and magnitude of the shifts that occur. A total of 36 data from 4 variables in the 2022-2024 range were processed using the R application to obtain the CUSUM control chart. The results obtained showed that the variables of education level and early marriage showed more data that was within the limits of the CUSUM constraint map, while the variables of divorce rate and poverty rate had a lot of data that was out of control, which occurred a lot in the months of 2023.
PERBANDINGAN METODE AVERAGE LINKAGE DAN K-MEANS DALAM MENGELOMPOKKAN PERSEBARAN PENYAKIT MULUT DAN KUKU DI INDONESIA Angelina; Harsyiah, Lisa; Purnamasari, Nur Asmita
Fraction: Jurnal Teori dan Terapan Matematika Vol. 4 No. 2 (2024): Fraction: Jurnal Teori dan Terapan Matematika
Publisher : Jurusan Matematika, Fakultas Teknik, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/fraction.v4i2.63

Abstract

The purpose of this study was to analyze the spread of Foot and Mouth Disease (FMD in Indonesia by using two different methods: average linkage and k-means. In addition, this study also aimed to determine the most effective method of classifying the distribution of FMD in Indonesia between the two methods used. The results of cluster validation showed that the optimal number of clusters formed in the average linkage method was 4, while in the k-means method, there were 3 clusters. The grouping with the average linkage method was better than the results of classifying with the k-means method, as the standard deviation ratio in the average linkage method was smaller at 0,035, compared to 0,258 in the k-means method. Therefore, it was concluded that the average linkage method was better than the k-means method in classifying the distribution of FMD in Indonesia.
Peningkatan Pemahaman Konsep Geometri melalui Visualisasi Sketsa Grafik Fungsi bagi Siswa Di SMA Negeri 1 Pujut Zulhan Widya Baskara; Abdurahim, Abdurahim; Robbaniyyah, Nuzla Af'idatur; Ramadhan, Hikmal Maulana; Hidayatullah, Azka Farris; Alfian, Muhammad Rijal; Bahri, Syamsul; Awalushaumi, Lailia; Syechah, Bulqis Nebula; Marwan, Marwan; Salwa, Salwa; Rusadi, Tri Maryono; Maharani, Andika Ellena Saufika Hakim; Harsyiah, Lisa; Baskara, Zulhan Widya; Satriyantara, Rio
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol. 5 No. 1 (2025): Juni
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v5i1.733

Abstract

Geometry is one of the fundamental topics in mathematics, playing a crucial role in understanding shapes, sizes, positions, and spatial relationships between objects. Mastery of this concept is essential; however, in practice, many students still struggle to grasp geometry material. This issue is also evident at SMA Negeri 1 Pujut, where several students demonstrate a low level of understanding of geometric concepts. In response to this problem, the aim of the research is a community service activity was carried out in the form of tutoring sessions focused on improving students' understanding of geometry. This activity employed a visualization approach through function graph sketches to help students better comprehend the interconnections between concepts in a more concrete way. Based on the evaluation results, data showed that 86.67% of students exhibited improved learning outcomes after participating in the activity. This achievement indicates that the instructional method used by the facilitators was quite effective and well-received by the majority of participants.
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