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All Journal Jurnal Simetris Jurnal Sosioteknologi Jurnas Nasional Teknologi dan Sistem Informasi INFORMAL: Informatics Journal JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research Jurnal Komputer Terapan Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Elektronika dan Telekomunikasi Jurnal ULTIMATICS SISFO KOMPUTIKA - Jurnal Sistem Komputer INTEGRITAS : Jurnal Pengabdian Journal of Innovation Information Technology and Application (JINITA) Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Jurnal Nasional Teknik Elektro dan Teknologi Informasi Ilmu Komputer untuk Masyarakat Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal Pengabdian Masyarakat Bidang Sosial dan Humaniora Proceeding International Applied Business and Engineering Conference PAPUMA: Journal of Comunnity Services JGGAG (Journal of Games, Game Art, and Gamification)
Furqon, Muhammad Ariful
Departemen Informatika, Universitas Jember
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Virtual Assistant for Thesis Technical Guide Using Artificial Neural Network Mohammad Ovi Sanjaya; Saiful Bukhori; Muhammad `Ariful Furqon
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 2 (2023): September 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i2.23473

Abstract

This study focuses on finding best practice for Artificial Neural Network (ANN) implementation in the information system for student’s thesis technical instructions. The machine learning model applied sequential model, it means ANN only use 1 input layer, a hidden/dense layer and 1 output layer. The Stochastic Gradient Decent (SGD) method was applied into data training process. The results of this study are chatbot applications, and model testing using the confusion matrix. The result of model evaluation are 99,49% accuracy and 91% in F-1 score.
Customer Relationship Management System at Aesthetic Clinic nina fadilah najwa; Muhammad Ariful Furqon; Yosari Dwi Fadhillah
Jurnal Komputer Terapan Vol. 9 No. 2 (2023): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35143/jkt.v9i2.6159

Abstract

Accessing and processing information more effectively and efficiently is made possible through the employment of quality information technology, one of which is in the technology the clinic requires. According to our case study, the clinic is still manually documenting customer service data and experiencing declining repeat client visits. Utilizing information technology is necessary for efforts to boost customer value innovation. As one of its aspects, Customer Relationship Management uses a framework of dynamics to acquire customer satisfaction data from loyal customers. The utilization of customer data will be categorized into platinum, gold, and silver using a ranking system for decision-making with the Simple Additive Weighting method—rating customers through the normalization of a decision matrix. The maximum consumer value based on the parameters determined by the choice matrix is one, while the lowest is 0.27. The testing that has been conducted is black-box testing. It is determined that 100 percent of the system's functionality is operating correctly, and UAT testing reveals that all features operate properly. Usability Testing conducted on patients yielded a ratio of 78.1%, indicating that the clinic evaluated customer satisfaction with the customer relationship management system.
Prediksi Harga Cabai Rawit di Provinsi Jawa Timur Menggunakan Metode Fuzzy Time Series Model Lee Komaria, Vida; Maidah, Nova El; Furqon, Muhammad Ariful
Komputika : Jurnal Sistem Komputer Vol. 12 No. 2 (2023): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v12i2.10644

Abstract

ABSTRACT - East Java is the province with the most significant amount of chili pepper production in Indonesia based on data from BPS in 2021 which is around 41.75. Chili pepper is a commodity that high price fluctuations that will impact several parties, so a mechanism is needed to predict the price of chili pepper to become a consideration in decision making. Lee's fuzzy time series method can be used to predict time series stationary or non-stationary data. The research was conducted using historical data on the price of red and green chili peppers in East Java Province from April 2017 to February 2023 with a weekly data period of 307 data. The Z1 and Z2 values used to get the smallest error results are Z1 = 950 and Z2=400 for red chili peppers while for green chili peppers values the Z1 and Z2=100. The error value of forecasting red chili pepper prices is MAE = 4,469.04 RMSE = 6,138.64 MAPE = 13.09% (good MAPE value category) and the error value for green chili pepper is MAE = 1,486.15 RMSE = 2,211.06 and MAPE = 6.72% (very good MAPE value category). Keywords – forecasting; Lee’s fuzzy time series; chili pepper price; MAPE; Python
Implementasi Metode Holt-Winters Multiplicative pada Sistem Peramalan Pengunjung Objek Wisata Kawah Ijen Kabupaten Bondowoso Irawan, Hendry Sakti; Adiwijaya, Nelly Oktavia; Furqon, Muhammad ‘Ariful
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 14, No 2 (2023): JURNAL SIMETRIS VOLUME 14 NO 2 TAHUN 2023
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v14i2.9549

Abstract

Kawah Ijen merupakan salah satu destinasi wisata dengan tingkat kepadatan pengunjung paling tinggi diantara seluruh objek wisata di Kabupaten Bondowoso. Kendala yang paling sering dialami oleh wisata Kawah Ijen pada tahun 2017 - 2022 yaitu terkait jumlah kedatangan pengunjung yang tidak menentu dan peningkatan maupun penurunan yang signifikan di bulan tertentu. Pola seperti ini dinamakan pola data musiman dan tren. Metode Holt-Winters Multiplicative ini dianggap sangat tepat digunakan untuk peramalan dengan pola data musiman dan tren. Pengukuran tingkat kesalahan yang digunakan pada penelitian ini menggunakan metode MAPE. Hasil dari perhitungan nilai MAPE tanpa melampirkan data 2020 menghasilkan nilai MAPE yaitu sebesar 9 %, sedangkan hasil dari perhitungan MAPE dengan melampirkan data 2020 menghasilkan nilai MAPE yaitu sebesar 209 %. Hal ini menunjukkan bahwa terdapat dua perbandingan perhitungan MAPE dengan metode Holt-Winters Multiplicative. Dapat disimpulkan bahwa perhitungan metode HoltWinters Multiplicative tanpa melampirkan data 2020 memiliki MAPE dengan nilai 9 % dapat dikatakan sangat rendah karena memiliki rata-rata nilai MAPE dibawah 10%.
PELATIHAN DAN PENGENALAN TEKNOLOGI INFORMASI (TI) DASAR UNTUK ANAK-ANAK DESA AMPELAN BONDOWOSO Sari, Vega Kartika; Deana Nathania Damayanti; Naura, Lintang Arsa; Furqon, Muhammad
PAPUMA: Journal of Community Services Vol. 2 No. 02 (2024): Agustus 2024
Publisher : Program Studi Agronomi Fakultas Pertanian Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/papuma.v2i02.1377

Abstract

Ampelan Village, which is in Wringin District, Bondowoso Regency, has a large number of residents, including elderly residents, adults and children. One of the problems in Ampelan Village is the lack of children's understanding of the world of technology. In fact, understanding it is currently very necessary, especially for children who are currently studying as a preparation for facing future challenges. One of the programs carried out in Ampelan Village is basic IT training for children which aims to equip the younger generation with digital skills so they can keep up with developments that are closely related to digitalization in education. This program is designed to provide a basic understanding of the use of computers, the internet and platforms to support their school work. The activity was attended by 31 children, who were very enthusiastic during the activity. The result of this activity was an increase in participants' understanding of the basics of navigation on laptops, typing, and the use of Microsoft Word and Microsoft PowerPoint. The hope is that this program can help access the introduction of technology education in rural areas to reduce the digital divide.
Sentiment Analysis of Universitas Jember’s Sister for Student Application Using Gaussian Naive Bayes and N-Gram Mochamad Bagoes Alfarazi; Muhammad 'Ariful Furqon; Harry Soepandi
Journal of Innovation Information Technology and Application (JINITA) Vol 6 No 2 (2024): JINITA, December 2024
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v6i2.2400

Abstract

This research aims to classify sentiment in reviews of the Universitas Jember Sister for Student application on Google Play Store, a vital student platform. The primary challenge tackled is the automated identification of positive and negative user sentiments. The study employs the Gaussian Naive Bayes method for classification and uses N-Gram techniques for sentiment analysis. The dataset consists of 1097 reviews, with 673 negative and 424 positive reviews, after removing 86 neutral spam reviews. The data is divided into 80% training data (877 reviews) and 20% test data (220 reviews). Gaussian Naive Bayes is used for modeling and combined with TF-IDF vectorization. The findings reveal that the Gaussian Naive Bayes model achieves an accuracy of 68%, precision of 68%, and recall of 71% on the test data. N-Gram analysis shows frequent occurrences of words like "bisa", "bagus", and "aplikasi" in positive sentiments, while "bisa", "hp", and "absen" are prevalent in negative sentiments. The study concludes that the Gaussian Naive Bayes model effectively classifies sentiment in application reviews, with the potential for further performance improvements.
Harmoni Multikultural: Membangun Kebersamaan di Tengah Perbedaan untuk Kaum Milenial Katarina Leba; Balthasar Watunglawar; Muhammad ‘Ariful Furqon; Dwi Wijonarko
ABDISOSHUM: Jurnal Pengabdian Masyarakat Bidang Sosial dan Humaniora Vol. 3 No. 4 (2024): Desember 2024
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/abdisoshum.v3i4.4217

Abstract

This community service activity is conducted through a religious seminar to strengthen the understanding and implementation of diversity values among young generations. The seminar is designed to respond to the increasing challenges of societal polarisation and intolerance, especially among millennials. Through a series of interactive sessions, participants are invited to explore the concept of multicultural harmony from a religious perspective, emphasizing universal values such as compassion, empathy, and mutual respect. The seminar material covers discussions on the role of religion in promoting peace, strategies to overcome inter-group prejudices and stereotypes, and best practices in building interfaith dialogue. The seminar also addresses the role of technology and social media in facilitating positive interactions between cultures and religions. It is hoped that through this activity, millennials can become active agents of change in building a harmonious and inclusive society while respecting the uniqueness of each cultural identity. Post-seminar evaluations show increased participants' understanding of the importance of togetherness in diversity and a commitment to apply the values of multicultural harmony in daily life.
Improving Software Defect Prediction Using a Combination of Ant Colony Optimization-based Feature Selection and Ensemble Technique Retnani, Windi Eka Yulia; Furqon, Muhammad 'Ariful; Setiawan, Juni
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 4, November 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i4.2038

Abstract

Software defect prediction plays a vital role in enhancing software quality and minimizing maintenance costs. This study aims to improve software defect prediction by employing a combination of Ant Colony Optimization (ACO) for feature selection and ensemble techniques, particularly Gradient Boosting. This research utilized three NASA MDP datasets: MC1, KC1, and PC2, to evaluate the performance of four machine learning algorithms: Random Forest, Support Vector Machine (SVM), Decision Tree, and Naïve Bayes. The data preprocessing comprised handling class imbalance using SMOTE and converting categorical data into numerical representations. The results indicate that the integration of ACO and Gradient Boosting significantly enhances the accuracy of all four algorithms. Notably, the Random Forest algorithm achieved the highest accuracy of 99% on the MC1 dataset. The findings suggest that combining ACO-based feature selection with ensemble techniques can effectively boost the performance of software defect prediction models, offering a robust approach for early detection of potential software defects and contributing to improved software reliability and efficiency.
Penerapan Metode Fuzzy Time Series Cheng Pada Peramalan Inflasi di Indonesia Putri, Ikfira Agustina; El Maidah, Nova; Ariful Furqon, Muhammad
Komputika : Jurnal Sistem Komputer Vol. 13 No. 2 (2024): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v13i2.12108

Abstract

Inflation is the increase in prices and goods in a certain period whose growth is always sought to remain low and stable in order to realize public welfare. High inflation fluctuations have a major influence on a country's economy, so forecasting is needed that can be used as a reference for the Government and Central Bank to prevent high inflation while maintaining price stability in the future. In addition, inflation forecasting can help economic actors in decision making. Forecasting can be done with various methods, one of which is Cheng's Fuzzy Time Series. The inflation data used in this study was obtained from the Bank Indonesia website from January 2003 to September 2023 with a monthly data period of 249 data. The prediction results for a 9-month period are 5.54% for the highest inflation and 2.92% for the lowest inflation. Based on the testing that has been done, the MAPE error value is 9.54% with a very good MAPE value category.
Segmentasi Citra Tanda Tangan Menggunakan Fitur Titik SURF (Speeded Up Robust Features) dan Klasifikasi Jaringan Syaraf Tiruan hidayat, muhamad arief; retnani, windy eka yulia; Firmansyah, Diksy Media; Santika, Gayatri Dwi; Furqon, Muhammad ‘Ariful
INFORMAL: Informatics Journal Vol 9 No 3 (2024): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v9i3.53514

Abstract

Signature image classification is an important field of image processing. One of the stages of signature classification is segmentation. The segmentation process aims to detect image pixels that are part of the signature and separate them from text or logo pixels in a document image. There is a signature segmentation technique using interest points extracted using the SURF (Speeded Up Robust Features) algorithm [1] In this technique, a connected component pixel will be considered part of the signature if it has more SURF points in common with the database connected component pixel signature. Compared to the similarity with the database connected component non-signature pixels. This method is able to provide good accuracy results for signature pixel segmentation. However, the recall value is relatively low, namely 56%. This is because many connected component logos are considered as connected component signatures. In this study, signature segmentation was carried out using SURF points by adding two things: 1) using internal connected component characteristics as additional classification atributs: extent, solidity, ratio, and circularity 2) using an Artificial Neural Network classification algorithm to assist the segmentation process. The test results show that the proposed method improves segmentation quality by an average of 20.7% for an increase in accuracy, an average of 22.4% for an increase in precision, and an average of 18.6% for an increase in recall. When compared with the results reported in (Ahmed et al., 2012), the recall has increased by 38.3% - 42.8%
Co-Authors Ahmad Sonny Pranata Alifian Sukma, Alifian Apol Pribadi Ar Ruhimat, Qurrota A'yuni Ari Cahaya Puspitaningrum Ati Kusmiati Balthasar Watunglawar Deana Nathania Damayanti Deny Hermansyah Dwi Wijonarko Eki Saputra Eki Saputra El Maidah, Nova Endah Septa Sintiya Fajariyanto, Gama Wisnu Fazrol Rozi, Fazrol Firmansyah, Diksy Media Gama Wisnu Fajarianto Gayatri Dwi Santika Gun Faisal Harry Soepandi Herman Cahyo Diartho Hidayat, Muhamad Arief Irawan, Hendry Sakti Kartika, Vera Katarina Leba Komaria, Vida Leba, Katarina Madani, Anis Mochamad Bagoes Alfarazi Mohammad Ovi Sanjaya Mohammad Zarkasi Muhammad Zuama Al Amin Najwa, Nina Fadilah Naura, Lintang Arsa Nina Najwa Nova El Maidah Nur Aini Rakhmawati Okfalisa Oktavia, Nelly Priza Pandunata Puspaningrum, Diah Putri, Ikfira Agustina Rakhmawati, Nur A retnani, windy eka yulia Rita Sari Rizqi Alvian, Muhammad Bagus Saiful Bukhori Sayekti Harits Suryawan Setiawan, Juni Suyudi, Fadil Abdillah Vega Kartika Sari Vera Kartika Windi Eka Yulia Retnani Yanuandika Akbar Yanuar Nurdiansyah, Yanuar Yanuarti, Rizky Yosari Dwi Fadhillah Yudha Alif Auliya Zarkasi, Mohamad Zarkasi, Mohammad