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Rizka Rizqi Robby
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Public Health

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IMPLEMENTASI METODE TRIPLE EXPONENTIAL SMOOTHING DALAM MERAMALKAN PENERIMAAN CUKAI HASIL TEMBAKAU DI KPPBC TMP C BLITAR Susi Darmawaningsih; Rizka Rizqi Robby
JURNAL DIFERENSIAL Vol 4 No 1 (2022): April 2022
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v4i1.6564

Abstract

Forecasting is an important tool in effective and efficient planning. One of the time series methods in objective forecasting is the exponential smoothing method which is a procedure that continuously improves forecasting by averaging (smoothing = smoothing) the past value of a time series data in a decreasing way (exponential). The purpose of this research is to predict the amount tax receipt from tobacco at the Office of Supervision and Service of Customs and Excise Intermediate Customs Type C Blitar using the triple exponential smoothing method by finding the smallest error using MAD (Mean Absolute Deviation), MSE (Mean Square Error) and MAPE (Mean Absolute Percentage Error) which is tested with a constant value of . Excise on tobacco products is a state income that is managed through the mechanism of the state revenue and expenditure budget has a fairly important and strategic role in financing government programs and performance as well as development throughout the territory of the Unitary State of the Republic of Indonesia in a planned, orderly, safe, fair and sustainable manner, so that the prosperity and people's welfare. The implementation of mathematics to be applied to statistical data is very necessary especially to predict future state treasury receipts. For that in this research the Triple Exponential Smoothing method is used which uses a constant value of to . The results of this test produce the smallest error value with a constant value of α =0.1 with a MAPE result of 0,27%.
PENERAPAN PEWARNAAN GRAF PADA PENJADWALAN WORK FROM HOME (STUDI KASUS KANTOR PENGAWASAN DAN PELAYANAN BEA DAN CUKAI TIPE MADYA PABEAN C BLITAR) Amaliya Asyraful Hida; Rizka Rizqi Robby
JURNAL DIFERENSIAL Vol 4 No 1 (2022): April 2022
Publisher : Program Studi Matematika, Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jd.v4i1.6570

Abstract

The Corona virus has been endemic in Indonesia since early March and has spread widely to almost all provinces in Indonesia which has resulted in changes in various aspects of human life. Various policies have been issued to minimize the spread of COVID-19, one of which is the implementation of PSBB (Large-Scale Social Restrictions), with the enactment of PSBB, this has resulted in disruption of community activities due to restrictions in various ways, one of which is work activities. The Blitar Customs Office implements Work From Home (WFH) with a minimum rule of 50 percent of people who carry out Work From Home (WFH). The preparation of the WFH (Work From Home) schedule is an example of scheduling that must be carried out by KPPBC TMP C Blitar, To solve the scheduling problem, an analysis will be carried out using graph theory, namely coloring, and processed with the Welch-Powell Algorithm. Welch-Powell algorithm can be used to color a graph G efficiently. From research conducted using the Welch-Powell algorithm to color WFH scheduling results in a more effective schedule. The results showed that the point coloring in the General Subdivision produced four colors with a chromatic number of 4, the point coloring in the Investigation and Investigation Section produced four colors with a chromatic number of 4, the point coloring in the Treasury Section produced 5 colors with a chromatic number of 5, the dot coloring in the KIP Section resulted in 4 colors with a chromatic number of 4.
PERBANDINGAN REGRESI ROBUST METODE LEAST TRIMMED SQUARE (LTS) DAN METODE ESTIMASI-S PADA PRODUKSI PADI DI KABUPATEN BLITAR ENDAH SETYOWATI; RACHMADANIA AKBARITA; RIZKA RIZQI ROBBY
Jurnal Matematika UNAND Vol 10, No 3 (2021)
Publisher : Jurusan Matematika FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmu.10.3.329-341.2021

Abstract

Produksi padi di Kabupaten Blitar mengalami peningkatan dan penurunan, hal ini dipengaruhi oleh beberapa faktor, diantaranya jumlah petani, alokasi pupuk, ratarata curah hujan, luas panen, luas tanam, produktivitas, dan alat pengolah padi. Oleh karena itu, untuk mengetahui faktor-faktor yang lebih signifikan tersebut, guna mencapai produksi padi yang optimal dapat digunakan analisis regresi. Namun, adanya data pencilan pada suatu data penelitian dapat mengganggu proses analisis data. Regresi robust merupakan metode yang efisien untuk menganalisis data yang mengandung pencilan. Regresi robust memiliki beberapa metode estimasi, dua diantaranya adalah Least Trimmed Square (LTS) dan Estimasi S yang memiliki persamaan karateristik pada efisiensi dan breakdown point. Penelitian ini bertujuan untuk membandingkan kedua metode tersebut pada data produksi padi di Kabupaten Blitar tahun 2018 dengan tujuh variabel bebas (jumlah petani, alokasi pupuk, rata-rata curah hujan, luas panen, luas tanam, produktivitas, dan alat pengolah padi). Pengambilan data pada tahun 2018 didasarkan pada kelengkapan dokumen serta adanya kekhawatiran pandemi Covid-19 mempengaruhi data. Estimasi regresi robust menggunakan metode Least Trimmed Square (LTS) pada produksi padi di Kabupaten Blitar diperoleh model: Y = −11262, 756 − 0, 01x1 + 0, 031x2 − 14, 304x3 + 2, 292x4 + 3, 741x5 + 188, 274x6 − 0, 419x7 dan estimasi regresi robust menggunakan metode Estimasi S pada produksi padi di Kabupaten Blitar diperoleh model: Y = −9698, 949−0, 14x1−0, 49x2−19, 531x3+0, 133x4+5, 714x5+175, 018x6−0, 507x7. Hasil penelitian menunjukan regresi robust metode Least Trimmed Square (LTS) merupakan metode yang menghasilkan model terbaik, karena metode Least Trimmed Square (LTS) memiliki nilai koefisien determinasi (R2 ) sebesar 0, 99999 yang lebih besar dibandingkan nilai koefisien determinasi (R2 ) metode Estimasi S sebesar 0,99882, dan metode Least Trimmed Square (LTS) memiliki nilai Mean Square Error (MSE) sebesar 0,62105 yang lebih kecil dibandingkan nilai Mean Square Error (MSE) metode Estimasi S sebesar 9,04800.Kata Kunci: Data Pencilan (outlier), Produksi Padi, Regresi Robust
Analisis Klaster Kependudukan di Kota Blitar Menggunakan Metode Fuzzy C-Means Clustering Yumna Salsabila Firdaus; Rachmadania Akbarita; Rizka Rizqi Robby
Jurnal Matematika Vol 12 No 2 (2022)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2022.v12.i02.p153

Abstract

Blitar City is one of 9 cities in East Java province with an area of 32.58 km2, and has an unequal population distribution in every urban village. There is a difference of 11,719 people between urban villages that have a dense population and a small population. The purpose of this study is to analyze clusters or categorize the population of 21 urban villages in Blitar City by population migration factors, births and mortality. In this study using secondary data obtained from the Blitar City Statistics Centre, namely demographic data in 2019. The methodology used in this study is Fuzzy C-Means (FCM) cluster analysis. FCM is a cluster method in which the existence of each data in a cluster is determined by the degree of membership based on fuzzy logic theory. This method was chosen because it makes it possible to group data that is scattered irregularly. Create a convergent cluster centre using the objective function. The test results were then validated using Partition Entropy, Partition Coefficient and Pseudo F. There were many clusters = 2, 22 iterations, with an objective function of 98252.44. There are 14 urban villages in Group Cluster 1 and 7 urban villages in Cluster 2.
Co-Authors Abd. Rasyid Syamsuri Amaliya Asyraful Hida Rachmadania Akbarita Susi Darmawaningsih Yumna Salsabila Firdaus