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PEMODELAN ANGKA PORI PADA STABILISASI TANAH GAMBUT Pradana, Mohammad Syaiful; Rohmah, Awawin Mustana
Buana Matematika : Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 8 No 2 (2018)
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (864.054 KB) | DOI: 10.36456/buanamatematika.v8i2:.1729

Abstract

Methods for improving peat soils to increase soil carrying capacity and reduce environmentally sound soil compressibility, namely stabilization of the peat layer. This method uses additives such as lime, fly ash and husks. This method has been developed based laboratory by civil engineers. However, it takes a relatively long time to find out the laboratory results. Therefore, research in the field of mathematical models for stabilization of peat soil was developed to predict the laboratory results. In this study, a mathematical model was derived one of the physical properties of peat soil, that is the pore number in stabilizing peat soil. The model is derived from fluid equations through porous media based on the principle of continuum and control volume. Furthermore, the model is completed using a finite difference method, the MacCormack scheme which consists of two steps, that are predictor and corrector. After the model is simulated using matlab, it is known that there is a decrease in the soil pore value to a constant condition. This decrease in pore number is due to chemical reactions that occur by additives which make the soil pores smaller. Keywords: pore number, maccormack, stabilization of peat soil
Estimasi Parameter Super Pairwise Alignment pada Kombinasi Virus Dengue Menggunakan Particle Swarm Optimization Dinita Rahmalia; Arif Rohmatullah; Mohammad Syaiful Pradana
Techno.Com Vol 18, No 3 (2019): Agustus 2019
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (664.28 KB) | DOI: 10.33633/tc.v18i3.2528

Abstract

Di Indonesia terdapat empat jenis virus dengue atau demam berdarah. Untuk melihat tingkat kesamaan (similarity) antara dua sekuens virus, dibutuhkan proses pensejajaran pada sekuens virus. Metode yang digunakan untuk pensejajaran pada dua sekuens virus adalah Super Pairwise Alignment (SPA). Nilai fungsi objective pada SPA adalah nilai penalty antara dua sekuens virus. Karena nilai fungsi objective tergantung pada parameter SPA, maka pada penelitian ini nilai parameter SPA akan diestimasi menggunakan metode heuristik seperti Particle Swarm Optimization (PSO). Simulasi diterapkan pada enam kombinasi virus dengue untuk proses estimasi parameter SPA. Berdasarkan hasil simulasi pada enam kombinasi virus dengue, PSO dapat menemukan parameter SPA yang optimal secara pendekatan. Parameter SPA yang optimal juga dapat mengetahui posisi dan panjang dari unit sekuens yang mengalami penambahan atau penghapusan.
Quality and Affordable Education through Quality Management Systems in Higher Education Muhammad Afif Hasbullah; Nisaul Barokati Selirowangi; Mohammad Syaiful Pradana; Buyun Khulel; Moh Hudi
EDUTEC : Journal of Education And Technology Vol 3 No 2 (2020): March 2020
Publisher : STAI Miftahul Ula Nganjuk

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29062/edu.v3i2.52

Abstract

The general goal of education is to develop Indonesian people completely in the sense that carried out education still maintain unity, diversity and develop individual’s ideals. Every citizen has the right to obtain education equally with excellence and a balance (equity) between the utilization (access) with achievement. The higher education system must be able to create a quality higher education that is also affordable by the people of Indonesia. A university leader must be in-line and lead a "quality revolution". All energy and attention are focused on the "quality revolution". For this reason, this paper will examine the Implementation of Higher Education Quality Management Systems. As a case study is that has implemented a Quality Management System. According to Law No. 12 of 2012 concerning Higher Education. Quality Higher Education is Higher Education that produces graduates who are able to actively develop their potential and produce Science and / or Technology that is useful for the Community, nation, and country. The government operates a higher education quality assurance system to get quality education. The Higher Education quality assurance system referred to consists of: a. internal quality assurance system developed by Higher Education; and b. external quality assurance system carried out through accreditation. Implementation of Quality Management Systems in Higher Education can produce Quality and Affordable Education.
Peramalan Nilai Tukar Petani Kabupaten Lamongan dengan Arima Mohammad Syaiful Pradana; Dinita Rahmalia; Ericha Dwi Ayu Prahastini
Jurnal Matematika Vol 10 No 2 (2020)
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.2020.v10.i02.p126

Abstract

Agriculture is a sector that has a significant role for the Indonesian economy. In Lamongan Regency, about 35.71 percent of the workers depends on the primary agricultural sector, so it is not surprising that the agricultural sector is the basis of growth, especially in rural areas. Agricultural development is oriented towards improving the welfare of farmers. One of the measurements the level of farmer welfare is by calculating the Farmer Exchange Rate. It is the relationship between the produce sold by farmers and the goods and services purchased by farmers. Seeing how important this Farmer Exchange Rate is, predicting the value of Farmer Exchange Rate in the following year will be very useful. The results of this value can be a benchmark to anticipate all situations in the following years and how to control the rising value of Farmer Exchange Rate so as to improve the welfare of the people of Lamongan. From the results of the analysis and discussion, food plants have a low NTP value, namely ?100 per month for a period of 3 years and have the highest Farmer Exchange Rate reduction in 2019 of 10.25%.
KLASTERISASI DATA PERTANIAN DI KABUPATEN LAMONGAN MENGGUNAKAN ALGORITMA K-MEANS DAN FUZZY C MEANS Arif Rohmatullah; Dinita Rahmalia; Mohammad Syaiful Pradana
Jurnal Ilmiah Teknosains Vol 5, No 2 (2019): JiTek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (276.66 KB) | DOI: 10.26877/jitek.v5i2.4254

Abstract

Di Indonesia, terdapat beberapa pekerja sebagai petani sebagai matapencaharian karena kebutuhan pokok pada pangan dan memiliki lahan pertanian yang luas. Karena terdapat perbedaan  luas lahan pertanian dan hasil produksi pertanian, maka diperlukan klasterisasi pada data pertanian. Tujuan klastering adalah untuk mengidentifikasi suatu kelompok data dari populasi data untuk menghasilkan sifat-sifat dari data itu sendiri. Pada penelitian ini akan digunakan dua metode yaitu : algoritma K-Means dan algoritma Fuzzy C Means (FCM). Algoritma K-Means dan algoritma FCM dapat mengklaster beberapa kecamatan di kabupaten Lamongan berdasarkan luas lahan pertanian dan hasil produksi pertanian. Pada algoritma K-Means, titik pusat klaster diupdate sehingga menghasilkan jumlahan euclidean distance yang minimum. Pada algoritma FCM, derajat keanggotaan (the degree of membership) diupdate sehingga menghasilkan nilai fungsi objective yang minimum. Berdasarkan hasil simulasi, kedua metode tersebut dapat mengklaster beberapa kecamatan di kabupaten Lamongan berdasarkan luas lahan pertanian dan hasil produksi pertanian.
Zika Virus Mutation and The Spreading to Indonesia Mohammad Syaiful Pradana; Siti Amiroch
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 4, No 1 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (333.109 KB) | DOI: 10.12962/j24775401.v4i1.3021

Abstract

More than 13 countries in the Americas have reported sporadic Zika virus infection that show very rapid geographic expansion. While in Indonesia, the euphoria is also increasingly prevalent virus discussed especially after the discovery of Jambi positive patients infected with the virus Zika on January 26, 2016 last.Viruses transmitted by mosquito bites to humans are the same mosquito transmits dengue fever, chikungunya and yellow fever with symptoms that have similar resemblance to the zika virus. Based on similarity of symptoms of infection with dengue virus, can be analyzed using sequence alignment to get identical percentage, local alignment calculation, genetic mutation and the spread of the zika virus to Indonesia. From the whole process, Smith Waterman algorithm can be used to align dengue virus type 1, type 2, type 3, and type 4 with zika virus (Jambi). Mutations between dengue virus and zika virus on average 28% of dissimilarity sequences in the same position between the sequence. Overall, the dengue virus type 1 mutation to the zika virus was 28.2723%, the dengue virus type 2 mutation to the zika virus was 28.1984%, the dengue virus type 3 mutation to the zika virus 27.9373% and the mutation of dengue virus type 4 to the zika virus of 28.7206%. By looking at all mutations, from the simulation results note that the mutations of both viruses include mutation type I. The phylogenetic tree showed the spread of the Zika virus to Indonesia, originally from South Africa, the islands of Chile, Caledonia, the Philippines, Yap Micronesia, Thailand, Cambodia, and finally reached Indonesia. Zika virus jambi suspected of dengue virus mutation because a few years earlier there was a dengue virus outbreaks in a long time in Jambi, it turns out the virus zika jambi is not from mutation dengue virus but the virus comes from the Asian region.
Klasifikasi Multi Output pada Harga Smartphone Menggunakan Learning Vector Quantization (LVQ) dan Backpropagation (BP) Dinita Rahmalia; Mohammad Syaiful Pradana; Teguh Herlambang
Systemic: Information System and Informatics Journal Vol. 6 No. 2 (2020): Desember
Publisher : Program Studi Sistem Informasi Fakultas Sains dan Teknologi, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29080/systemic.v6i2.967

Abstract

There are many smartphones with various price sold in market. The price of smartphone is affected by some components such as weight, internal storage, memory (RAM), rear camera, front camera and brands. There are two methods for classifying price class of smartphone in market such as Learning Vector Quantization (LVQ) and Backpropagation (BP). From classifying price class of smartphone in market using LVQ and BP, there are the differences on the both of them. LVQ classifies price range of smartphone by euclidean distance of weight and data on its iteration. BP classifies price range of smartphone by gradient descent of target and output on its iteration. In multi output classification, one object may have multi output. Based on simulation results, BP gives the better accuracy and error rate in training data and testing data than LVQ.
PEMODELAN KADAR AIR PADA SIFAT FISIK STABILISASI TANAH GAMBUT Mohammad Syaiful Pradana; Awawin Mustana Rohmah
Journal of Mathematics and Mathematics Education Vol 8, No 1 (2018): Journal of Mathematics and Mathematics Education (JMME)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/jmme.v8i1.25826

Abstract

Abstract: Peat soil is an organic soil with very low carrying capacity and high compressibility. The condition is less profitable for civil engineers in building a civil foundation foundation. One method of peat soil improvement can be done with astabilization method that more environment-friendly and cheaper than other methods. Laboratory based peat stabilization studies to increase carrying capacity, reduce compression and improve peat soil physical properties have been conducted in Indonesia. The results of laboratory studies shown in the graph are still limited by time and content of the mixture. Therefore, further research is needed on the mathematical model toward the physical properties of peat soil stabilization. In this research will be formulated mathematical model of water content on the physical properties of peat soil stabilization. The model is derived from the fluid equation through porous media based on the principle of continum and controlvolume. The model is then resolved numerically by different method until MacCormack scheme with two steps are predictor step using forward difference and correctorstep using backward difference. The MacCormack scheme has the advantage of solving fluid flow equations and continuity. The model is then simulated and validated by comparing the simulation results with the real system. From the simulation results obtained the water content gradually decreased, the decrease is almost close to zero. In addition, it can be seen the difference in decrease in moisture content at each test point although in small quantities.Keywords:Moisture Content, MacCormack, Peat Soil Stabilization.
PEMODELAN ANGKA PORI PADA STABILISASI TANAH GAMBUT Mohammad Syaiful Pradana; Awawin Mustana Rohmah
Buana Matematika : Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 8 No 2 (2018)
Publisher : Universitas PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (864.054 KB) | DOI: 10.36456/buanamatematika.v8i2:.1729

Abstract

Methods for improving peat soils to increase soil carrying capacity and reduce environmentally sound soil compressibility, namely stabilization of the peat layer. This method uses additives such as lime, fly ash and husks. This method has been developed based laboratory by civil engineers. However, it takes a relatively long time to find out the laboratory results. Therefore, research in the field of mathematical models for stabilization of peat soil was developed to predict the laboratory results. In this study, a mathematical model was derived one of the physical properties of peat soil, that is the pore number in stabilizing peat soil. The model is derived from fluid equations through porous media based on the principle of continuum and control volume. Furthermore, the model is completed using a finite difference method, the MacCormack scheme which consists of two steps, that are predictor and corrector. After the model is simulated using matlab, it is known that there is a decrease in the soil pore value to a constant condition. This decrease in pore number is due to chemical reactions that occur by additives which make the soil pores smaller. Keywords: pore number, maccormack, stabilization of peat soil
THE ACTIVITY INFLUENCE USING GEOGEBRA PROGRAM ON CIRCLE SUBJECT OF STUDENT ACHIEVEMENT Mohammad Syaiful Pradana
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 1 No 01 (2015): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1657.726 KB) | DOI: 10.52166/ujmc.v1i01.435

Abstract

Nowdays, education has support by modern facilities like a computer. So, this facilities should be utilized maximally, especially in mathematics. One of the computer program for learning mathematics is Geogebra. This program provides a geometric visualization to clarify certain concepts to students. The purpose of this research is determine the activity of learners using Geogebra program and its effect for students achievement. The research type is not purely experimental studies with one shot case studymodels. This is an experiment models conducted without comparison group and also preview test. The research population is students at XI MIA-1 until XI MIA-7 Senior High School 1 Manyar Gresik academic years 2014-2015. While the sample is XI MIA-2 randomly selected after homogenity test. The research instrument using observation sheet and test. From the data collected and analyzed using normality test, liniearity test, linear regression test, F test, t test and determination coefficient results regression equation