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All Journal REKAYASA JOIN (Jurnal Online Informatika) SENTIA 2017 SENTIA 2016 Jurnal Informatika dan Rekayasa Elektronik Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) GUYUB: Journal of Community Engagement TRILOGI: Jurnal Ilmu Teknologi, Kesehatan, dan Humaniora Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Nusantara Journal of Computers and its Applications Proceeding Of International Conference On Education, Society And Humanity
Fadli Hidayat, M. Noer
Universitas Nurul Jadid
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Physics Public Health Social Sciences Other

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Comparison of C4.5 and Naive Bayes for Predicting Student Graduation Using Machine Learning Algorithms Abu Tholib; M Noer Fadli Hidayat; Supri yono; Resty Wulanningrum; Erna Daniati
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3364

Abstract

Student graduation is a very important element for universities because it relates to college accreditation assessment. One of them is at the Faculty of Engineering Nurul Jadid University, which has problems completing the study period within a predetermined time. So that it can be detrimental because accreditation is less than optimal, and the number of active students makes it less ideal in teaching and learning activities. This study aimed to compare the level of accuracy using the C4.5 algorithm and Naïve Bayes method in predicting graduation on time. The C4.5 and Naïve Bayes algorithms are one of the methods in the algorithm for classifying. Tests were carried out using the C4.5 and Naïve Bayes algorithms using Google Colab with Python programming language, then validated using 10-fold cross-validation. The results of this study indicate that the Naïve Bayes method has a higher accuracy value with an accuracy rate of 96.12%, while the C4.5 algorithm method is 93.82%.
KLASIFIKASI BUAH ALPUKAT BERDASARKAN TEKSTUR BUAH MENGGUNAKAN METODE BACKPROPAGATION BERBASIS IMAGE PROCESSING M. Noer Fadli Hidayat
Jurnal Informatika dan Rekayasa Elektronik Vol. 6 No. 2 (2023): Jire Nopember 2023
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v6i2.725

Abstract

Proses klasifikasi buah alpukat biasa dilakukan dengan cara manual yang sederhana yaitu dengan pemilihan alpukat berdasarkan ciri-ciri umum. Hasilnya banyak terjadi kesalahan klasifikasi karena perbedaan pendapat dari tiap orang. Cara yang dapat dilakukan guna mengatasi kesalahan tersebut yaitu menggunakan citra digital dengan metode backpropagation. Metode backpropagation ini dapat mengklasifikasikan buah alpukat berdasarkan jenisnya dengan mengenali karakteristik buahnya seperti tekstur dan bentuk buahnya. Di dalam proses klasifikasi dengan metode backpropagation ini terdapat proses image processing yaitu pemrosesan gambar 2 dimensi menggunakan komputer. Setelah dilakukan tahapan image processing dilakukan ekstraksi fitur tekstur menggunakan asm, kontras, idm, entropi dan korelasi, dev, skewness dan cur. Data training yang dipakai sebanyak 60 data dan data testing sebanyak 40 data. Hasil pengujian klasifikasi buah alpukat berdasarkan tekstur buah diperoleh akurasi keberhasilan sebesar 85% dan maksimal kegagalan 15% dari 30 kali pengujian.
Analisis Sentimen Hasil Pemilu (Quick Count) Calon Presiden dan Wakil Presiden 2024 di Media Sosial Media X Menggunakan Metode Bidirectional Long Short-Term Memory (BiLSTM) Qurrotu Aini; M. Noer Fadli Hidayat; Abu Tholib
Journal of Computer System and Informatics (JoSYC) Vol 5 No 3 (2024): May 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i3.5223

Abstract

It is important to understand public opinions, attitudes and sentiments in relation to presidential and vice presidential candidates in the context of Indonesia's general elections. The fact that quick count results have become a major topic of conversation on social media, especially on platforms such as Twitter, shows how important it is to monitor people's views on election results. However, tweets that are free-form and use digital language are often difficult for the unfamiliar to understand, which can lead to the spread of misinformation or inaccurate views. Sentiment analysis is therefore key in understanding people's views on election results. This research proposes the use of the Bidirectional Long Short Term-Memory (BiLSTM) method to analyse sentiment related to the quick count results of the 2024 presidential and vice presidential elections on X social media. This sentiment analysis aims to classify texts into positive, negative, or neutral categories. The purpose of this study is to measure the sentiment value and accuracy of the BiLSTM method in sentiment analysis of election results. Data was collected by scraping X social media using the keywords "quick count results of 2024 presidential election" and "results of 2024 presidential election", resulting in 1348 tweets. Preprocessing included cleaning, case folding, normalisation, tokenisation, stopword removal, and stemming. Sentiments were labelled using the Vader lexicon dictionary. BiLSTM modelling was performed by dividing the data into 70% for training and 30% for testing. The results showed that neutral sentiment had the highest percentage at 92.86%, followed by positive sentiment at 3.83% and negative at 3.31%. The BiLSTM model achieved an accuracy of 86.89% with an overall accuracy of 97%. The highest precision, recall, and F1-score values were found in the neutral class, at 98%, 99%, and 99% respectively. This research proves that BiLSTM is an effective method for sentiment analysis of complex texts such as election results.
FAKTORISASI MATRIKS MENGGUNAKAN STOCHASTIC GRADIENT DESCENT UNTUK OPTIMASI SISTEM REKOMENDASI HOTEL abu tholib; Inayatul Maula; M. Noer Hidayat
NJCA (Nusantara Journal of Computers and Its Applications) Vol 9, No 1 (2024): June 2024
Publisher : Computer Society of Nahdlatul Ulama (CSNU) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36564/njca.v9i1.367

Abstract

In today's digital world, recommendation systems have a very important role to help users find hotels that match their preferences. This research focuses on developing a hotel recommendation system by combining matrix factorization method with Stochastic Gradient Descent (SGD) algorithm. The matrix factorization method is used to model the hotel ranking data as the product of the user matrix and the hotel matrix. While for the Stochastic Gradient Descent (SGD) algorithm plays a role in optimizing model parameters efficiently, where the method will be tested on hotel rating datasets or ratings. Evaluation of model performance in this study, using metrics such as Root Mean Squared (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE). This study shows fairly accurate results, with an RMSE value of 0.370312, an MSE value of 0.137131, and an MAE value of 0.089932. These results show that combining the matrix factorization method with Stochastic Gradient Descent (SGD) can be an effective solution for building a hotel recommendation system according to user preferences
Pendampingan Analisis Sistem Pemerintahan Daerah Kabupaten Probolinggo Berbasis Elektronik (SPBE) Hidayat, M Noer Fadli
GUYUB: Journal of Community Engagement Vol 5, No 1 (2024)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/guyub.v5i1.6701

Abstract

The Indonesian government is focusing on the development of information and communication technology as a means to improve public services to the community. This is reflected in the issuance of the Electronic-Based Government System (EBS) guidelines. The Probolinggo District Government also implements good governance to improve the welfare of the community. In 2022, Probolinggo Regency has carried out an SPBE evaluation which resulted in an SPBE index value of 2.42 and received a Fair predicate. This Community Service (PkM) aims to analyze the aspects that have the lowest contribution to the evaluation of SPBE of the Probolinggo Regency Government. Several aspects of the SPBE assessment are presented as having the lowest contribution value which results in a lack of SPBE index value for the Probolinggo Regency Government. The aspect with the lowest contribution is located in the SPBE Governance domain, namely the SPBE Organizer aspect and is located in the SPBE Management domain, namely the SPBE Management Implementation aspect and the ICT Audit aspect. Each aspect has its own weaknesses as a measure of the low value obtained. Recommendations for improvement to increase the evaluation value in each aspect in the hope of building quality work in the Probolinggo Regency Government that is effective, efficient, and productive as well as harmonizing the SPBE architecture and SPBE plan map from the central government
PKM Pengembangan Desa Ekonomi Digital melalui Pendampingan Badan Usaha Milik Desa (BUMDES) dalam Sertifikasi, Komersialisasi, dan Digitalisasi Produk Lokal Desa Clarak Kabupaten Probolinggo Hidayat, M Noer Fadli; Febrianto, Achmad; Mundir, Abdillah; Akil, Ahmad Ibnu; Nisa', Chairun; Amelia, Lina; Yanuar, Rizqi Alif; Nabila, Uyun
GUYUB: Journal of Community Engagement Vol 4, No 3 (2023)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/guyub.v4i3.6850

Abstract

Program Kemitraan Masyarakat ini dilatarbelakangi oleh masyarakat Desa Clarak yang belum mampu meningkatkan potensi desanya secara maksimal, sementara desa ini memiliki potensi besar menjadi desa mandiri ekonomi digital. Secara geografis, pembangunan jalan tol Probolinggo-Banyuwangi (Probowangi) menjadikan Desa Clarak sebagai desa yang strategis dalam pengembangan UMKM karena berbatasan langsung dengan jalur jalan tol. Tujuan dari PKM ini adalah menghubungkan produk/usaha lokal masyarakat dengan UMKM dengan memberikan pendampingan layanan merek dagang, pemasaran digital (e-commerce), dan sertifikasi produk halal. Hasil dari PKM ini adalah terdaftarnya merek dagang Café Nyantol sebagai bisnis lokal binaan Clarak, terdaftarnya hak cipta salah satu motif batik pelaku usaha lokal Clarak, terbentuknya e-commerce Clarak Store, terdaftarnya salah satu produk es krim ke Komisi Fatwa MUI, serta beberapa produk usaha lainnya. Outcome yang diharapkan dari PKM ini adalah terbentuknya kesadaran dan pengetahuan pelaku usaha lokal, UMKM, dan BUMDES Desa Clarak untuk mendigitalisasi seluruh produknya hingga terbentuk Clarak sebagai Desa Ekonomi Digital. 
ANALISIS SENTIMEN ULASAN APLIKASI PEMBELAJARAN DUOLINGGO DI PLAY STORE MENGGUNAKAN DISTILBERT Syindy Mauliddiyah; M.Noer Fadli Hidayat; Fathur Rizal
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1395

Abstract

Learning media innovation is currently required to keep up with the development of science and technology. Duolingo is a free language learning application. Duolinggo has been downloaded more than 500 million times and recorded more than 21 reviews in the comments column consisting of positive and negative comments. Duolinggo user reviews are classified into two sentiments, namely positive sentiment and negative sentiment. Sentiment analysis is an activity used to analyze a person's opinion or opinion on a topic, to support the classification, the algorithm used is DistilBERT. DistilBERT is a technique of how to make the BERT model smaller, but has similar qualities to a large model, distilBERT can be termed as 2 running models, namely the teacher model and the student model, the teacher model is a large model and is trained with a complete range of features such as the base (pre-trained model) The results of the DistilBERT algorithm for classifying 1000 reviews of the Duolingo learning application produce precision, recall, f1-score values on class 1 labels are 74%, 96%, and 84%, indicating that this BERT algorithm is very good at predicting label classes. With the accuracy result obtained is 80% in 85 seconds.
Comparison of C4.5 and Naive Bayes for Predicting Student Graduation Using Machine Learning Algorithms Abu Tholib; M Noer Fadli Hidayat; Supri yono; Resty Wulanningrum; Erna Daniati
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 2 No. 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3364

Abstract

Student graduation is a very important element for universities because it relates to college accreditation assessment. One of them is at the Faculty of Engineering Nurul Jadid University, which has problems completing the study period within a predetermined time. So that it can be detrimental because accreditation is less than optimal, and the number of active students makes it less ideal in teaching and learning activities. This study aimed to compare the level of accuracy using the C4.5 algorithm and Naïve Bayes method in predicting graduation on time. The C4.5 and Naïve Bayes algorithms are one of the methods in the algorithm for classifying. Tests were carried out using the C4.5 and Naïve Bayes algorithms using Google Colab with Python programming language, then validated using 10-fold cross-validation. The results of this study indicate that the Naïve Bayes method has a higher accuracy value with an accuracy rate of 96.12%, while the C4.5 algorithm method is 93.82%.
Anatomy of Sentiment Analysis in Ontological, Epistemological, and Axiological Perspectives Fadli Hidayat, M. Noer; Dwi Prasetya, Didik; Widiyaningtyas, Triyanna; Patmanthara, Syaad
JOIN (Jurnal Online Informatika) Vol 10 No 1 (2025)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v10i1.1228

Abstract

The aim of this article was to examine sentiment analysis methods from the perspective of the philosophy of science with three approaches, ontological, epistemological and axiological. This research used a qualitative research method (descriptive-analysis) with an ontological, epistemological and axiological approach that uses library research and document studies of previous research results. Data collection was carried out through books and reputable scientific journals on Scopus, ScienceDirect, IEEEXplore and Springer Link. The results of this research showed that sentiment analysis from an ontological perspective describes the definition, development and relationship of sentiment with social reality. Meanwhile, from an epistemological perspective, sentiment analysis is viewed from how the source of knowledge is obtained, explaining the production of sentiment analysis knowledge, and several ways of working that can be applied in studies. Axiologically, sentiment analysis can see the function and value resulting from sentiment analysis, as well as discussing the results of interpretation from sentiment analysis studies. These findings showed the development of sentiment analysis in answering various problems to improve the quality of sustainable services in various fields.
Sistem Informasi Manajemen Stok Mengimplementasikan Metode Min-Max Pada Toko Grosir Amanah Jose, Anthonio Fernando; Sucipto, Sucipto; Muzaki, M.Najibulloh; Hidayat, M. Noer Fadli
JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Vol. 3 No. 2 (2025): Juni 2025
Publisher : Cipta Media Harmoni

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53624/jsitik.v3i2.563

Abstract

Latar Belakang: Toko Grosir Amanah sering mengalami kekurangan dan kelebihan stok barang, yang menyebabkan ketidakefisienan dalam pembiayaan dan pengelolaan stok. Saat ini, sistem manajemen stok masih dilakukan secara manual, yang meningkatkan risiko kesalahan dalam pencatatan dan pengambilan keputusan. Tujuan: Penelitian ini bertujuan untuk mengembangkan sistem manajemen stok berbasis metode min-max guna menghindari terjadinya kelebihan maupun kekurangan stok di gudang. Metode: Penelitian ini menggunakan pendekatan analisis deskriptif dengan pengumpulan data lapangan secara langsung melalui observasi dan wawancara. Data yang diperoleh dianalisis untuk merancang sistem manajemen stok yang lebih efektif dan efisien menggunakan metode min-max. Hasil: Penerapan metode min-max dalam pengelolaan stok di Toko Grosir Amanah menunjukkan peningkatan efisiensi dalam pengendalian persediaan. Sistem ini mampu memberikan batas minimal dan maksimal stok yang harus tersedia, sehingga meminimalkan risiko kelebihan stok dan menghindari kekurangan barang. Kesimpulan: Sistem manajemen stok berbasis metode min-max terbukti efektif dalam mengatasi masalah kelebihan dan kekurangan stok di Toko Grosir Amanah. Dengan penerapan sistem ini, proses pengendalian stok menjadi lebih sistematis dan efisien. Penelitian selanjutnya dapat diarahkan pada pengembangan sistem berbasis digital atau otomatisasi agar pengelolaan stok semakin optimal.
Co-Authors Abdillah Mundir Abu Tholib Achmad Febrianto Ahmad Fawaid Akil, Ahmad Ibnu Anando Setyo Adiwirawan Didik Dwi Prasetya Dwiki Qutsi Ali Multazam Erna Daniati Fathorazi Nur Fajri Fathur Rizal Fauzan Abdul Latif Inayatul Maula Indah Sri Mulyati Jose, Anthonio Fernando Kamil Malik Lailatul Qomariyah, Lailatul Misbahul Munir Moh. Furqan Mohammad Alfian Faisol Mustaqim Muhammad Najibulloh Muzaki Nabila, Uyun Nisa', Chairun Qurrotu Aini Rahman, Handono Fatkhur Resty Wulanningrum Siti Helmyati Soleh, Paisal Suci Rahayu Agustini Sucipto Sucipto Supri yono Syaad Patmanthara Syindy Mauliddiyah Triyanna Widiyaningtyas Wahab Sya’roni Yanuar, Rizqi Alif