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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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The Decision on Selecting the Best Laptop Using Analytical Hierarchy Process and Simple Additive Weighting Method at the Faculty of MIPA University of Mataram Fadhilah, Rifdah; Harsyiah, Lisa; Robbaniyyah, Nuzla Af’idatur
Eigen Mathematics Journal Vol 7 No 2 (2024): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v7i2.231

Abstract

Laptops have the potential to increase educational productivity in Indonesia. For example, students at the Faculty of Mathematics and Natural Sciences (MIPA) at the University of Mataram now feel involved. However, the decision to choose the right laptop according to the needs of students is difficult. The research population used was active students from the class of 2020-2023, Faculty of Mathematics and Natural Sciences (MIPA), University of Mataram. This research aims to determine the best laptop selection based on alternative laptop brands, namely Asus Vivobook, Acer 3, HP 14S, Dell Vostro 14, and Lenovo IP1. Further criteria include price, processor, Random Access Memory (RAM), Read Only Memory (ROM), and screen size. The methods used are the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The research results show that the first priority position is filled by the Asus Vivobook with a weight of 0,26 for the AHP method and the Lenovo IP1 with a weight of 0,898 for the SAW method. The results of priority comparisons using euclidean distance, it was found that the most optimal method for deciding on the best laptop was the AHP method. The AHP method has a value closest to 0 (zero), namely with an average value of 0,127, while the SAW method has an average value of 0,798.
Pengenalan Data Science Untuk Mempersiapkan Era Digital Pada Siswa Di SMAN 1 Gunung Sari Dina Eka Putri; Baskara, Zulhan; Lisa Harsyiah; Agus Kurnia; Nur Asmita Purnamasari; Mustika Hadijati; Lilik Hidayati; Helmina Andriani; Jihadil Qudsi; Hafizah Ilma; Adis Tia Juli Agil Asri; Yuliana Lestari; Jihan Melani; Rifdah Fadhilah; M. Syahrul; M. Naoval Husni
Jurnal Pengabdian Magister Pendidikan IPA Vol 7 No 4 (2024): Oktober-Desember 2024
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmpi.v7i4.9022

Abstract

The Fourth Industrial Revolution and Society 5.0 have created a demand for technology-based skills, including Data Science. This community service program aimed to introduce Data Science concepts to students at SMAN 1 Gunung Sari, preparing them for the digital era. Through interactive training sessions covering Data Science basics, data analysis simulations, and career discussions, both students and teachers gained essential foundational knowledge. The results showed an increase in students' knowledge and motivation towards STEM fields, as well as new skills for teachers in integrating data-driven learning. This program also strengthened the school's profile as an institution proactive in preparing students for future technological challenges.
PERBANDINGAN ANALISIS DISKRIMINAN DAN NAIVE BAYES DALAM PENGKLASIFIKASIAN STATUS PENERIMA BANTUAN PROGRAM KELUARGA HARAPAN DI NTB HARSYIAH, LISA; HADIJATI, MUSTIKA; FITRIYANI, NURUL
Jurnal Matematika UNAND Vol 13, No 4 (2024)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.13.4.296-308.2024

Abstract

Permasalahan dalam penyaluran bantuan sosial PKH adalah ketidak tepatan penyaluran bantuan PKH. Upaya yang dapat dilakukan untuk mengatasi per masalahan tersebut adalah dengan memastikan kriteria penerimaan bantuan PKH su dah benar dan sesuai dengan kriteria KPM. Berdasarkan kriteria KPM, perlu dilakukan klasifikasi status rumah tangga penerima bantuan PKH dan yang tidak. Hal ini di lakukan dengan tujuan untuk mengetahui apakah bantuan sosial PKH yang disalurkan tepat sasaran atau tidak. Proses klasifikasi dapat dilakukan dengan menggunakan anal isis diskriminan dan metode Na¨ıve Bayes. Hasil penelitian menunjukkan bahwa ketika melakukan klasifikasi menggunakan analisis diskriminan terhadap status penerima ban tuan PKH di NTB diperoleh tingkat kesalahan klasifikasi sebesar 24,5%. Sedangkan hasil klasifikasi menggunakan metode Na¨ıve Bayes memperoleh tingkat kesalahan sebe sar 27,6%. Hasil pengklasifikasian status penerima bantuan PKH dengan menggunakan kedua metode ini tergolong akurat dan analisis diskriminan memiliki kinerja yang lebih baik dibandingkan metode Na¨ ıve Bayes untuk kasus pengklasifikasian status penerima bantuan PKH di NTB
PERBANDINGAN ANALISIS DISKRIMINAN DAN NAIVE BAYES DALAM PENGKLASIFIKASIAN STATUS PENERIMA BANTUAN PROGRAM KELUARGA HARAPAN DI NTB HARSYIAH, LISA; HADIJATI, MUSTIKA; FITRIYANI, NURUL
Jurnal Matematika UNAND Vol. 13 No. 4 (2024)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.13.4.296-308.2024

Abstract

Permasalahan dalam penyaluran bantuan sosial PKH adalah ketidak tepatan penyaluran bantuan PKH. Upaya yang dapat dilakukan untuk mengatasi per masalahan tersebut adalah dengan memastikan kriteria penerimaan bantuan PKH su dah benar dan sesuai dengan kriteria KPM. Berdasarkan kriteria KPM, perlu dilakukan klasifikasi status rumah tangga penerima bantuan PKH dan yang tidak. Hal ini di lakukan dengan tujuan untuk mengetahui apakah bantuan sosial PKH yang disalurkan tepat sasaran atau tidak. Proses klasifikasi dapat dilakukan dengan menggunakan anal isis diskriminan dan metode Na¨ıve Bayes. Hasil penelitian menunjukkan bahwa ketika melakukan klasifikasi menggunakan analisis diskriminan terhadap status penerima ban tuan PKH di NTB diperoleh tingkat kesalahan klasifikasi sebesar 24,5%. Sedangkan hasil klasifikasi menggunakan metode Na¨ıve Bayes memperoleh tingkat kesalahan sebe sar 27,6%. Hasil pengklasifikasian status penerima bantuan PKH dengan menggunakan kedua metode ini tergolong akurat dan analisis diskriminan memiliki kinerja yang lebih baik dibandingkan metode Na¨ ıve Bayes untuk kasus pengklasifikasian status penerima bantuan PKH di NTB
Peranan Statistika di Era Transformasi Digital untuk Agen Perubahan di SMAN 1 Gunungsari Lombok Barat Zulhan Widya Baskara; Purnamasari, Nur Asmita; Mustika Hadijati; Lilik Hidayati; Desy Komalasari; Zulhan Widya Baskara; Lisa Harsyiah; Jihadil Qudsi; Helmina Andriani; Dina Eka Putri; Fara Fid
Jurnal Pengabdian Magister Pendidikan IPA Vol 8 No 1 (2025): Januari-Maret 2025
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpmpi.v8i1.10423

Abstract

The digital transformation era and technological advancements demand rapid adaptability from human resources, including the increasingly important utilization of data science across various industries. Statistics, as a core component of data science, plays a crucial role in transforming data into valuable information for decision-making. Considering the significance of statistical analysis, this skill has become one of the most sought-after in today's industrial world, especially for the younger generation, such as high school students, who will become agents of change in the future. Community service activities at SMA Negeri 1 Gunungsari, Lombok Barat, aim to enhance students understanding of the role of statistics in the digital transformation era. These activities include raising awareness about the importance of statistics in career choices and the application of statistical tools in digital contexts. Furthermore, the material delivered also covers how statistics can be used as a tool to address future industrial challenges. The evaluation of this activity shows an increase in students understanding, as evidenced by the post-test results, which show significant improvement compared to the pre-test. This demonstrates that raising awareness about statistics is effective in equipping students with relevant skills in the digital era. Therefore, similar activities are expected to be implemented in other schools to strengthen students readiness to utilize statistics as agents of change in the digital transformation era.
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/semeton.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 Zulhan Widya Baskara; 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.
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 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 Hidayatullah, Azka Fariz Hidayatullah, Azka Farris Hisan, Khairatun Inarah, Filzah 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 Salwa Salwa Salwa Salwa Saputra, Dede Saputri, Intan Editia Sari, Baiq Desi Nurma Sari, Kurnia Mahraini Kartika Setiawana, Ena 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