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All Journal International Journal of Evaluation and Research in Education (IJERE) Cakrawala Pendidikan Jurnal Buana Informatika Kubik Jurnal Sains Matematika dan Statistika Proceeding of the Electrical Engineering Computer Science and Informatics Fountain of Informatics Journal JRPM (Jurnal Review Pembelajaran Matematika) Jurnal Matematika: MANTIK Al-MARSHAD: Jurnal Astronomi Islam dan Ilmu-Ilmu Berkaitan BAREKENG: Jurnal Ilmu Matematika dan Terapan International Journal of Computing Science and Applied Mathematics Mathvision : Jurnal Matematika Jurnal Statistika dan Aplikasinya KUBIK: Jurnal Publikasi Ilmiah Matematika Journal of Mathematics Education and Science Engagement: Jurnal Pengabdian Kepada Masyarakat
Ahmad Hanif Asyhar
UIN Sunan Ampel Surabaya
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Optimal ANFIS Model for Forecasting System Using Different FIS Deasy Adyanti; Dian Candra Rini Novitasar; Ahmad Hanif Asyhar; Fajar Setiawan
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (356.341 KB) | DOI: 10.11591/eecsi.v5.1617

Abstract

Adaptive Network Based Fuzzy Inference System (ANFIS) using time series analize is one of intelligent systems that can be used to predict with good accuracy in all fields like in meteorology. However, some research about forecasting has less emphasis on the structure of the FIS ANFIS. Thus, in this paper, the optimization of the ANFIS model for predicting maritime weather is carried out by analyzing the appropriate initialization determinations of the three fuzzy Inference structures ANFIS which includes FIS structure 1 (grid partition), FIS structure 2 (subtractive clustering) and FIS structure 3 (fuzzy c-means clustering). In this paper, the variable input used are two hours (t-2) and one hour (t-1) before, and data at that time (t), and the output of this system is the prediction of next hour, six hours, twelve hours and next day of variable ocean currents velocity (cm/s) and wave height (m) using the three FIS ANFIS approaches. Based on the smallest goal error (RMSE and MSE) of the three FIS ANFIS approaches used to predict the ocean currents speed (velocity) and wave height, the model is best generated by subtractive clustering. It can be seen that subtractive clustering produces the smallest RMSE and MSE error values of other FIS structure.
Automated Diagnosis System of Diabetic Retinopathy Using GLCM Method and SVM Classifier Ahmad Zoebad Foeady; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar; Muhammad Firmansjah
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.455 KB) | DOI: 10.11591/eecsi.v5.1630

Abstract

Diabetic Retinopathy (DR) is the cause of blindness. Early identification needed for prevent the DR. However, High hospital cost for eye examination makes many patients allow the DR to spread and lead to blindness. This study identifies DR patients by using color fundus image with SVM classification method. The purpose of this study is to minimize the funds spent or can also be a breakthrough for people with DR who lack the funds for diagnosis in the hospital. Pre-processing process have a several steps such as green channel extraction, histogram equalization, filtering, optic disk removal with structuring elements on morphological operation, and contrast enhancement. Feature extraction of preprocessing result using GLCM and the data taken consists of contrast, correlation, energy, and homogeneity. The detected components in this study are blood vessels, microaneurysms, and hemorrhages. This study results what the accuracy of classification using SVM and feature from GLCM method is 82.35% for normal eye and DR, 100% for NPDR and PDR. So, this program can be used for diagnosing DR accurately.
ANALISIS SINYAL EKG ARITMIA UNTUK DETEKSI RISIKO JANTUNG KORONER MENGGUNAKAN ADAPTIVE NEURO FUZZY INFERENCE (ANFIS) Dian Candra Rini; Ahmad Hanif Asyhar; Moh. Hafiyusholeh; Gita Purnamasari R; Yuyun Monita
MathVisioN Vol 1 No 1 (2019): Maret 2019
Publisher : Prodi Matematika FMIPA Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (131.542 KB)

Abstract

Sinyal EKG (Elektrokardiograf) merupakan sinyal yang digunakan untuk mendeteksi irama jantung. Irama jantung dari setiap orang berbeda-beda,terlebih jika orang tersebut berisiko penyakit jantung koroner (PJK). Dalam penulisan ini bertujuan untuk mengklasifikasikan data dari sinyal EKG aritmia ke antara kelompok yang berisiko terkena PJK atau yang tidak berisiko. Penelitian ini menggunakan metode Adaptive Neuro Fuzzy Inference System (ANFIS) serta tranformasi wavelet dan penerapan filter Infinite Impuls Respons (IIR) pada pengolahan sinyal. Hasil akurasi dari data 22 testing yang digunakan yaitu sebesar 90,9%
PENGELOMPOKKAN SUNSPOT PADA CITRA MATAHARI DENGAN MENGGUNAKAN K-MEANS CLUSTERING Rifa Atul Hasanah; Dian Candra Rini Novitasari; Nanang Widodo; Ahmad Hanif Asyhar
MathVisioN Vol 1 No 02 (2019): September 2019
Publisher : Prodi Matematika FMIPA Unirow Tuban

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.616 KB)

Abstract

Pada lapisan fotosfer nampak sunspot atau bintik matahari yang mana sunspot tersebut dapat menimbulkan ledakan-ledakan, seperti ledakan dahsyat (flare) dan pelontaran massa korona (Coronal Mass Ejection/CME). Ledakan-ledakan ini dapat mengganggu komunikasi radio frekuensi tinggi dan kebisingan radio yang mengganggu komunikasi dan sistem radar. Untuk mengetahui tingkat kompleksitas grup sunspot dan aktivitasnya digunakan klasifikasi metode Zurich, yang berisi tentang klasifikasi jenis grup sunspot. Informasi ini sangat penting untuk mengetahui seberapa besar gangguan yang didapatkan dari jenis grup sunspot tersebut. Tujuan dari penulisan yaitu untuk meneliti bagaimana mengelompokkan sunspot pada citra matahari dengan menggunakan K-Means Clustering. Pengolompokan sunspot menggunakan data citra matahari. Citra matahari diproses untuk diambil posisi x,y. Pengambilan posisi x, y sesuai dengan piksel sunspot yang digunakan untuk proses clustering. Hasil penelitian yaitu cluster piksel sunspot yang menunjukkan grup sunspot, hasil clustering telah menunjukkan hasil yang baik dengan nilai Silhouette Coefficient sebesar 0.9381, yang berarti bahwa struktur dari cluster termasuk kuat.
Peramalan Kecepatan Angin yang Direkam oleh Sistem AWS dengan Analisis Fuzzy Time Series Fajar Darwis Dzikril Hakimi; Moch. Noor Affan Anshori; Ahmad Hanif Asyhar
KUBIK Vol 2, No 2 (2017): KUBIK : Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v2i2.1857

Abstract

Kehidupan manusia tidak bisa dipisahkan dari faktor alam yang bernama cuaca. Salah satunya yaitu kecepatan angin. Angin mempunyai banyak manfaat bagi kehidupan manusia. Tetapi, angin juga bisa mempunyai dampak buruk bagi manusia. Untuk mengantisipasi dampak buruk yang ditimbulkan oleh angin, maka diperlukan peramalan kecepatan angin. Selain itu, adanya krisis energi global juga menyebabkan pengembangan energi terbarukan yang salah satunya adalah energi angin. Jurnal ini berisi tentang peramalan data kecepatan angin dengan analisis fuzzy time series. Hasil error peramalan dihitung dengan metode MSE dan didapat error sebesar 1,0909. 
Does opportunity to learn explain the math score gap between madrasah and non-madrasah students in Indonesia? Ahmad Umar; Kusaeri Kusaeri; Ali Ridho; Ahmad Yusuf; Ahmad Hanif Asyhar
Jurnal Cakrawala Pendidikan Vol 41, No 3 (2022): Cakrawala Pendidikan (October 2022)
Publisher : LPMPP Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/cp.v41i3.40169

Abstract

The opportunity to learn (OTL) is one of the important aspects of achieving the goal of the learning process. There have been three dimensions of OTL: instructional time (IT), content covered during instruction (CC), and quality of instruction (QI) mentioned in the literature and used as a framework in this article. This study aims to reveal the gap in math ability between madrasah and non-madrasah students in Indonesia and the contribution of the three OTL aspects toward math scores. This study employed a cross-sectional survey approach with self-report instruments. The data were obtained from a survey of participants in the New Students National Selection for Madrasah Aliyah Negeri (Islamic High-school managed by the ministry of religious affairs) in 2021. There were 8,258 participants, consisting of 4,842 students from madrasah and 3,416 from non-madrasah. This study used multilevel structural equation modeling (SEM) to analyze the data. The findings show that (a) there is a gap in math ability score between madrasah and non-madrasah students which is -27, with a mean math ability score of madrasah students being lower than non- madrasah students, and (b) the time invested in learning significantly affects the occurrence of gaps in math ability scores, while the scope of the materials and the quality of learning do not affect the occurrence of the gap in math ability scores. These findings suggest that it is important for the Ministry of Religious Affairs to consider the addition of mathematical lesson duration in madrasah while restructuring the allocation for Islamic lessons.
Analisis Sentimen Ulasan Aplikasi Jamsostek Mobile Menggunakan Metode Support Vector Machine Vina Fitriyana; Lutfi Hakim; Dian Candra Rini Novitasari; Ahmad Hanif Asyhar
Jurnal Buana Informatika Vol. 14 No. 01 (2023): Jurnal Buana Informatika, Volume 14, Nomor 1, April 2023
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v14i01.6909

Abstract

Sentiment Analysis of Jamsostek Mobile Application Reviews Using the Support Vector Machine Method. Today's technology is evolving quickly, leading to new developments that have helped produce JMO and other mobile applications that can be useful to Indonesians. The reviews or comments in the JMO can be used as a gauge for quality and user satisfaction. This study aims to analyze the quality of JMO applications and classify reviews or opinions into positive, negative, and neutral categories through sentiment analysis. The Support Vector Machine method is used in this analysis process with a linear kernel approach to determine the level of accuracy of classifying JMO application reviews. Research shows that classifying the SVM method against sentiment analysis of reviews or JMO application reviews produces the best accuracy scores, obtaining results with accuracy of 96%, precision of 92%, recall of 96%, and f1-score of 94%, while for the results of most reviews are positive category reviews with a total of 17.571.Keywords: sentiment analysis, JMO, SVM, linear kernel   Perkembangan pesat teknologi saat ini memunculkan inovasi baru untuk menciptakan berbagai aplikasi mobile yang dapat memberi kemudahan bagi masyarakat Indonesia, salah satunya yaitu JMO. Penelitian ini bertujuan untuk menganalisis kualitas aplikasi JMO dan mengklasifikasikan ulasan atau opini kedalam kategori positif, negatif dan netral melalui analisis sentimen. Metode Support Vector Machine digunakan pada proses analisis ini dengan pendekatan kernel linear untuk mengetahui tingkat akurasi dari pengklasifikasian ulasan aplikasi JMO tersebut. Penelitian menunjukkan bahwa pengklasifikasian metode SVM terhadap analisis sentimen ulasan atau review aplikasi JMO menghasilkan nilai akurasi terbaik, didapatkan hasil dengan accuracy 96%, precision 92%, recall 96%, dan f1-score 94%, sedangkan untuk hasil ulasan terbanyak adalah ulasan berkategori positif dengan jumlah 17.571.Kata Kunci: analisis sentimen, JMO, SVM, kernel linear
Analisis Perbandingan Pengelompokan Kota di Indonesia Berdasarkan Indikator Inflasi Tahun 2021 dengan Metode Ward dan K-Means Lia Puspita Sari; Aris Fanani; Ahmad Hanif Asyhar
Jurnal Sains Matematika dan Statistika Vol 9, No 2 (2023): JSMS Juli 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jsms.v9i2.21100

Abstract

Inflasi merupakan suatu kondisi perekonomian yang menujukkan adanya kecenderungan kenaikan tingkat harga umum karena barang dan jasa yang ada di pasaran mempunyai jumlah dan jenis yang sangat beragam, sebagian besar dari harga-harga tersebut selalu meningkat dan mengakibatkan terjadinya inflasi. Perhitungan laju inflasi salah satunya adalah menggunakan Indeks Harga Konsumen (IHK), indeks ini disusun dari harga barang dan jasa yang dikonsumsi oleh masyarakat. Penelitian ini membahas tentang perbandingan pengelompokan kota di Indonesia berdasarkan indikator inflasi metode Ward dan K-Means dengan menggunakan 11 variabel kelompok pengeluaran pada IHK. Evaluasi metode dilakukan dengan membandingkan nilai rasio simpangan baku dari masing-masing metode. Berdasarkan hasil penelitian jumlah cluster yang dihasilkan adalah sebanyak 3 cluster, dengan nilai rasio simpangan baku yang diperoleh menggunakan metode Ward adalah 1,77, sedangkan dengan metode K-Means adalah sebesar 1,43. Dengan demikian hasil cluster yang bisa digunakan sebagai rujukan pada pengelompokan kota di Indonesia berdasarkan indikator inflasi adalah hasil analisis cluster menggunakan metode K-Means.  
Pendampingan Guru Madrasah untuk Mewujudkan Kompetensi Pedagogik Guru Matematika yang Berdaya Melalui Penguasaan Soal High Order Thinking Skills (HOTS) Moh Hafiyusholeh; Ahmad Lubab; Ahmad Hanif Asyhar; Aris Fanani; Yuniar Farida; Dian C. Rini Novitasari; Nurissaidah Ulinnuha; Putroue Keumala Intan; Wika Dianita Utami; Zainullah Zuhri; Ahmad Zaenal Arifin; Dian Yuliati; Abdulloh Hamid
Engagement: Jurnal Pengabdian Kepada Masyarakat Vol 4 No 1 (2020): May 2020
Publisher : Asosiasi Dosen Pengembang Masyarajat (ADPEMAS) Forum Komunikasi Dosen Peneliti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/engagement.v4i1.97

Abstract

High Order Thinking Skills (HOTS) is the ability to connect, manipulate, and change the knowledge and experience that is owned critically and creatively in determining decisions to solve problems in new situations. To include HOTS questions in a learning process is an obstacle for Madrasah teachers, including teachers of PC. LP. Maarif NU Lamongan. This community service aimed at improving the pedagogical competence of mathematics teachers of PC. LP. Maarif NU Lamongan. Community-Based Research (CBR) was employed through workshop and training administered by the Mathematics Study Program of UIN Sunan Ampel Surabaya in designing and completing high order thinking questions followed by assistance. The results indicated that the ability of Madrasah teachers to solve HOTS questions as well as its implementation in classroom teaching and learning activities improved significantly.
Determination of the Beginning of Prayer Time on the Mount Prau Hiking Trail by Applying Spherical Trigonometry Nur Aulia, Shofinatul Wahdah; Hamid, Abdulloh; Yuliati, Dian; Asyhar, Ahmad Hanif; Khaulasari, Hani
Al-Marshad: Jurnal Astronomi Islam dan Ilmu-Ilmu Berkaitan Vol 10, No 1 (2024): Al-Marshad
Publisher : University of Muhammadiyah Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jam.v10i1.18366

Abstract

Determining the beginning of prayer time on the Mount Prau hiking trail is very important for Muslims, especially when performing the five daily prayers. Calculation of the beginning of prayer time is important even though prayers can be performed within a certain time range. This study aims to apply spherical trigonometric calculations and to determine the results of the beginning of prayer time on the Mount Prau hiking trail. This research uses spherical trigonometry hisab method with the required data are latitude of place, longitude of place, solar declination and equation of time. The calculation results show the exact prayer time, such as dawn between 04.24 to 04.29 WIB, zuhur between 11.39 to 11.44 WIB, asar between 15.01 to 15.05 WIB, maghrib between 17.32 to 17.36 WIB and isya between 18.46 to 18.51 WIB. This information is useful for climbers of Mount Prau so that they can carry out worship on time.
Co-Authors Abdulloh Hamid Abdulloh Hamid Adyanti, Deasy Adyanti, Deasy Alfiah Ahmad Hidayatullah Ahmad Umar Ahmad Zaenal Arifin Ahmad Zoebad Foeady Ali Ridho Anistya, Mery Arifin, Ahmad Zaenal Deasy Adyanti Deasy Alfiah Adyanti Dian C. Rini Novitasari Dian Yuliati Fajar Darwis Dzikril Hakimi FAJAR SETIAWAN Fajar Setiawan Fanani, Aris Farida, Yuniar Firmansjah, Muhammad Fitria Febrianti Foeady, Ahmad Zoebad Fransisca, Velicia Gita Purnamasari R Hani Khaulasari Hidayati, Syahrotul Hilmi, Moh. Aditya Sirojul ian Candra Rini Novitasari Krisnawan, Alvin Kusaeri Kusaeri Lia Puspita Sari Lubab, Ahmad Lutfi Hakim Lutfi Hakim M. Hasan Bisri Maulidya, Rahmania Moch. Noor Affan Anshori Moh. Hafiyusholeh Muhammad Busyro Karim Muhammad Busyro Karim, Muhammad Busyro Muhammad Thohir Nanang Widodo Nisa, Titin Faridatun Novitasari , Dian Candra Rini Novitasari, Dian C Rini Nur Aulia, Shofinatul Wahdah Nurissaidah Ulinnuha Putri Oktavia, Nabiilah Putri, Anindya Maya Putri, Risma Madurahma Putroue Keumala Intan Rifa Atul Hasanah Rini Novitasari, ian Candra Ririn Komaria Rozi, Muhammad Fahrur Sari, Dian Candra Rini Novita Sari, Firda Yunita Setiawan, Fajar Suwanto Suwanto Utami, Wika Dianita Vina Fitriyana Wahyudi, Sharenada Norisdita Widiaputra, Muhammad Iqbal Wika Dianita Utami Wika Dianita Utami Yuliati, Dian Yuliati, Dian Yusuf, Ahmad Yuyun Monita Zainullah Zuhri