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Fairus, Fairus
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CLUSTER ANALYSIS FOR DISTRICT/CITY GROUPING BASED ON VARIABLES AFFECTING POVERTY IN ACEH PROVINCE USING AVERAGE LINKAGE METHOD Olivia, Mirda; Nurviana, Nurviana; Fairus, Fairus
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp1865-1872

Abstract

Poverty is an inability of a person/household to meet basic needs in everyday life. Aceh is one of the provinces in Indonesia which is still faced with the problem of poverty. In March 2021 the poor population in Aceh numbered 834.24 thousand people and in September 2021 the poor population in Aceh increased by 16 thousand people, a total of 850.26 thousand people. Therefore the authors are interested in classifying and looking at the characteristics of 23 districts/cities in Aceh Province based on 5 variables that affect poverty. This study uses data from SUSENAS processed from BPS Kota Langsa in 2021. The variables used are households with the type of floor of a residential building made of soil/bamboo (X1), households with a floor area of ​​a residential building < 10 m2 per capita (X2), households with residential walls made of bamboo/rumbia/wood (X3), households with a source of drinking water from unprotected wells/springs/rivers/rainwater (X5), and households whose head of household did not attend school/didn't finish primary school/only primary school (X8). This study uses the average linkage method, namely the distance between two clusters is measured by the average distance between objects in each cluster. Of the 23 regencies/cities, 3 clusters were formed, namely cluster 1 with the lowest poverty rate consisting of 17 regencies/cities. Cluster 2 with the highest poverty rate consists of 2 districts/cities. Cluster 3 with a moderate poverty level consists of 4 districts/cities. The characteristics of the clusters that are formed are in clusters 1, 2 and 3 the dominant poverty level is influenced by the variable X3, which means that there are still many households that have houses with inadequate wall types. In clusters 1 and 3 the poverty rate is not dominantly influenced by variable X1, which means that many households have houses with proper floor types. In cluster 2 the poverty rate is not dominantly influenced by variable X5, which means that many households consume drinking water from cleaner and more protected sources.
APPLICATION OF CAUSAL FORECASTING METHOD TO FORECAST SHALLOT PRODUCTION IN NORTH SUMATRA PROVINCE Zebua, Feber Wati; Fairus, Fairus; Amelia, Amelia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0667-0680

Abstract

Shallot are one of the superior horticultural commodities that has a great influence on the economic value and daily needs of society. The province of North Sumatra is a strategic region for producing shallot, making the province the eighth largest producer of shallot in Indonesia. The need and consumer demand for shallot along with the increasing population is a problem, as by 2021 the amount of shallot production in the household sector will only be met by 11% in the North Sumatra province. The authors are therefore interested in studying the factors that influence shallot production and predicting the amount of shallot production in the future North Sumatra province. The source of data the research was carried out by the Agricultural Department of the Province of North Sumatra. The study was conducted using Causal Forecasting and ARIMA methods. The causal forecasting method used is the econometric method. The econometric method is a method for analyzing and predicting future conditions by finding and measuring several important independent variables and their influence on the variables. Dependents are observed. The ARIMA method is used to predict exogenous variables from the results of the analysis performed. Based on the analysis, it is obtained that the factors affecting the amount of shallot production are the quantity of productivity and the extent of the onion harvest. The greater the amount of productivity and the size of the harvest, the more shallot production will increase. The result of the production forecast obtained is the lowest amount of shallot production occurred in April 2022 at 5212,763 tons and the highest amount produced on the onion occurs in March 2023 at 6502,112 tonnes and the average monthly amount of production is 5856,886 tons.
ANALISA KORELASI PEARSON DALAM MENENTUKAN HUBUNGAN ANTARA JUMLAH RUMAH TANGGA PENERIMA MANFAAT BANTUAN SOSIAL DENGAN JUMLAH PENDUDUK DI KOTA LANGSA Ritonga, Baldan zulzamzami; Muliani, fitra; Fairus, Fairus
JURNAL GAMMA-PI Vol 6 No 2 (2024): Jurnal Gamma-Pi (Matematika dan Pendidikan Matematika)
Publisher : Program Studi Matematika, Fakultas Teknik, Universitas Samudra. Langsa, Aceh.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/gamma-pi.v6i2.9529

Abstract

Bantuan sosial merupakan pemberian bantuan berupa uang/barang dari pemerintah daerah kepada individu,keluarga, kelompok dan/atau masyarakat yang sifatnya tidak secara terus menerus dan selektif yang bertujuan untuk melindungi dari kemungkinan terjadinya resiko sosial. Data penerima bantuan sosial di kota Langsa cukup fluktuatif, begitu pula data jumlah penduduk, sehingga perlu di ketahui apakah data tersebut berhubungan Tujuan penelitian ini adalah untuk mengetahui korelasi antara jumlah penduduk terhadap penerima bantuan sosial di Kota Langsa. Data yang digunakan adalah data jumlah penduduk dan jumlah rumah tangga penerima bantuan sosial tahun 2018 sampai dengan 2022 tahunan dengan jenis adalah data sekunder yang diperoleh dari Badan Pusat Statistik (BPS) Kota Langsa. Berdasarkan hasil Analisa yang dilakukan, diperoleh bahwa data berdistribusi normal sehingga sangat cocok menggunakan uji korelasi Pearson. Dengan data yang berjumlah masing-masing 25, diperoleh = 2,27115 Jika maka dengan dk = 25 – 2 =23, dari daftar distribusi t di dapat = 2,068658. Jelas bahwa nilai = 2,27115 > = 2,068658 sehingga dapat disimpulkan bahwa terdapat hubungan signifikan antara jumlah penduduk dengan jumlah penerima bantuan sosial Kota Langsa.
PENGARUH PENDAPATAN DAERAH DAN SISA ANGGARAN TAHUN SEBELUMNYA (SiLPA) TERHADAP REALISASI BELANJA APBD KOTA LANGSA TAHUN 2011-2023 husna, asmaul; Mawarni; Fairus, Fairus
JURNAL GAMMA-PI Vol 6 No 2 (2024): Jurnal Gamma-Pi (Matematika dan Pendidikan Matematika)
Publisher : Program Studi Matematika, Fakultas Teknik, Universitas Samudra. Langsa, Aceh.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/gamma-pi.v6i2.11757

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh Pendapatan Daerah dan Sisa Anggaran Tahun Sebelumnya (SiLPA) terhadap Realisasi Belanja APBD Kota Langsa tahun 2011–2023. Jenis data yang digunakan adalah data sekunder yang diperoleh dari Kantor Pelayanan Perbendaharaan Negara (KPPN) Langsa. Metode analisis yang digunakan dalam penelitian ini adalah regresi linear berganda yang didahului dengan uji asumsi klasik, seperti uji normalitas, uji multikolinearitas, uji heteroskedastisitas, dan uji autokorelasi. Hasil penelitian menunjukkan bahwa secara simultan, Pendapatan Daerah dan SiLPA berpengaruh signifikan terhadap Realisasi Belanja APBD . Secara parsial, Pendapatan Daerah berpengaruh signifikan terhadap Realisasi Belanja APBD . Meskipun demikian, variabel SiLPA tidak menunjukkan pengaruh yang signifikan secara parsial terhadap variabel dependen, yang ditunjukkan oleh nilai t hitung sebesar 0,535 dengan tingkat signifikansi sebesar 0,605, melebihi ambang signifikansi 0,05. Koefisien determinasi (R²) sebesar 93,4% menunjukkan bahwa model dapat menjelaskan variabel dependen dengan sangat baik. Penelitian ini memberikan rekomendasi agar Pemerintah Kota Langsa terus mengoptimalkan Pendapatan Daerah dan mengelola SiLPA secara strategis untuk mendukung efektivitas perencanaan dan pelaksanaan anggaran di masa mendatang.
Co-Authors Abdul Latief Adnan Achmad Afrah Junita Agus Kurniawan Agus Putra AS Ahmad Zuhdi Amelia Amelia Asmaul Husna Baihaqi Baihaqi Chaidir Chaidir Edi Syahputra Edy Surya Ellida Novita Lydia Ety, Dusra Fakhri, Fakhri Intan Khairina, Mashitah Intan Sari Jarnawi Jarnawi Liza Fitria, Liza Mawarni Muhammad Fuad Muhammad JAMIL Muhammad Ridla Muliani, Fitra Murdani, T mutiara mutiara Nabilla, Ulya Nurarafah, Nurarafah Nurviana, Nurviana Olivia, Mirda Prinelti, Maria Novianti Putri, Gita Amanda Putri, Sonia Anisa Rahmatillah, Syauqas Rasyidah Rasyidah Ritonga, Baldan zulzamzami Saiman Saiman Sari, Riezky Purnama Sari, Sari Yuliani Suriah Suriah Sutrisno, Imam Hadi Syamsuddin AB, Syamsuddin Wulandari, Tri Indah Yusuf, Fakhri Zebua, Feber Wati