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All Journal AlphaMath: Journal of Mathematics Education UNEJ e-Proceeding AKSIOMA Indonesian Journal of Applied Statistics Seminar Nasional Teknologi Informasi Komunikasi dan Industri JISTech (Journal of Islamic Science and Technology) Journal on Education Jurnal PADI (Pengabdian mAsyarakat Dosen Indonesia) Jurnal Sintak Multi Proximity: Jurnal Statistika Universitas Jambi Limits: Journal of Mathematics and Its Applications
Gusmi Kholijah
Fakultas Sains Dan Teknologi, Universitas Jambi
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Social Sciences Other

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Prediksi Predikat Kelulusan Mahasiswa dengan Rantai Markov dan Faktor-Faktor yang Mempengaruhi Indeks Prestasi Mahasiswa Arfarani Rosalindari; Sufri Sufri; Gusmi Kholijah
AlphaMath : Journal of Mathematics Education Alphamath: Vol. 7, No. 1, May 2021
Publisher : Department of Mathematics Education, Universitas Muhammadiyah Purwokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/alphamath.v7i1.9919

Abstract

Students' Achievement Index (IP) changes each semester, both increase and decrease. This affects the GPA obtained by graduation. IP obtained by students in even semester is only influenced by IP in odd semester. Based on nature of Markov Chain, if there are past and future events, then future events are independent of past events and only tied to current events. Markov chain is used to analyze probability of IP change each semester and to predict the predicate of graduation with state space used, namely: satisfactory predicate with GPA of 2.00 - 2.75 to state 0, satisfactory predicate with GPA of 2.76 - 3, 24 becomes state 1, predicate is very satisfactory with GPA of 3.25 - 3.79 being state 2, and cumlaude predicate with GPA of 3.80 - 4.00 being state 3. This study aims to predict the predicate of student graduation and to analyze factors that have significant effect on IP. Dummy regression is used to analyze factors that have significant effect on IP with the factors studied, namely: campus facilities and infrastructure, friendship, organizational activeness, internet use, and money. Results showed that predicate of graduation with satisfactory predicate, GPA range of 2.00-2.75 was 0.56%, students who graduated with satisfactory predicate GPA range 2.76-3.24 was 7.39%, students who graduated with very satisfactory predicate, GPA ranges 3.25-3.79 was 54.18%, and students who graduated with cumlaude predicate ranged from GPA 3.80-4.00 was 37.87%. Factors that have significant effect on student GPA are activeness in the organization and use of the internet.
ESTIMASI TINGKAT KEMISKINAN PROVINSI JAMBI DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) Edi Saputra; gusmi kholijah; niken rarasati
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2019: SNTIKI 11
Publisher : UIN Sultan Syarif Kasim Riau

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Abstract

Kemiskinan salah satu penghambat dalam pembangunan, sehingga kemiskinan masuk dalam program yang harus diatasi. Pengentasan kemiskinan dapat dilakukan dengan melakukan berbagai program perbaikan ekonomi masyarakat. Sehingga dilakukanlah analisis faktor-faktor yang menyebabkan kemiskinan. Penyebab dari kejadian kemiskinan dikatakan sebagai variabel prediktor dan tingkat kemiskinan disebut sebagai variabel respon. Adanya hubungan pengaruh antara variabel respon dan variabel prediktor dinamakan dengan regresi. Kemudian penyebab dari tingkat kemiskinan ternyata tidak hanya dipengaruhi oleh variabel prediktor, tetapi lokasi dari daerah sangat mempengaruhi. Adanya keterhubungan antar lokasi ini dapat dianalisis dengan Geographically Weighted Regression (GWR). Hasil yang diperoleh yaitu variabel prediktor secara keseluruhan berpengaruh yaitu tidak ada ijazah SD, lulus SMP, lulus PT, upah minimum pendapatan, manfaat BPJS, besar konsumsi pangan dan papan, pendapatan per kapita. Jika dilihat dari nilai AIC dan RRS yang lebih kecil serta nilai  yang tinggi sebesar 95,95% maka model GWR dihasilkan lebih baik menganalisis tingkat kemiskinan di Provinsi Jambi.
MODEL REGRESI POISSON UNTUK PENDUGAAN FAKTOR-FAKTOR YANG MEMPENGARUHI COVID-19 DI PULAU SUMATERA Gusmi Kholijah; Niken Rarasati; Corry Sormin
UNEJ e-Proceeding 2022: E-Prosiding Seminar Nasional Matematika, Geometri, Statistika, dan Komputasi (SeNa-MaGeStiK)
Publisher : UPT Penerbitan Universitas Jember

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Abstract

Covid-19 which has hit various countries in the world has become a scary thing for people to do activities outside the home. So that to carry out community activities, they must follow the rules of the health protocol that have been set, such as wearing masks, washing hands and keeping a distance. Covid-19 cases that occur can be spread through interactions between infected people. The interaction between communities is not only carried out in each region, but can be carried out between provinces within a region. The extent of interaction between people at this time can lead to the easy spread of Covid-19 cases. So that the number of COVID-19 cases can appear in several areas. The existence of a relationship between several predictor variables that affect the response variable in the form of count data can be referred to as Poisson regression. The dominant factors that caused the large number of Covid-19 sufferers on the island of Sumatra were the population, poverty level, income, regional temperature, compliance with wearing masks and compliance with maintaining distance. Keyword: Covid 19, Poisson, Regression
Prediksi Harga Cabai Rawit Hijau di Kota Jambi Menggunakan Rantai Markov Ditya Ismi Budiarti; Gusmi Kholijah; Sherli Yurinanda; Bunga Mardhotillah
Multi Proximity: Jurnal Statistika Vol. 2 No. 1 (2023): Applied Statistics
Publisher : Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (507.224 KB) | DOI: 10.22437/multiproximity.v2i1.22528

Abstract

Harga bahan pokok seringkali mengalami perubahan yang bervariasi. Perubahan ini dapat dikategorikan seperti sangat rendah, rendah, sedang, tinggi dan sangat tinggi. Perubahan-perubahan yang terjadi pada harga bahan pokok bisa saja berubah-ubah dari periode ke-(n) sangat rendah dan periode ke-(n-1) rendah dan lainnya. Berdasarkan website Pusat Informasi Harga Pangan Strategis Nasional (PIHPS Nasional) pada Bulan Juli 2022 di Kota Jambi, harga cabai rawit hijau mengalami perubahan yang fluktuatif dari hari ke hari. Sehingga para pedagang/UMKM Kuliner yang membutuhkan cabai rawit hijau sedikit khawatir untuk persediaan cabai rawit hijaunya. Penelitian ini bertujuan untuk menentukan peluang transisi harga cabai rawit hijau dan peluang masing-masing state harga cabai rawit hijau tersebut saat kondisi steady state. Terdapat 5 state yang dipakai pada penelitian kali ini yaitu state 0 untuk mewakili harga sangat rendah, state 1 untuk mewakili harga rendah, state 2 untuk mewakili harga sedang, state 3 untuk mewakili harga tinggi dan state 4 untuk mewakili harga sangat tinggi. Berdasarkan hasil penelitian didapatkan bahwa Cabai rawit hijau memiliki peluang saat mencapai kondisi steady state untuk harga sangat rendah yaitu 19,4%; harga rendah yaitu 29%; harga sedang yaitu 25,8%; harga tinggi yaitu 22,6% dan harga sangat tinggi yaitu 3,2%.
Model Project Based Learning pada Mata Kuliah Metode Peramalan Gusmi Kholijah; Corry Sormin; Gusmanely Z
AKSIOMA : Jurnal Matematika dan Pendidikan Matematika Vol 14, No 2 (2023): AKSIOMA: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/aks.v14i2.16253

Abstract

Pendidikan tinggi memiliki tujuan terhadap capaian kualitas lulusan mahasiswa dalam bentuk sikap, keterampilan umum, keterampilan khusus dan pengetahuan. Pencapaian kualitas lulusan direalisasikan dalam mata kuliah yang diajarkan dalam perkuliahan yang dilaksanakan. Salah satunya dengan mengembangkan capaian pembelajaran mata kuliah melalui penelitian terhadap pembelajaran. Pembelajaran yang dilakukan harus menumbuhkan skill mahasiswa, sehingga pembelajaran yang diadakan berbasis kepada proyek. Pembelajaran dilakukan dengan proyek pada mata kuliah metode peramalan. Metode Peramalan memiliki capaian mata kuliah berupa keahlian dalam analisis data. Mata kuliah ini dapat dikerjakan dalam bentuk proyek pada topik analisis regresi sederhana, regresi berganda dan regresi dummy. Pelaksanaan proyek dikerjakan oleh mahasiswa dalam skema team-based yang dilaksanakan dalam bentuk tim. Kemudian mata kuliah ini juga dilaksanakan dalam bentuk penelitian dan pengembangan yang menghasilkan produk Capaian Pembelajaran Mata Kuliah, Silabus dan Kontrak Perkuliahan, Rencana Pembelajaran Semester, Rencana Tugas Project Mahasiswa atau Lembar Kerja Project Mahasiswa, Lembar Penilaian Hasil Belajar sesuai dengan model pembelajaran berbasis proyek, soal ujian serta rubrik penilaian yang telah di-review. Kemudian hasil evaluasi melalui indikator motivasi belajar dan indikator aktivitas belajar mahasiswa diperoleh bahwa persepsi yang baik terhadap kegiatan model pembelajaran Metode Peramalan menggunakan projek. Hasil angket persepsi tersebut dianalisis dengan uji reliabilitas, didapatkan nilai cronbach’s alpha sebesar 0,799. Nilai ini mengartikan bahwa reliabilitas mata kuliah metode peramalan tinggi. Hal ini menyampaikan bahwa angket persepsi mahasiswa terhadap mata kuliah metode peramalan tinggi.
PELATIHAN ANALISIS REGRESI DENGAN SOFTWARE STATISTIK UNTUK MENINGKATKAN KUALITAS PENELITIAN DOSEN POLITEKNIK KESEHATAN JAMBI gusmi kholijah; Niken Rarasati; Corry Sormin; Gusmanely Z; Jevi Perdana
JURNAL PADI (Pengabdian mAsyarakat Dosen Indonesia) Vol 6 No 1 (2023): Jurnal PADI (Pengabdian mAsyarakat Dosen Indonesia) Vol. 6 No. 1
Publisher : STKIP PGRI Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51836/jpadi.v6i1.585

Abstract

Lecturer is a profession that has the obligations of the Tridharma of Higher Education. Tridharma includes teaching, research and community service. Each tridharma element must be properly measured as the performance of a lecturer. Lecturer performance in research can be assessed from the quality of the output. The outputs of lecturer research activities are required to be published so that they can be known and become a public reference. Thus, published research results must be properly presented. Problems were found in analyzing the data by the lecturers of the Health Polytechnic of the Jambi Ministry of Health when carrying out the research. So far, data analysis has been limited to analysis of variance (ANOVA). The drawback in using analysis of variance alone in research is that errors will appear in drawing conclusions. Therefore, to overcome these problems, regression analysis training was held to improve the quality of lecturer research at the Jambi Ministry of Health Polytechnic as a form of dedication by lecturers from Jambi University. The activities carried out were in the form of workshops and practice of regression analysis for health cases using Minitab and SPSS software, besides that, interpretation of the results was also carried out. The community service activities carried out were carried out according to the plan, then this activity received a good response from the lecturers at the Jambi Health Polytechnic. This training activity also provides opportunities for communication and collaboration between lecturers from different fields and agencies. Keywords: Regression Analysis, Minitab, Community Service, SPSS
Markov Chain Analysis in Predicting Consumer Price Index for the Food, Beverage and Tobacco Sector in Jambi City gusmi kholijah; Fitriyani Fitriyani
JURNAL SINTAK Vol. 2 No. 1 (2023): SEPTEMBER 2023
Publisher : LPPM-ITEBA

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Abstract

The Consumer Price Index (CPI) is an economic indicator that can provide information regarding developments in prices of goods/services. CPI is one of the factors that can measure inflation. According to the information provided, inflation pressure is influenced by the food, beverage and tobacco sectors and is one of the mainstays in providing a major contribution to economic growth. Every month the CPI can increase or decrease so data from previous times is used to see predictions for the present so time series data is used. Prediction of CPI time series data can use one of the mathematical techniques, namely Markov chain analysis. Markov chain is a method that studies the properties of a variable in the present in an effort to estimate the properties of the same variable in the future, therefore Markov chain analysis is suitable for use in predicting CPI. In this research, it was applied to CPI data for January 2018 to June 2022. After conducting the analysis, it was concluded that in the following months the opportunity for CPI in categories above the basic price was greater than the opportunity above the basic price. So it is hoped that the results of this analysis can help the government stabilize the CPI in the Food, Miniman and Tobacco sectors
Implementasi Project Based Learning dengan Pengembangan e-modul dalam Perkuliahan Matematika Preneurship untuk Meningkatkan Kemampuan Analisis Data dan Resiliensi Mahasiswa Bunga Mardhotillah; Gusmi Kholijah
Journal on Education Vol 5 No 4 (2023): Journal on Education: Volume 5 Nomor 4 Mei-Agustus 2023
Publisher : Departement of Mathematics Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joe.v5i4.5271

Abstract

Mathematics Preneurship is one of the lectures that has great potential for application Project-based learning that is highly recommended in the MBKM, because through Mathematics Preneurship lecture, students can run a business While applying his mathematical knowledge through sharpening his business-related data analysis skills. This integrated Project Based Learning (PjBL) learning model can provide opportunities for designing his own study by creating products/services that are integrated with Data analysis skills and student resilience in doing business. This research aims to develop integrated PjBL-based e-modules Data Analysis and Student Resilience in Mathematics Preneurship Lecture. It is expected that in its application, there will be an increase in thinking skills. This research is in the form of development research by applying the development model with ADDIE procedure. The data analysis technique used is Mixed Method. Implementation of learning with projects on Mathematics Preneurship lecture as a form of learning innovation. This learning innovation will be presented in the form of projects for the achievement of graduate learning outcomes, Student resilience, knowing the results of conceptual feasibility, lecturer assessment, and student response. Implementation of learning-based The project in the Mathpreneurship lecture gives hope that business, industry and service innovation can presented by students in order to create jobs. In addition, learning is based This project result had conclution that students will have soft skills in leading, communicating, cooperation, critical thinking, responsibility and socializing with the community. Keywords: Mathematics Preneurship, math student resilience, project based learning
Analisis Pengelompokan Bulan Berdasarkan Jenis Surat Tahun 2023 Menggunakan Metode K-Means di UPTD/SAMSAT Kabupaten Bungo Nurmarita, Nurmarita; Kholijah, Gusmi; Syafmen, Wardi
JISTech (Journal of Islamic Science and Technology) Vol 10, No 1 (2025)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v10i1.23801

Abstract

Pengelolaan data menjadi kunci efisiensi pelayanan publik di era digital, termasuk di UPTD/SAMSAT Kabupaten Bungo yang menangani pajak kendaraan serta pengolahan surat. Penelitian ini bertujuan mengidentifikasi pola aktivitas surat sepanjang tahun 2023 dengan mengelompokkan bulan berdasarkan karakteristik jenis surat menggunakan metode K-Means Clustering, salah satu metode non-hierarkis yang efektif untuk segmentasi data. Empat variabel dianalisis: Surat Masuk, Surat Keluar, Surat Perintah Tugas (SPT), dan Surat Perintah Perjalanan Dinas (SPPD). Jumlah klaster optimal ditentukan dengan metode Elbow, menunjukkan tiga klaster optimal (k=3). Hasilnya, klaster 1 (September, November, Desember) menunjukkan aktivitas surat tertinggi; klaster 2 (Januari, Februari, April, Mei, Juni, Agustus, Oktober) memiliki aktivitas normal; dan klaster 3 (Maret, Juli) menonjol dengan jumlah surat masuk yang sangat tinggi. Nilai BCSS sebesar 64,6% mengindikasikan pemisahan klaster yang cukup baik. Temuan ini memberikan wawasan penting bagi instansi dalam merancang strategi pengelolaan surat berbasis waktu, seperti perencanaan beban kerja dan penguatan sistem arsip digital, sehingga pelayanan administrasi dapat meningkat secara terstruktur dan berbasis data.
Prediksi Tinggi Muka Air Di Lahan Gambut Provinsi Jambi Berdasarkan Curah Hujan, Suhu Dan Kelembapan Udara Menggunakan Metode Random Forest Regression Irawan, Randi; Kholijah, Gusmi; Multahadah, Cut
JISTech (Journal of Islamic Science and Technology) Vol 10, No 1 (2025)
Publisher : UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jistech.v10i1.24569

Abstract

Lahan gambut merupakan ekosistem penting yang rentan terhadap kerusakan, terutama akibat kebakaran yang sering dipicu oleh penurunan tinggi muka air (TMA). Provinsi Jambi, sebagai salah satu wilayah dengan luasan gambut yang signifikan, mengalami kebakaran berulang dalam beberapa tahun terakhir. Penelitian ini bertujuan untuk membangun model prediksi TMA berbasis algoritma Random Forest Regression guna mendukung mitigasi kebakaran dan pengelolaan lahan gambut berkelanjutan. Model dilatih menggunakan data iklim (curah hujan, suhu, dan kelembaban udara) dari tahun 2019 hingga 2024 di wilayah gambut Provinsi Jambi, dengan 100 pohon keputusan dan pendekatan bootstrap sampling, menggunakan Python dan pustaka Scikit-Learn. Hasil evaluasi menunjukkan performa model yang cukup baik, dengan nilai RMSE sebesar 0,1173 dan R² sebesar 0,7182, yang berarti sekitar 72% variasi TMA dapat dijelaskan oleh model. Analisis feature importance mengidentifikasi curah hujan sebagai faktor paling berpengaruh yaitu sebesar 51.05%, disusul kelembaban sebesar 32.9% dan suhu sebesar 11.9%. Temuan ini menegaskan peran utama curah hujan dalam dinamika TMA, serta potensi penggunaan model sebagai alat bantu dalam sistem peringatan dini dan perencanaan pengelolaan lahan gambut yang lebih efektif.
Co-Authors Abdillah, M Hafiz Arfarani Rosalindari Corry Sormin Corry Sormin Corry Sormin Ditya Ismi Budiarti Edi Saputra Fitriyani Fitriyani Gusmanely Z Irawan, Randi Jevi Perdana Kartika Anjalya Khairul Alim Mahya Ihsan Mardhotillah, Bunga Meinarisa, Meinarisa Multahadah, Cut Nduru, Piky Pratama Niken Rarasati Nurmarita, Nurmarita Oliva Cantica Siti Nurhalizah Sufri Sufri Wardi Syafmen Yurinanda, Sherli