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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Statistika Universitas Muhammadiyah Semarang AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Kreativitas PKM Jurnal Aplikasi Statistika & Komputasi Statistik METIK JURNAL Variance : Journal of Statistics and Its Applications Jurnal Varian Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Mandalika Mathematics and Educations Journal Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Journal of Mathematics Education and Science Mathematics and Applications (MAp) Journal VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Research Applications in Community Services Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Progressive Physics Journal Eksponensial Journal of Mathematics, Computation and Statistics (JMATHCOS) IJASDS: Indonesian Journal of Applied Statistics and Data Science

Memi Nor Hayati

Universitas Mulawarman

Author-ID : 278791

Religion Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Pelatihan Penulisan Karya Tulis Ilmiah Untuk Mendorong Peningkatan Kualitas Siswa Tingkat SMA Ika Purnamasari; Memi Nor Hayati; Desi Yuniarti
Aksiologiya: Jurnal Pengabdian Kepada Masyarakat Vol 4, No 2 (2020): Agustus
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/aks.v4i2.3565

Karya tulis ilmiah (KTI) merupakan karya ilmiah yang ditulis dengan mengikuti kaidah ilmiah. Kaidah ilmiah sebagai syarat utama dalam penulisan sebuah karya dimaksudkan agar karya yang dihasilkan dapat dipertanggung jawabkan secara ilmiah. Tujuan kegiatan pelatihan penulisan karya tulis ilmiah yaitu menumbuhkan minat, semangat, serta ide kreatif dan inovatif dari siswa-siswi kelas X dan XI SMAN 5 Samarinda untuk menghasilkan sebuah karya ilmiah yang sesuai dengan kaidah penulisan. Berdasarkan hasil pelaksanaan kegiatan pelatihan dapat disimpulkan bahwa kegiatan berjalan dengan baik dan mendapat dukungan penuh dari pihak sekolah. Seluruh peserta pelatihan mengikuti kegiatan hingga akhir dengan tingkat kehadiran sebesar 100%. Peserta kegiatan antusias untuk bertanya, mengeksplorasi ide, serta mengemukakan pendapat. Dengan demikian, kedepannya diharapkan adanya kegiatan lanjutan dengan melibatkan guru pendamping untuk mengoptimalkan perannya dalam penyusunan karya tulis ilmiah bagi peserta didik.Kata Kunci: kaidah ilmiah; KTI; peserta didik. Training on Writing Scientific Papers to Encourage Quality Improvement of High School Level Students ABSTRACT The scientific paper is an essay written by following scientific rules that are the main requirement so that the resulting essay can be justified scientifically. The purpose of the training is to increase the interest, enthusiasm, creative, and innovative ideas from students of class X and XI of SMAN 5 Samarinda to create a scientific paper that is following the rules. Based on the implementation of the training, it can be concluded that it is run well and received support from the school. All participants follow this activity until the end with an attendance rate of 100%. They are enthusiastic to ask, explore, and express their ideas and opinions. Then, in the future, it is expected that there will be further activities involving the teachers to optimization the role of assistants to create their student’s scientific papers.Keywords: scientific paper; scientific rules; students.

PENGELOMPOKAN KABUPATEN/KOTA DI PULAU KALIMANTAN BERDASARKAN INDIKATOR KESEJAHTERAAN RAKYAT MENGGUNAKAN METODE FUZZY C-MEANS DAN SUBTRACTIVE FUZZY C-MEANS Nur Annisa Fitri; Memi Nor Hayati; Rito Goejantoro
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 1 (2021): September 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i1.14416

Cluster analysis has the aim of grouping several objects of observation based on the data found in the information to describe the objects and their relationships. The grouping method used in this research is the Fuzzy C-Means (FCM) and Subtractive Fuzzy C-Means (SFCM) methods. The two grouping methods were applied to the people's welfare indicator data in 42 regencies/cities on the island of Kalimantan. The purpose of this study was to obtain the results of grouping districts/cities on the island of Kalimantan based on indicators of people's welfare and to obtain the results of a comparison of the FCM and SFCM methods. Based on the results of the analysis, the FCM and SFCM methods yield the same conclusions, so that in this study the FCM and SFCM methods are both good to use in classifying districts/cities on the island of Kalimantan based on people's welfare indicators and produce an optimal cluster of two clusters, namely the first cluster consisting of 10 Regencies/Cities on the island of Kalimantan, while the second cluster consists of 32 districts/cities on the island of Borneo.

Forecasting Stock Price PT. Telkom Using Hybrid Time Series Regression Linear– Autoregressive Integrated Moving Average Model Kartika Ramadani; Sri Wahyuningsih; Memi Nor Hayati
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 2 (2022): JANUARY 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i2.18837

The hybrid method is a method of combining two forecasting models. Hybrid method is used to improve forecasting accuracy. In this study, the Time Series Regression (TSR) linear model will be combined with the Autoregressive Integrated Moving Average (ARIMA) model. The TSR linear model is used to obtain the model and residual value, then the residual value of the TSR linear model will be modeled by the ARIMA model. This combination method will produce a hybrid TSR linear-ARIMA model. The case study in this research is stock closing price (daily) of PT. Telkom Indonesia Tbk. The stock closing price (daily) of PT. Telkom Indonesia Tbk in 2020 showed an decreasing and increasing trend pattern. The results of this study obtained the best model of hybrid TSR linear-ARIMA (2,1,1) with the proportion of data training and testing is 70:30. In the best model, the MAD value is 56.595, the MAPE value is 1.880%, and the RMSE value is 78.663. It is also found that the hybrid TSR linear-ARIMA model has a smaller error value than the TSR linear model. The results of forecasting the stock price of PT. Telkom Indonesia Tbk for the period 02 January 2021 to 29 January 2021 formed a decreasing trend pattern.

Metode Quick Count dan Analisis Autokorelasi Spasial Menggunakan Indeks Moran (Studi Kasus: Pemilihan Presiden Indonesia Tahun 2019 di Kalimantan Timur) Riska Veronika; Memi Nor Hayati; Ika Purnamasari
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 8, No 2 (2020): Jurnal Statistika
Publisher : Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.8.2.2020.121-126

Quick count is a quick caculation method based on sampling that is used to show the results of the temporary vote before the official election results are published. Votes can be influenced by party bases in various regions, so the linkage of the results of vote acquisition between regions needs to be taken into account. Spatial autocorrelation is the correlation between variables and themselves based on space or region. This research has a goal to determine the difference between the results of the estimated vote acquisition using the quick count method with the results of the KPU vote and spatial autocorrelation using the Moran index to determine whether or not there is a spatial autocorrelation of the results of the vote acquisition in the presidential election. The data used is the vote acquisition data of each pair of presidential candidates in the 2019 Indonesian presidential election in East Kalimantan Province using stratified random sampling. The results of the difference between the estimated votes obtained by the quick count method and the KPU calculation is relatively small at 0.01% and from the results of the spatial autocorrelation test hypothesis it is known that there is no spatial autocorrelation of the results of the vote acquisition for each pair of Indonesian presidential candidates in 10 districts/cities in East Kalimantan in 2019.

PERBANDINGAN PERAMALAN METODE DOUBLE EXPONENTIAL SMOOTHING SATU PARAMETER BROWN DAN METODE DOUBLE EXPONENTIAL SMOOTHING DUA PARAMETER HOLT Julnita Bidangan; Ika Purnamasari; Memi Nor Hayati
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 4, No 1 (2016): Jurnal Statistika
Publisher : Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

Peramalan merupakan suatu proses atau metode dalam meramal suatu peristiwa yang akan terjadi pada masa yang akan datang. Pemulusan eksponensial adalah suatu metode peramalan rata-rata bergerak yang melakukan pembobotan menurun secara eksponensial terhadap nilai observasi yang lebih lama. Pada penelitian ini membahas tentang metode double exponential smoothing satu parameter dari Brown dan double exponential smoothing dua parameter dari Holt dalam meramalkan jumlah produksi air bersih Kota Samarinda. Metode double exponential smoothing satu parameter dari Brown dan double exponential smoothing dua parameter dari Holt merupakan metode extrapolasi atau deret waktu dengan menggunakan riwayat permintaan masa lalu dalam membuat ramalan untuk masa depan yang dijadikan panduan dalam proses pembuatan keputusan. Metode double exponential smoothing satu parameter dari Brown dengan parameter menghasilakn ramalan jumlah produksi air pada bulan November 2015 adalah 6.673,93 m3, bulan Desember 2015 adalah 6.728,11 m3, dan bulan Januari 2016 adalah 6.728,11 m3 dengan MAPE adalah 2,9629 %. Pada metode double exponential smoothing dua parameter dari Holt dengan parameter dan menghasilkan ramalan jumlah produksi air pada bulan November 2015 adalah 6.694,09 m3, bulan Desember 2015 adalah 6.831,22 m3, dan bulan Januari 2016 adalah 6.968,35 m3 dengan MAPE adalah 2,9016 %. Hasil yang diperoleh menunjukkan bahwa MAPE untuk metode double exponential smoothing dua parameter dari Holt dengan dan lebih kecil dibandingkan MAPE untuk metode double exponential smoothing satu parameter dari BrownKata Kunci : Double Exponential Smoothing Dua Parameter dari Holt, Double Exponential Smoothing Satu Parameter dari Brown, MAPE.

CATEGORIC DATA GROUPING BY ALGORITHM QUICK ROBUST CLUSTERING USING LINKS (QROCK) (Case Study: Status of Value Addrd Tax Payments at the Samarinda Ulu Primary Tax Office in 2018) Nana Nirwana; Memi Nor Hayati; Syaripuddin Syaripuddin
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 9, No 1 (2021): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.9.1.2021.18-27

Clustering is a method for finding and grouping data that have similar characteristics (similarity) between one data and another. The method of grouping used in this study is the Qrock Algorithm (Quick Robust Using Links).The Qrock Algorithm has a more efficient method to produce the final cluster when the Rock Algorithm has no link beetwen the clusters.The concept of the Qrock Algorithm basically has the same principles as the Rock Algorithm, except that the Qrock Algorithm classifies objects only based on the neighbors of each object. The purpose of this study was to classify 200 Value Added Tax Payment Status data at the Samarinda Ulu Tax Service Office in 2018. Based on the analysis results, the threshold value ( ) = 0.1; 0.2; 0.3; 0.4; 0, 5 and 0.6 produce 1 cluster while the threshold values ( ) = 0.7; 0.8 and 0.9 produce 56 clusters.

MIXED GEOGRAPHICALLY WEIGHTED MULTIVARIATE LINEAR MODEL Memi Nor Hayati; Purhadi -
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 2, No 2 (2014): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Model linier multivariat adalah model linier dengan variabel respon lebih dari satu. Geographically Weighted Multivariate Linier Model (GWMLM) merupakan pengembangan dari model linier multivariat, dimana variabel respon lebih dari dari satu dan informasi lokasi diketahui. Pada model linier multivariat hanya dihasilkan penaksir parameter yang berlaku secara global, sedangkan dalam GWMLM dihasilkan penaksir parameter model yang bersifat lokal untuk setiap titik pengamatan atau lokasi dimana data tersebut diperoleh. Akan tetapi, pada kenyataannya tidak semua variabel prediktor dalam GWMLM mempunyai pengaruh secara lokal. Beberapa variabel prediktor berpengaruh secara global, sedangkan yang lainnya dapat mempertahankan pengaruhnya secara lokal. Oleh karena itu dikembangkan suatu metode Mixed Geographically Weighted Multivariate Linier Model (MGWMLM) yang merupakan gabungan dari model linier multivariat dan GWMLM. Hasil penelitian menunjukkan bahwa penaksiran parameter MGWMLM dapat dilakukan dengan metode Weighted Least Square (WLS). Pemilihan bandwidth optimum digunakan metode Cross Validation (CV). Pengujian kesesuaian model regresi multivariat dan MGWMLM didekati dengan distribusi F begitu juga pada pengujian parameter MGWMLM secara serentak, sedangkan pengujian parameter MGWMLM secara parsial baik untuk parameter global dan parameter lokal menggunakan distribusi t.

ANALISIS DESKRIPTIF PADA FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT SISWA UNTUK MELANJUTKAN PENDIDIKAN KE TINGKAT PERGURUAN TINGGI Ika Purnamasari; Memi Nor Hayati
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 6, No 2 (2018): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

The success of human development in an area can be measured based on the level of education which is influenced by several factors, both internal and external. The mean years of schooling (MYS) are the basis for measuring the high level of education that affects the size of the Human Development Index (HDI). The aims of this study is to explore data based on internal and external factors that affect the interest of senior highschool students in the Penajam Paser Utara (PPU) to continue their education at college level. Exploration of data in this study was carried out using descriptive statistical analysis. Descriptive statistics are methods that are often used to process data and present it to be easier to understand, both in the form of diagrams and tables. Based on 292 respondents who are interested in continuing their study, it is known that the average levelof education of parents of respondents is still quite low. The level of education of parents affects the income level of parents, as many as 138 respondents have parents with an average income of one million to three million per month. Although the level of education and income of respondents parents is quite low, in fact, the ratio of respondents who areinterested in continuing their education to college institutions is 2.72 times greater than those of respondents who are not interested. Keyword : descriptive statistics, HDI, MYS, PPU.

KLASIFIKASI TINGKAT KELANCARAN NASABAH DALAM MEMBAYAR PREMI DENGAN MENGGUNAKAN METODE K-NEAREST NEIGHBOR DAN ANALISIS DISKRIMINAN FISHER (Studi kasus: Data Nasabah PT. Prudential Life Samarinda Tahun 2019) Amanah Saeroni; Memi Nor Hayati; Rito Goejantoro
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 8, No 2 (2020): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.8.2.2020.88-94

Classification is a technique to form a model of data that is already known to its classification group. The model that was formed will be used to classify new objects. The K-Nearest Neighbor (K-NN) algorithm is a method for classifying new objects based on their K nearest neighbor. Fisher discriminant analysis is a multivariate technique for separating objects in different groups to form a discriminant function for allocate new objects in groups. This research has a goal to determine the results of classifying customer premium payment status using the K-NN method and Fisher discriminant analysis and comparing the accuracy of the K-NN method classification and Fisher discriminant analysis on the insurance customer premium payment status. The data used is the insurance customer data of PT. Prudential Life Samarinda in 2019 with current premium payment status or non-current premium payment status and four independent variables are age, duration of premium payment, income and premium payment amount. The results of the comparative measurement of accuracy from the two analyzes show that the K-NN method has a higher level of accuracy than Fisher discriminant analysis for the classification of insurance customers premium payment status. The results of misclassification using the APER (Apparent Error Rate) in K-NN method is 15% while in Fisher discriminant analysis is 30%.

ANALISIS PENGARUH CURAH HUJAN DAN MORFOMETRI PADA PENINGKATAN DEBIT DAN SEDIMEN DI DAS KONTO HULU DENGAN PENDEKATAN MIXED GEOGRAPHICALLY WEIGHTED MULTUVARIATE LINIER MODEL Memi Nor Hayati; - Purhadi
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 3, No 1 (2015): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Metode Mixed Geographically Weighted Multivariate Linier Model (MGWMLM) yangmerupakan gabungan dari model linier multivariat dan GWMLM). Pemilihanbandwidth optimum digunakan metode Cross Validation (CV). Pengujian kesesuaianmodel regresi multivariat dan MGWMLM didekati dengan distribusi F begitu juga padapengujian parameter MGWMLM secara serentak, sedangkan pengujian parameterMGWMLM secara parsial baik untuk parameter global dan parameter lokalmenggunakan distribusi t. Aplikasi dari MGWMLM ini untuk mengetahui pengaruhcurah hujan dan morfometri DAS terhadap penentuan besarnya debit dan sedimentasiDAS Konto Hulu. Berdasarkan MGWMLM dengan pembobot fungsi kernel Gaussian,faktor-faktor yang mempengaruhi debit dan sedimen di DAS Konto Hulu secara lokaladalah luas sub DAS dan rata-rata kemiringan lahan. Sedangkan variabel curah hujanharian berpengaruh signifikan secara global pada seluruh lokasi pengamatan.Kata Kunci : MGWMLM, GWMLM, DAS.

Co-Authors - Purhadi Abda Abda Alifta Ainurrochmah Amanah Saeroni Anak Agung Gede Sugianthara Andi M. Ade Satriya Anjani Anjani Annabaa Aulia, Muzizah Asnita, Asnita Astuti, Putri Sri Cahyaningsih, Ariyanti Candra Dewi, Ni Luh Ayu Casuarina, Indah Putri Damayanti, Elok Dani, Andrea Tri Rian Darnah Darnah Darnah, Darnah Desi Yuniarti Deviyana Nurmin Dewi, Isma Diani, Milda Alfitri Dini Elizabeth Dwi Husnul Mubiin Edy Fahrin Emi Harmianti Eric Sapto Raharjo Fatma wati Fauzia, Rina Fauziyah, Meirinda Fidia Deny Tisna Amijaya Goenjatoro, Rito Hadisti, Zahrah Dhafina Hadistii, Zahrah Dhafiinia Hidayatullah, Aji Syarif Hisintus Suban Hurint Ibrahim, Rizky Nur Iim Masfian Nur Ika Purnamasari Ika Purnamasari Ika Puspita, Ika Ineu Sintia Julia Julia Julnita Bidangan Karima, Nabila Al Kartika Ramadani Khairun Nida Khasanah, Lisa Dwi Nurul Krisna Rendi Awalludin Lestari, Nur Aini Ayu Lili Widyastuti Lupinda, Indah Cahyani M. Fathurahman Mahmuda, Siti Marsandy, Aldwin Falah Hasan Masrawanti Masrawanti Meiliyani Siringoringo Messakh, Gerald Claudio Mochammad Imron Awalludin Muhammad Jainudin Nabilla, Maghrisa Ayu Nana Nirwana Nanda Arista Rizki Nida, Khairun Ningsih, Eva Lestari Nohe, Darnah Andi Nur - Azizah Nur Annisa Fitri Nur Azizah Nur Fajar Apriyani Nurmalia Purwita Yuriantari Nurmin, Deviyana Nurul Hidayah Oroh, Chiko Zet Paradilla, Yunda Sasha Pratama Yuly Nugraha Pratiwi, Reni Purhadi - Putri Ayu Dwi Lestari, Putri Ayu Dwi Putri, Nurlia Sucianti Rahmah, Putri Aulia Rahmaulidyah, Fatihah Noor Ramadani, Kartika Riska Veronika Rito Goejantoro, Rito Ronald Tediwibawa Safitri, Ranita Nur Sari, Devi Nur Endah Sa’diyah, Lita Vindiyatus Sekar Nur Utami Sembiring, Rinawati Sifriyani, Sifriyani Sinaga, Julia Oriana Siringoringo, Meiliyani Siti Mahmuda Siti Rahmah Binaiya Soraya, Raihana Sri Wahyuningsih Sri Wahyuningsih Sri Wahyuningsih Suerni, Widya - Sumartini Sumartini Surya Prangga Suyitno Suyitno Suyitno Suyitno Suyitno Suyitno Suyitno Suyono, Ari Krisna Syamsiar, Syamsiar Syaripuddin Syaripuddin Tiara Nur Hikmaulida Tiara Nurul Ma’ala Utami, Riska Putri Verawaty Bettyani Sitorus Wahyuni, Nanda Anggun Yuki Novia Nasution, Yuki Novia Yuniarti, Desi

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