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All Journal Journal of Education and Learning (EduLearn) AKSIOMA: Jurnal Program Studi Pendidikan Matematika AlphaMath: Journal of Mathematics Education JURNAL ILMIAH MATEMATIKA DAN TERAPAN Buana Matematika : Jurnal Ilmiah Matematika dan Pendidikan Matematika Jurnal Basicedu International Journal of Elementary Education Jurnal Ilmiah Sekolah Dasar Delta: Jurnal Ilmiah Pendidikan Matematika PRISMATIKA: Jurnal Pendidikan dan Riset Matematika BERNAS: Jurnal Pengabdian Kepada Masyarakat Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Logaritma : Jurnal Ilmu-ilmu Pendidikan dan Sains Khazanah Intelektual Jurnal Engineering Edumatica: Jurnal Pendidikan Matematika Journal Focus Action of Research Mathematic (Factor M) Ta'dib Jurnal Penelitian Pendidikan Indonesia Mathematical Sciences and Applications Journal
Sufri Sufri
FKIP Universitas Jambi
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Nursing Public Health Social Sciences Veterinary Other

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CLUSTERING ANALYSIS WITH AVERAGE LINKAGE METHOD FOR GROUPING PROVINCE IN INDONESIA BASED ON WELFARE INDICATORS dwiki Prasetia; sufri; gusmi kholijah
Mathematical Sciences and Applications Journal Vol. 1 No. 1 (2020): Mathematical Sciences and Applications Journal
Publisher : Department of Mathematics, Faculty of Science and Technology Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The high level of social inequality in Indonesia is a problem that must be resolved immediately. High social inequality will result in an increase in social tension which also impacts on the high level of conflict and crime in society. The problem of social inequality can be solved by accelerating the welfare distribution program by the government. The provision of this program must be fair and adapted to the conditions needed by each region. This is because each region has different causes of welfare problems. Therefore, in providing the program, the government must have a priority scale on welfare issues in an area that can be done using a mathematical method in the field of statistics, namely cluster analysis. This study aims to obtain, analyze and interpret the results of grouping provinces in Indonesia based on indicators of people's welfare. As many as 34 provinces in Indonesia as objects will be grouped based on 20 variables related to people's welfare. The grouping is done using the Hierarchy Method, the agglomeration grouping procedure with the Average Linkage technique and the size of the Euclidean Distance. From the clustering algorithm, it was found that from 34 provinces in Indonesia grouped into 5 clusters namely Cluster 1 consisting of 24 members namely Aceh Province; North Sumatra; West Sumatra; Riau; Jambi; South Sumatra; Bengkulu; Lampung; Head of Pacific Islands; Riau Islands; West Java; Central Java; East Java; Banten; West Nusa Tenggara; Central Kalimantan; South Borneo; East Kalimantan; North Kalimantan; North Sulawesi; Central Sulawesi; South Sulawesi; Southeast Sulawesi; and Gorontalo. Cluster 2 consists of 1 member, DKI Jakarta Province. Cluster 3 consists of 2 members including DI Yogyakarta and Bali Provinces. Cluster 4 consists of 6 members including East Nusa Tenggara Province; West Kalimantan; West Sulawesi; Maluku; North Maluku; and West Papua. Cluster 5 consists of 1 member, Papua Province. Based on the comparison of the average value of each cluster, the five clusters are sorted based on their level of welfare, namely: Cluster 3 as a very good cluster, Cluster 2 as a better cluster, Cluster 1 as a good cluster, Cluster 4 as a pretty good cluster and cluster 5 as a less good claser. Keywords: Cluster Analysis, Average Linkage, People's Welfare
PENGGUNAAN MODEL SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) DALAM MEMPREDIKSI JUMLAH CURAH HUJAN DI KABUPATEN MUARO JAMBI TAHUN 2024 Nurhafisah; Gusmanely.Z; Sufri
Jurnal Khazanah Intelektual Vol. 8 No. 1 (2024): Khazanah Intelektual
Publisher : Balitbangda Provinsi Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37250/khazanah.v8i1.237

Abstract

Rain is a source of water where water is an important element in life, one of which is in the agricultural sector. High rainfall can cause floods which cause damage to agricultural crops so that farmers will experience crop failure. In 2021, 2,591 hectares of rice fields in Muaro Jambi Regency experienced crop failure due to flooding caused by high rainfall. This is an important reason to predict the amount of rainfall in Muaro Jambi Regency so that it can help in making decisions to anticipate crop failure. Rainfall is often difficult to predict, so it is necessary to identify data patterns to determine the appropriate method and determine the best model that can be used to predict the amount of rainfall in Muaro Jambi Regency. The results of identifying rainfall data patterns in Muaro Jambi Regency show that the rainfall data in Muaro Jambi Regency contains seasonal patterns. SARIMA is a forecasting method that is suitable for application to data that contains seasonal patterns. The best model that can be used to predict the amount of rainfall in Muaro Jambi Regency is the SARIMA(1,0,0)(1,0,0)12 model with forecasting accuracy classified as very good with a MAPE value of 0.05041% and an MSE of 8959 .8 which is obtained from calculating the error value between the actual data and the forecast results on outsample data.
Desain elmolus (elektronik modul kalkulus) berbasis android berbantuan sigil menggunakan concept rich instruction dengan pengaplikasian live worksheet Sufri Sufri; Feri Tiona Pasaribu
JPPI (Jurnal Penelitian Pendidikan Indonesia) Vol 9, No 4 (2023): JPPI (Jurnal Penelitian Pendidikan Indonesia)
Publisher : Indonesian Institute for Counseling, Education and Theraphy (IICET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29210/020232247

Abstract

Penelitian ini dilatarbelakangi oleh proses pembelajaran saat ini di masa pandemic covid 19 yang mengakibatkan pembelajaran dilakukan secara daring sehingga dituntut untuk menggunakan teknologi dan untuk meningkatkan kemampuan berpikir tingkat tinggi. Penelitian ini bertujuan untuk mendeskripsikan hasil desain dan kualitas ELMOLUS berbasis android berbantuan sigil menggunakan concept rich instruction dengan pengaplikasian live worksheet. Penelitian ini mendesain dan mengembangkan dengan menggunakan model pengembangan ADDIE yang diawali tahap analisis, desain, pengembangan, implementasi dan dilakukan evaluasi setiap fase. Pada penelitian ini menghasilkan produk berupa e-modul untuk mahasiswa pada materi kalkulus. ELMOLUS ini didesain menggunakan pendekatan concept rich instruction dengan lima karakteristik yaitu practice, decontextualization, encapsulating a generalization in words, recontextualization dan realization. Berdasarkan uji validasi dan uji praktikalitas, diperoleh hasil dari validasi oleh ahli materi dan ahli desain dengan persentase berturut-turut 88% dan 89,4% dengan kriteria “sangat valid”. Dan untuk hasil uji kepraktisan dari uji coba perorangan diperoleh dengan persentase 88,8% dan uji coba kelompok kecil diperoleh dengan persentase 85%, sehingga pada kriteria persentase kepraktisan didapatkan kriteria “sangat praktis” dengan revisi kecil.
Optimasi Keuntungan Menggunakan Metode Karush- Kuhn-Tucker (Studi Kasus: Mi Aceh Pattimura di Jambi) Agustina, Ellys; Sufri; Rozi, Syamsyida
Journal Focus Action of Research Mathematic (Factor M) Vol. 3 No. 2 (2021)
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/factor_m.v3i2.3222

Abstract

Masalah pengeluaran yang tidak stabil dan produksi yang tidak optimal mendorong pelaku usaha untuk merumuskan strategi yang tepat agar usaha dapat terus berjalan dengan lancar. Hal tersebut juga terkait dengan adanya keinginan untuk memaksimalkan keuntungan. Masalah yang demikian dialami pula oleh pelaku usaha Mi Aceh Pattimura, Jambi. Adapun tujuan dari penelitian ini adalah untuk menentukan dan mengidentifikasi jumlah produksi yang optimal per hari supaya pelaku usaha Mi Aceh Pattimura memperoleh keuntungan harian yang optimal berdasarkan modal dan bahan yang tersedia. Dan pada penelitian ini, metode yang digunakan untuk menemukan keadaan optimal tersebut adalah metode Kuhn Tucker. Berdasarkan perhitungan menggunakan metode Karush-Kuhn-Tucker, diperoleh jumlah produksi optimal per hari pada usaha Mi Aceh Pattimura adalah mi aceh kuah sebanyak 15 porsi, mi aceh goreng sebanyak 6 porsi, mi aceh tumis sebanyak 19 porsi, mi aceh daging sebanyak 20 porsi, mi aceh ayam sebanyak 20 porsi, dan mi aceh udang sebanyak 20 porsi dengan keuntungan optimal yang dapat diperoleh sebesar Rp. 745.169,9279 per hari.
PENGGUNAAN MODEL SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) DALAM MEMPREDIKSI JUMLAH CURAH HUJAN DI KABUPATEN MUARO JAMBI TAHUN 2024 Nurhafisah; Gusmanely.Z; Sufri
Jurnal Khazanah Intelektual Vol. 8 No. 1 (2024): Khazanah Intelektual
Publisher : Brida Provinsi Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37250/khazanah.v8i1.237

Abstract

Rain is a source of water where water is an important element in life, one of which is in the agricultural sector. High rainfall can cause floods which cause damage to agricultural crops so that farmers will experience crop failure. In 2021, 2,591 hectares of rice fields in Muaro Jambi Regency experienced crop failure due to flooding caused by high rainfall. This is an important reason to predict the amount of rainfall in Muaro Jambi Regency so that it can help in making decisions to anticipate crop failure. Rainfall is often difficult to predict, so it is necessary to identify data patterns to determine the appropriate method and determine the best model that can be used to predict the amount of rainfall in Muaro Jambi Regency. The results of identifying rainfall data patterns in Muaro Jambi Regency show that the rainfall data in Muaro Jambi Regency contains seasonal patterns. SARIMA is a forecasting method that is suitable for application to data that contains seasonal patterns. The best model that can be used to predict the amount of rainfall in Muaro Jambi Regency is the SARIMA(1,0,0)(1,0,0)12 model with forecasting accuracy classified as very good with a MAPE value of 0.05041% and an MSE of 8959 .8 which is obtained from calculating the error value between the actual data and the forecast results on outsample data.
Co-Authors Agustina, Ellys Ali Idrus Arfarani Rosalindari Dewi Iriani dwiki Prasetia Ellys Agustina Elza Triani Feri Tiona Pasaribu Fhadira Insani Putri Gusmanely.Z gusmi kholijah Gusmi Kholijah Ika Puspita Sari Ilham Yusuf Triputra Kamid Kamid Kamid Kartika Anjalya Khairul Anwar Mardhotillah, Bunga Multahadah, C Nizlel Huda Nurhafisah Rido Ilham Widodo Robi Soma Robin Pratama Rohati Rohati Roseli Theis Roseli Theis Roseli Theis Sabila Eka Septi Sabila Eka Septi Sembiring, R R Septi, Sabila Eka Setiyadi, Bradley Siti Rohana Siti Rohana Sofnidar - Suci Wulandari Suci Wulandari Susilawati Susilawati Syaiful . Syaiful Syaiful Syamsyida Rozi Tri Gita Yuliana Wardi Syafmen Widodo, Rido Ilham Yelli Ramalisa Yon Adlis Yurinanda, Sherli