PREDICTION OF ECONOMIC GROWTH RATE OF TUBAN REGENCY WITH ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM ALGORITHM Maya Muaziza, Ahmad Zaenal Arifin, Suzatmo Putro Barekeng, 2025 This research aims to implement and evaluate the accuracy of the Adaptive Neuro Fuzzy Inference System (ANFIS) forward stage method to predict the economic growth rate of the Tuban Regency. In the application of ANFIS, two types of variables are required, namely, input variables which include road length, the number of electricity customers, the number of health workers, the number of high schools, and the number of cases of ordinary theft. Meanwhile, the predicted output variable is the economic growth rate. The fuzzification process uses a triangular membership function to map the input values. The data used in this study were obtained from the Central Bureau of Statistics (BPS) of Tuban Regency for 2014-2024. The prediction results show a very low Mean Absolute Percentage Error (MAPE) value of 0.14%, which reflects a very high level of accuracy. With MAPE < 10%, the accuracy of this model reaches 99.86% based on calculations made through the Matlab GUI. This research shows that the Adaptive Neuro Fuzzy Inference System (ANFIS) method can be used effectively and accurately to predict the economic growth rate of the Tuban Regency.
Simulation of Tsunami Wave Propagation Using the Finite Difference Method for Disaster Early Warning System Nonlinear Dynamics and Systems Theory, 2025
Vaccine Effectiveness Impact on the COVID-19 Dynamics Spread Outbreak Using Improved SEIR Mathematical Epidemic Model Thai Journal of Mathematics, 2024
MODEL DESIGN OF SOCIOPRENEURSHIP: HALAL BASED-DEVELOPMENT OF MICRO, SMALL AND MEDIUM ENTERPRISES THROUGH ZAKAT INSTITUTIONS Siti Nur Azizah Siti Nur Azizah, Annisa Nur Salam, Ahmad Zaenal Arifin Isra International Journal of Islamic Finance, 2023 Purpose — This study aims to examine the extent to which halal branding and digital media utilisation affect consumer behaviour. It also intends to provide an overview of the sociopreneurship model—a model that targets both financial and social benefits, while also working to solve problems in the community—to empower micro, small and medium enterprises (MSMEs) through the use of halal branding and digital media managed by zakat institutions.Design/Methodology/Approach — In the first stage, this study employs a quantitative approach to analyse the factors of digital use and halal branding in influencing consumer behaviour. In this respect, multiple linear regression was used to analyse 172 research respondents. In the second stage, it uses a qualitative approach in designing a sociopreneurship model based on the results of the first stage.Findings — This study found that religiosity and halal branding have a positive and significant effect on Muslim interest in buying halal products. In addition, the factors of price, religiosity and halal branding also positively and significantly affect satisfaction in consuming halal products. The sociopreneurship model can be applied to zakat institutions to facilitate MSMEs in developing product quality through halal branding and digital utilisation.Originality/Value — The unique characteristic of this study lies in the use of both the quantitative and qualitative approaches in carrying out this research. It is hoped that the model offered in this study will be able to develop the MSME sector to keep abreast of modern trends despite the limited capital available to such institutions.Research Limitations/Implications — The sample used in this study was restricted to Indonesia, with a limited number of respondents. Moreover, data collection was conducted through questionnaires without in-depth interviews with consumers, MSMEs and zakat institutions.Practical Implications — The zakat institution’s scheme or model of sociopreneurship will be beneficial for the modern development of MSMEs even though they possess limited capital. Zakat institutions provide three types of assistance: 1) direct monitoring that starts from production inputs to the production process and which continues to the distribution process to ensure that the products developed by the fostered MSMEs are truly halal; 2) assistance at the digital marketing stage; and 3) assistance in accessing loan funds under qarḍ ḥasan (benevolent loans) schemes.Social Implications — This research has a social impact on the development of MSMEs through the implementation of the concept of sociopreneurship. In this case, MSME actors who are classified as donation recipients can turn into donors, which would assist in reducing poverty levels. Therefore, social and business benefits will be achieved through the modern development of MSMEs.
Tsunami Wave Simulation in the Presense of a Barrier Nonlinear Dynamics and Systems Theory, 2023
Study of the Use of Block Compos on the Growth of Teak (Tectona grandis) in Used Lands of Kapur Stone Mine Supiana Dian Nurtjahyani, Dwi oktafitria, Sriwulan, Ahmad Zaenal Arifin, Eko Purnomo, Aris Santoso, Ali Mustofa Iop Conference Series Earth and Environmental Science, 2021 The limestone mining area is a karst area that has an important ecological function as a water conservation area. After the mining process, the ex-mining area becomes critical land that is poor in nutrients, decreases soil microbial diversity, increases soil pH and temperature. This study aimed to examine the use of conventional and block compost based on plant height parameters and stem diameter. Block compost was made using the bokashi method with the ingredient of teak leaf litter (Tectona grandis). The composition of leaf litter (30%), manure (40%), and sawdust (30%). Block compost is made by adding adhesive and it is made using a pressing device. Block compost application on plants is very effective compared without block compost. The average plant height with block compost is 163.2 cm, while without block compost is 27 cm. the average of stem growth diameter of plants with block compost of 1.61 cm, while without block compost was 0.71 cm. This shows that block compost is a solution in mining land reclamation.
Rainfall Prediction Based on Himawari-8 IR Enhanced Image Using Backpropagation D C R Novitasari, B D Supatmanto, M F Rozi, Hermansah, Y Farida, Rr D N Setyowati, Ilham, R Junaidi, A Z Arifin, A R Fatoni Journal of Physics Conference Series, 2020 The wider sea area causes greater evaporation of water in Indonesia. In addition, these conditions have an impact on the season that Indonesia has. Indonesia’s high rainfall disrupts human activities. As a result, it is very important to detect cumulonimbus clouds using satellite imagery. The satellite image used is intended to be taken two values of the characteristics possessed. Characteristics taken are average cover and average cloud temperature. Previous studies predicting rain were only done using observational data taken at the height of 10 meters. This research predicts using satellite imagery that represents the cloud peak temperature value. Furthermore, the classification of data is done using backpropagation. The results of the classification process using backpropagation obtained the best results on the distribution of 80% training data and 20% testing data, with the activation function logging in the hidden layer and that the output layer. The results obtained indicate the accuration rate of 88,283%.
Automatic Approach for Cervical Cancer Detection Based on Deep Belief Network (DBN) Using Colposcopy Data Dian Candra Rini Novitasari, Ahmad Zoebad Foeady, Muhammad Thohir, Ahmad Zaenal Arifin, Khoirun Niam, Ahmad Hanif Asyhar 2020 International Conference on Artificial Intelligence in Information and Communication Icaiic 2020, 2020 Cervical cancer is one of the diseases with the highest mortality rate. In the world, cervical cancer is ranked as the fourth most dangerous disease. Based on these problems, this paper can be an alternative to help medical authorities in detecting cervical cancer with the help of the Computer-Aided Diagnosis (CAD) System. CAD System used has two processes, such as preprocessing and classification. Preprocessing is useful to improve the image so that it is easier to do the process of identifying features. Preprocessing used is greyscale, histogram equalization, and median filter. Preprocessing results will be formed into a vector matrix using the reshaping process. The final step is the process of classifying data using the Deep Belief Network method. The best accuracy results obtained from the identification process of cervical cancer using the DBN method is 84%. Based on the results of accuracy, is expected to help reduce the number of deaths from cervical cancer with early detection.
Implementation LSTM Algorithm for Cervical Cancer using Colposcopy Data Ahmad Hanif Asyhar, Ahmad Zoebad Foeady, Muhammad Thohir, Ahmad Zaenal Arifin, Dina Zatusiva Haq, Dian Candra Rini Novitasari 2020 International Conference on Artificial Intelligence in Information and Communication Icaiic 2020, 2020 Cervical cancer ranks second highest cause of death in women in various worlds. This happens because most women are not aware of the symptoms of cervical cancer in the early stages. To reduce the number of deaths caused by cervical cancer by identifying the symptoms of cervical cancer in the early stages. Identification of early symptoms of cervical cancer can be made with colposcopy tests that produce colposcopy image data. Colposcopy test is a method to identify cervical cancer based on images of the cervix with an enlargement of up to 10 times and it gets accurate results. Accuracy results from colposcopy tests can be improved by using computational calculations. Besides being used to improve accuracy, computational calculations also make it easier for people to detect cervical cancer. In this study, computational calculations are performed by implementing the Long Short-Term Memory (LSTM) algorithm to identify cervical cancer using colposcopy data. The implementation of the LSTM algorithm in the classification process of colposcopy data with an optimal number of hidden layers of 150 hidden layers results in an accuracy rate of 66%.
Classification of Colposcopy Data Using GLCM-SVM on Cervical Cancer Muhammad Thohir, Ahmad Zoebad Foeady, Dian Candra Rini Novitasari, Ahmad Zaenal Arifin, Bunga Yuwa Phiadelvira, Ahmad Hanif Asyhar 2020 International Conference on Artificial Intelligence in Information and Communication Icaiic 2020, 2020 cervical cancer is the second deadliest disease for women. To reduce the number of deaths caused by this disease, it is necessary that there is prevention by early detection of cancer. The method used to identify the presence of cervical cancer is to make visual observations that produce image data. However, a visual observation also has weaknesses, so it needs to be done computer-based observation to facilitate early detection. In this study, the computer-based observation method used is preprocessing, followed by a feature extraction process using the Gray Level Co-occurrence Matrix (GLCM) and Support Vector Machine (SVM) as a classification method. The best SVM classification results are using the polynomial kernel and GLCM feature extraction with an angle of 450. The accuracy rate obtained is 90%.
Peramalan Curah Hujan di Kabupaten Tuban Menggunakan Algoritma KNN V Fatimah, AZ Arifin, S Putro Imajiner: Jurnal Matematika dan Pendidikan Matematika 7 (4), 297-307 , 2025 2025 Citations: 1
PREDICTION OF ECONOMIC GROWTH RATE OF TUBAN REGENCY WITH ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM ALGORITHM M Muaziza, AZ Arifin, S Putro BAREKENG: Jurnal Ilmu Matematika dan Terapan 19 (3), 1699-1710 , 2025 2025
Upaya Peningkatan Penjualan Beras Leran Melalui Pengemasan Dan Labeling AZ Arifin, S Sriwulan, N Nurfitria, K Febriyantiningrum, SD Anggraini, ... Jurnal Abdisembrani 3 (1), 1-6 , 2025 2025 Citations: 3
Simulation of Tsunami Wave Propagation Using the Finite Difference Method for Disaster Early Warning System. AZ Arifin, Sriwulan, MI Joesidawati, T Herlambang, S Mizan, AA Suryanto Nonlinear Dynamics & Systems Theory 25 (1) , 2025 2025
Pemodelan Waktu Keberangkatan Bus pada Angkutan antar Kota antar Provinsi Jalur Semarang-Surabaya Menggunakan Aljabar Max-Plus A Muzammil, AZ Arifin 2024
A ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERBEDAAN UPAH DI KABUPATEN TUBAN MENGGUNAKAN PENDEKATAN REGRESI LINIER BERGANDA: ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI PERBEDAAN … I Lailannaza, AZ Arifin MathVision: Jurnal Matematika 6 (1), 29-36 , 2024 2024 Citations: 1
Vaccine Effectiveness Impact on the COVID-19 Dynamics Spread Outbreak Using Improved SEIR Mathematical Epidemic Model F Akbar, AH Asyhar, A Lubab, A Hamid, M Hafiyusholeh, DCR Novitasari, ... Thai Journal of Mathematics 22 (3), 485-502 , 2024 2024
APLIKASI PEWARNAAN GRAF PADA PENYUSUNAN JADWAL MATA KULIAH DI PROGRAM STUDI MATEMATIKA UNIVERSITAS PGRI RONGGOLAWE AZ Arifin, S Mizan Prosiding SNasPPM 8 (1), 538-543 , 2023 2023
PENDAMPINGAN PEMBUATAN DESAIN KEMASAN DAN PEMASARAN BERAS “LERAN” DI DESA LERAN WETAN KECAMATAN PALANG KABUPATEN TUBAN AZ Arifin, S Sriwulan, SD Anggraini, K Febriyantiningrum, N Nurfitria, ... Prosiding SNasPPM 8 (1), 175-182 , 2023 2023
IMPLEMENTATION OF THE QUEUE SYSTEM MODEL [M/M/1]:[GD/∞/∞] IN THE DOCTOR QUEUE SERVICE PROCESS AT JETAK HEALTH CENTER, TUBAN DISTRICT AZ Arifin, AK Mustofa MathVision: Jurnal Matematika 5 (2), 63-69 , 2023 2023
PENYUSUNAN JADWAL MATA KULIAH DI PROGRAM STUDI MATEMATIKA UNIVERSITAS PGRI RONGGOLAWE MENGGUNAKAN PEWARNAAN GRAF AZ Arifin, S Mizan MathVision: Jurnal Matematika 5 (2), 53-57 , 2023 2023
POTENSI EKOLOGI DARI KEANEKARAGAMAN BURUNG MIGRAN DI AREA GREENBELT PENAMBANGAN BATU KAPUR DAN TANAH LIAT D Oktafitria, AN Fuadi, AN Aina, S Sriwulan, SD Nurtjahyani, C Khotimah, ... Biology Natural Resources Journal 2 (1), 19-23 , 2023 2023 Citations: 1
PENYUSUNAN JADWAL MATA KULIAH DENGAN MENGGUNAKAN ALGORITMA WELCH-POWEL: STUDI KASUS: PROGRAM STUDI PENDIDIKAN GURU SEKOLAH DASAR DI UNIVERSITAS PGRI RONGGOLAWE TUBAN AR Setiawan, AZ Arifin, N Nurfitria Prosiding New SNASPPM 8 (2), 788-794 , 2023 2023
Tsunami Wave Simulation in the Presense of a Barrier K Oktafianto, AZ Arifin, EF Kurniawati, T Tafrikan, T Herlambang, ... Nonlinear Dynamics and Systems Theory 23 (1), 69-78 , 2023 2023 Citations: 5
PENDAMPINGAN MANAJEMEN PENERIMA HIBAH PENCAPAIAN TARGET KONSUMSI PANGAN PERKAPITA TAHUN 2021 SESUAI ANGKA KECUKUPAN GIZI KABUPATEN TUBAN S Suwarsih, MI Joesidawati, S Sriwulan, R Andriani, SD Anggraini, ... DedikasiMU: Journal of Community Service 4 (4), 384-399 , 2022 2022
ANALISIS WAKTU TUNGGU LAMPU LALU LINTAS DAN LEBAR JALAN TERHADAP TINGKAT KEMACETAN MENGGUNAKAN REGRESI LINEAR BERGANDA AZ Arifin, S Mizan MathVision: Jurnal Matematika 4 (2), 55-58 , 2022 2022
OPTIMALISASI WAKTU LAMPU LALU LINTAS DI PERSIMPANGAN JALAN DENGAN METODE ALJABAR MAX-PLUS:(STUDI KASUS: PERSIMPANGAN POLRES TUBAN DAN GOR RANGGA JAYA ANORAGA TUBAN) A Afifah, AZ Arifin, K Oktafianto Prosiding SNasPPM 7 (1), 500-505 , 2022 2022
PEMBERDAYAAN POKJA 3 TP PKK DESA PEKUWON KECAMATAN RENGEL KABUPATEN TUBAN DALAM PROSES PEMBUATAN JAMU INSTAN DARI TANAMAN TOGA PEKARANGAN RUMAH K Febriyantiningrum, S Sriwulan, N Nurfitria, AZ Arifin Prosiding SNasPPM 7 (1), 764-769 , 2022 2022
ANALISIS PENGARUH VOLUME KENDARAAN DAN LEBAR JALAN TERHADAP WAKTU LAMPU LALU LINTAS SERTA MENENTUKAN WAKTU LAMPU LALU LINTAS YANG OPTIMAL: STUDI KASUS: PERSIMPANGAN POLRES TUBAN V Novawati, AZ Arifin Prosiding SNasPPM 7 (1), 476-482 , 2022 2022
ANALISIS WAKTU LAMPU LALU LINTAS DAN DESAIN ARAH ARUS LALU LINTAS DI PEREMPATAN KARANGWARU KABUPATEN TUBAN AZ Arifin, S Mizan Prosiding SNasPPM 7 (1), 774-780 , 2022 2022
MOST CITED SCHOLAR PUBLICATIONS
Pelatihan Pembuatan Ujian Berbasis Computer Base Test (Cbt) Bagi Guru Sma/Ma Dikabupaten Tuban AZ Arifin Prosiding SNasPPM 4 (1), 281-283 , 2019 2019 Citations: 59
Pengembangan Desain Pembelajaran Basic Mathematic dengan Metode Estafet Kartu K Oktafianto, EF Kurniawati, L Muzdalifah, AZ Arifin, N Nurfitria, A Afifah, ... Abdimas Universal 1 (2), 24-26 , 2019 2019 Citations: 47
The Effect of Hate Speech Exposure on Religious Intolerance Among Indonesian Muslim Teenagers A Muhid, M Hadi, A Fanani, A Arifin, A Hanif 2019 Ahmad Dahlan International Conference Series on Education & Learning … , 2019 2019 Citations: 34
Automatic Approach for Cervical Cancer Detection Based on Deep Belief Network (DBN) Using Colposcopy Data DCR Novitasari, AZ Foeady, M Thohir, AZ Arifin, K Niam, AH Asyhar 2020 International Conference on Artificial Intelligence in Information and … , 2020 2020 Citations: 32
Optimasi Pada Misil Menggunakan Bang-Bang control dan Ensamble Kalman Filter AZ Arifin Technology Science and Engineering Journal 1, 71-86 , 2017 2017 Citations: 32
Classification of Colposcopy Data Using GLCM-SVM on Cervical Cancer M Thohir, AZ Foeady, DCR Novitasari, AZ Arifin, BY Phiadelvira, ... 2020 International Conference on Artificial Intelligence in Information and … , 2020 2020 Citations: 27
Cervical Cancer Identification Based Texture Analysis Using GLCM-KELM on Colposcopy Data DCR Novitasari, AH Asyhar, M Thohir, AZ Arifin, H Mu'jizah, AZ Foeady 2020 International Conference on Artificial Intelligence in Information and … , 2020 2020 Citations: 25
Simulasi Sebaran Abu Pabrik Kapur Menggunakan Metode Beda Hingga R Awanda, K Oktafianto, AZ Arifin, N Fatihah Zeta-Math Journal 4 (2), 34-39 , 2019 2019 Citations: 24
Prediksi Tingkat Pengangguran Di Kabupaten Tuban Tahun 2020 Menggunakan Metode Regresi Linear Sederhana N Ariyani, AZ Arifin MathVision: Jurnal Matematika 3 (1), 6-13 , 2021 2021 Citations: 21
Pendampingan Guru Madrasah untuk Mewujudkan Kompetensi Pedagogik Guru Matematika yang Berdaya Melalui Penguasaan Soal High Order Thinking Skills (HOTS) M Hafiyusholeh, A Lubab, AH Asyhar, A Fanani, Y Farida, DCR Novitasari, ... Engagement: Jurnal Pengabdian Kepada Masyarakat 4 (1), 183-200 , 2020 2020 Citations: 19
Sebaran Debu Jubung Pabrik Kapur dengan Gaussian Plume AZ Arifin, K Oktafianto, R Awanda, N Fatihah MathVision: Jurnal Matematika 1 (02), 79-82 , 2019 2019 Citations: 18
Implementation LSTM Algorithm for Cervical Cancer using Colposcopy Data AH Asyhar, AZ Foeady, M Thohir, AZ Arifin, DZ Haq, DCR Novitasari 2020 International Conference on Artificial Intelligence in Information and … , 2020 2020 Citations: 17
Penerapan Fuzzy Inference System Dalam Pengoptimalan Suhu Ruangan Pada Double Air Conditioner (Ac) Secara Otomatis DC Rini, AZ Arifin, A Fanani, GBD Prasanda, WNP Sunaryo MathVision: Jurnal Matematika 1 (1), 11-16 , 2019 2019 Citations: 9
Identification and Analysis of Macrozoobenthos in The Reclamation Land Area of Lime Mining SD Nurtjahyani, D Oktafitria, AZ Arifin, S Sriwulan, AY Pambudi, ... Advances in Tropical Biodiversity and Environmental Sciences 6 (2), 45-49 , 2022 2022 Citations: 8
Upaya Pembinaan Pembentukan Kampung Salak sebagai Kampung Wisata di Kabupaten Tuban AZ Arifin, S Sriwulan, D Oktafitria Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming 4 (1), 123-130 , 2021 2021 Citations: 8
MODEL DINAMIK PENYAKIT TUBERCULOSIS DI KABUPATEN TUBAN MENGGUNAKAN SIR (Susceptible, Infectious, Reccovered) K Amin, K Oktafianto, AZ Arifin Prosiding SNasPPM 3 (1), 438-441 , 2018 2018 Citations: 8
MUTU ORGANOLEPTIK IKAN ASAP HASIL PENGASAPAN DENGAN ALAT ASAP EFHILINK MENGGUNAKAN SUMBER BAHAN BAKAR BERBEDA SD Anggraini, AZ Arifin Prosiding SNasPPM 6 (1), 614-620 , 2021 2021 Citations: 7
PENERAPAN METODE QUALITY FUNCTION DEPLOYMENT GUNA MENINGKATKAN KUALITAS PELAYANAN JASA PADA KOPERASI MAHASISWA UNIROW TUBAN K Oktafianto, AY Rathomi, N Fatihah, A Wulandari, AZ Arifin MathVision: Jurnal Matematika 2 (2), 59-64 , 2020 2020 Citations: 7
Simulasi Dampak Penghalang pada Gelombang Tsunami Menggunakan Persamaan Air Dangkal dengan Metode Beda Hingga AZ Arifin Jambura Journal of Mathematics 3 (2), 93-102 , 2021 2021 Citations: 6
Penggunaan Metode Backpropagation Untuk Peramalan Jumlah Ledakan Matahari (Flare) Y Monita, DCR Novitasari, N Widodo, AZ Arifin MathVision: Jurnal Matematika 1 (02), 67-71 , 2019 2019 Citations: 6
