Vol. 5 No. 1 Juni 2022

Published: 2022-06-21

DOI: https://doi.org/10.29303/emj.v5i1

Articles

Application of the Poverty Equivalent Growth Rate (PEGR) Method (Case Study: Household Income Group in South Sulawesi 2016-2018)

Andy Rezky Pratama Syam, Badan Pusat Statistik, Indonesia

1-6
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DOI : https://doi.org/10.29303/emj.v5i1.125
Analysis of Bottled Water Quality Control Using the FMEA Method and the Application of Kaizen (Case Study at PT. Lombok Pusaka Adam, Jelantik, Central Lombok)

Lailatul Pahmi, Program Studi Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Mataram, Indonesia

Emmy Dyah Sulistiowati, Program Studi Teknik Mesin, Fakultas Teknik, Universitas Mataram, Indonesia

Lisa Harsyiah, Program Studi Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Mataram, Indonesia

7-14
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DOI : https://doi.org/10.29303/emj.v5i1.126
Factor Analysis for Mapping Characteristics in Robusta Coffee Decaffeination Experiments

Zulhan Widya Baskara, Program Studi Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Mataram, Indonesia

Lisa Harsyiah, Program Studi Matematika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Mataram, Indonesia

Dewa Nyoman Adi Paramartha, Program Studi Ilmu dan Teknologi Pangan, Fakultas Teknologi Pangan dan Agroindustri, Universitas Mataram, Indonesia

Qabul Dinanta Utama, Program Studi Ilmu dan Teknologi Pangan, Fakultas Teknologi Pangan dan Agroindustri, Universitas Mataram, Indonesia

15-20
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DOI : https://doi.org/10.29303/emj.v5i1.139
Rice Production Forecasting using Exponential Smoothing Method

Khalilah Nurfadilah, Program Studi Matematika, Fakultas Sains dan Teknologi, Universitas Islam Negeri Alauddin Makassar, Indonesia

Adnan Sauddin, Program Studi Matematika, Fakultas Sains dan Teknologi, Universitas Islam Negeri Alauddin Makassar, Indonesia

Winda Saputri, Program Studi Matematika, Fakultas Sains dan Teknologi, Universitas Islam Negeri Alauddin Makassar, Indonesia

21-26
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DOI : https://doi.org/10.29303/emj.v5i1.127
The Prime Submodule Of The Integer Module Over Itself

Muhammad Rijal Alfian, Program Studi Matematika, FMIPA, Universitas Mataram, Indonesia

Fariz Maulana, Department of Mathematics, Institut Teknologi Bandung, Indonesia

Ni Wayan Switrayni, Program Studi Matematika, FMIPA, Universitas Mataram, Indonesia

Qurratul Aini, Program Studi Matematika, FMIPA, Universitas Mataram, Indonesia

Dwi Noorma Putri, Fakultas Pertanian, Universitas Mataram, Indonesia

I Gede Adhitya Wisnu Wardhana, Program Studi Matematika, FMIPA, Universitas Mataram, Indonesia

27-30
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DOI : https://doi.org/10.29303/emj.v5i1.132
Comparison of the Trend Moment and Naive Methods in Forecasting Gross Regional Domestic Product in Blitar Regency

Umi Habibah, Program Studi Matematika, Fakultas Ilmu Eksakta, Universitas Nahdlatul Ulama Blitar, Indonesia

Rizka Rizqi Robby, Program Studi Matematika, Fakultas Ilmu Eksakta, Universitas Nahdlatul Ulama Blitar, Indonesia

M. Nurhaqqul Qomaruddin, Program Studi Matematika, Fakultas Ilmu Eksakta, Universitas Nahdlatul Ulama Blitar, Indonesia

31-36
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DOI : https://doi.org/10.29303/emj.v5i1.121
Classification of Poverty Status using the Random Forest Algorithm

Syaidatussalihah, Politeknik Medica Farma Husada Mataram, Indonesia

Abdurahim, Politeknik Medica Farma Husada Mataram, Indonesia

37-44
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DOI : https://doi.org/10.29303/emj.v5i1.133

Vol. 5 No. 1 Juni 2022

Articles

Application of the Poverty Equivalent Growth Rate (PEGR) Method (Case Study: Household Income Group in South Sulawesi 2016-2018)

Analysis of Bottled Water Quality Control Using the FMEA Method and the Application of Kaizen (Case Study at PT. Lombok Pusaka Adam, Jelantik, Central Lombok)

Factor Analysis for Mapping Characteristics in Robusta Coffee Decaffeination Experiments

Rice Production Forecasting using Exponential Smoothing Method

The Prime Submodule Of The Integer Module Over Itself

Comparison of the Trend Moment and Naive Methods in Forecasting Gross Regional Domestic Product in Blitar Regency

Classification of Poverty Status using the Random Forest Algorithm