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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications Jurnal Inovasi dan Pembelajaran Fisika Edu Komputika Journal International Journal of Artificial Intelligence Research Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control J I M P - Jurnal Informatika Merdeka Pasuruan JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Bioedusiana: Jurnal Pendidikan Biologi EDUMATIC: Jurnal Pendidikan Informatika J-ADIMAS (Jurnal Pengabdian kepada Masyarakat) RESEARCH AND DEVELOPMENT JOURNAL OF EDUCATION (RDJE) Infotek : Jurnal Informatika dan Teknologi IJPD (International Journal Of Public Devotion) AKSIOMA : Jurnal Sains Ekonomi dan Edukasi
Rozi, Fahrur
STKIP PGRI Tulungagung
Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Social Sciences Other

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ANALISIS PEMINATAN KOMPETENSI TEKNOLOGI INFORMASI DAN KOMUNIKASI SISWA SEKOLAH MENENGAH PERTAMA Wafiq Azizah Ramadhani; Hapsari Assasanaim; Aishwanda Azizah Resanti; Sudirman Rizki Ariyanto; Fahrur Rozi
Research and Development Journal of Education Vol 9, No 2 (2023)
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/rdje.v9i2.15884

Abstract

Penelitian ini bertujuan untuk mengeksplorasi minat belajar siswa terhadap kompetensi Teknologi Informasi dan Komunikasi (TIK) di SMPN 1 Kauman Tulungagung. Minat belajar siswa menjadi faktor penting dalam mencapai keberhasilan pembelajaran, karena dapat mempengaruhi proses pemahaman dan aplikasi materi pembelajaran. Metode penelitian yang digunakan adalah deskriptif kuantitatif dengan menggunakan instrumen kuesioner sebagai alat pengumpulan data. Hasil penelitian menunjukkan bahwa mayoritas siswa di SMPN 1 Kauman memiliki minat yang tinggi terhadap mata pelajaran TIK. Faktor-faktor yang mempengaruhi minat belajar siswa meliputi cara mengajar guru, suasana kelas, dan fasilitas belajar yang memadai. Penggunaan alat peraga pengajaran dan kreativitas guru dalam penyampaian materi pelajaran juga berperan penting dalam meningkatkan minat dan motivasi siswa dalam belajar TIK. Selain itu, kesempatan untuk melanjutkan pendidikan ke jenjang yang lebih tinggi juga menjadi faktor pendorong minat belajar siswa terhadap TIK. Siswa menyadari bahwa pengetahuan tentang teknologi informasi akan memberikan peluang kerja yang lebih luas di masa depan. Fasilitas belajar yang memadai juga memberikan kontribusi positif dalam meningkatkan minat siswa terhadap mata pelajaran TIK. Berdasarkan hasil penelitian, dapat disimpulkan bahwa minat belajar siswa terhadap kompetensi TIK di SMPN 1 Kauman Tulungagung memiliki nilai yang positif. Faktor-faktor seperti cara mengajar guru, kreativitas penggunaan media pembelajaran, dan fasilitas belajar yang memadai berkontribusi dalam meningkatkan minat siswa. Pentingnya pengetahuan tentang TIK sebagai persiapan untuk masa depan, termasuk kesempatan kerja yang lebih luas, juga menjadi faktor pendorong minat siswa terhadap mata pelajaran TIK.
Aplikasi Pembelajaran Interaktif berbasis Android pada Mata Pelajaran Informatika Fahrur Rozi; Ellyfiana Nikmahtus Sholikah
Jurnal Pendidikan Informatika (EDUMATIC) Vol 7 No 2 (2023): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v7i2.14064

Abstract

The use of smartphone technology among students has not been utilized properly, because it is only used for entertainment. This is one of the factors inhibiting learning due to excessive use of smartphones so that it consumes learning time, especially in informatics subjects, so a learning media is needed in the form of an android-based interactive learning application. This study aims to develop interactive learning media and determine the feasibility level of the application. The research method used is research and development (R&D) with the R2D2 development model (Reflective, Recurcive, Design and Development) which has 3 main focuses, namely the focus of determination, the focus of determining design and development, and the focus of dissemination. The data collection methods used are interviews and distributing questionnaires which are then analyzed by calculating percentages based on the level of media feasibility which will be converted to a feasibility scale. The results of the first data analysis were carried out to media experts who got a result of 78% and entered the feasible category, the second test was carried out by material experts and got a percentage of 90% and entered the very feasible category, the third test was carried out to a small group and got a percentage of 92% and entered the very feasible category, and the last test carried out to a large group got a percentage of 92.5% with conversion to a feasible scale.
EFFICIENCY OF CMMS (COMPUTERIZED MAINTENANCE MANAGEMENT SYSTEM) PROJECT STAGES WITH K-MEANS Sukmana, Farid; Rozi, Fahrur
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 1 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i1.5453

Abstract

This study scrutinized four CMMS (Computerized Maintenance Management System) development projects using the K-Means clustering method to evaluate stages that require improvement by the GrX team. The projects under consideration were named Tim, Lix, Akb, and Mnk. The results indicated that the Tim project leaned more towards efficient CMMS development stages, while the Lix and Akb projects were predominantly in less efficient clusters at the implementation stages. The Mnk project had stages in less efficient clusters located at stages other than implementation processes. This suggests that each project has its unique challenges in achieving efficiency. However, the overarching conclusion is that the GRX team needs to enhance efficiency in the CMMS software development process. Several stages need to be evaluated, particularly the “data analysis and coordination” and “implementation of asset, work order, preventive and spare part modules” stages. Inefficiency occurs when the designing work time has a value lower than twice the workload. The K-Means algorithm was employed in the clustering process because it was believed that the data to be grouped was well-suited for implementation with this algorithm. The variables involved in this study were time and workload. This research provides valuable insights into the efficiency of CMMS development projects and offers a roadmap for future improvements.
Media Pembelajaran Sistem Periodik Unsur Berbasis Android dengan Metode Self Directed Learning Rozi, Fahrur; Romadhoni, Sugeng
Edu Komputika Journal Vol 10 No 1 (2023): Edu Komputika Journal
Publisher : Jurusan Teknik Elektro Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukomputika.v10i1.61637

Abstract

Mata pelajaran kimia sering kali dianggap sebagai salah satu mata pelajaran yang kompleks dan menantang. Konsep-konsep dalam kimia, termasuk Sistem Periodik Unsur, sering bersifat abstrak dan sulit untuk dipahami oleh beberapa siswa. Oleh karena itu, pendekatan pembelajaran yang tepat dan alat bantu yang efektif diperlukan untuk membantu siswa mengatasi kesulitan dalam memahami dan menguasai materi kimia. Media pembelajaran pada materi sistem periodik berbasis android menggunakan metode pembelajaran self directed learning merupakan salah satu solusi yang dapat dilakukan. Penelitian ini menggunakan metode Research and Development dengan model pengembangan ADDIE yaitu Analysis (analisis), Design (desain), Development (pengembangan), Implementation (implementasi) dan Evaluation (evaluasi). Media yang dikembangkan akan diuji oleh ahli media dan materi untuk menilai kelayakan media sebelum diujikan kepada siswa. Hasil menunjukkan uji kelayakan ahli media sebesar 88,23%, uji kelayakan ahli materi 96,66%, uji coba kelompok kecil 90,22%, dan uji coba kelompok besar 89,33%. Dari keempat pengujian tersebut, aplikasi media pembelajaran yang dikembangkan termasuk dalam kategori “Sangat Layak”. Jadi dapat disimpulkan bahwa media pembelajaran sistem periodik unsur berbasis Android dengan metode pembelajaran Self Directed Learning di SMA Negeri 1 Durenan sangat layak untuk menunjang kegiatan pembelajaran di SMA Negeri 1 Durenan.
THE EFFECT OF PROBLEM-BASED LEARNING MODEL IN INFORMATICS SUBJECTS ON THE CREATIVITY OF STUDENTS IN CLASS X SMK NEGERI 2 TULUNGAGUNG Hartono, Fabyo Aryasena; Rozi, Fahrur; Sukmana, Farid
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 3 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i3.6984

Abstract

This research was motivated by the low level of student creativity in the class X informatics subject at SMK Negeri 2 Tulungagung. The purpose of this research is to determine the effect of implementing the Problem Based Learning learning model on the creativity of class X students at SMK Negeri 2 Tulungagung. This type of research is a quasi-experiment with a post-test only control group design. The samples from this research were taken from 2 classes X AKL of SMK Negeri 2 Tulungagung. The experimental class is taught using a problem based learning model and the control class uses a conventional learning model, namely using the discovery learning model. The posttest score results for the experimental class had an average of 86.83 and for the control class the average posttest score was 77.69. Based on the results of the hypothesis test, a sig = 0.000 value was obtained at the significance level  = 0.05. This means that the sig value 0.05 means the sig value is outside the H0 acceptance area. So it can be concluded that there is an influence of the problem based learning model in informatics subjects on the creativity of class X students at SMK Negeri 2 Tulungagung
SENTIMENT ANALYSIS OF PUBLIC OPINION ON APPLICATION X (TWITTER) IN INDONESIA AGAINST CHATGPT USING NAÏVE BAYES ALGORITHM Sari, Yayak Kartika; Rozi, Fahrur; Muhyiddin, Sulthon; Sukmana, Farid
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.7052

Abstract

In the era of technological development and information is increasingly widespread. Data and information are easier to obtain using current technology, especially using social media such as Instagram, Facebook, (x) Twitter and others. In social media, information can be in the form of public opinions containing praise, hate speech, and hoaxes which can result in arguments against the information presented, especially on the x (twitter) application. Therefore, research was conducted on sentiment analysis of positive and negative opinions of Indonesian people on application x (twitter) about ChatGPT using the naive bayes method. Basically, Naive Bayes looks for the largest conditional probability value for each class. The technique used to explore public opinion data on application x (twitter) about ChatGPT is google collabs with the results of data mining as much as 1012 data. of these 1012 data cleaning and sentiment analysis using the naive bayes method. Naïve Bayes method classification results with a total of 762 twitter comments about ChatGPT. 100 are used as training data modeled using the naïve bayes method. The accuracy value is 99.00%, positive prediction precision is 100%, negative prediction precision is 96.43%, positive data recall is 98.63%, and negative data recall is 100%.
Implementasi K-Nearest Neighbor (K-NN) Untuk Prediksi Kebutuhan Stok Pakan Kucing Di Ngunut Petshop Ansor, Mohamad Khoirul; Rozi, Fahrur; Syamsoe, Rafif Mallow Dwi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.9192

Abstract

Persaingan bisnis yang semakin ketat menuntut setiap pengusaha untuk mampu mengambil keputusan secara cepat dan tepat berdasarkan in-formasi yang akurat. Salah satu permasalahan yang dihadapi Ngunut Petshop adalah penumpukan stok pakan kucing akibat ketidaktepatan dalam memprediksi kebutuhan konsumen. Untuk mengatasi hal terse-but, penelitian ini menerapkan metode K-Nearest Neighbor (K-NN) sebagai teknik data mining guna memprediksi kebutuhan stok pakan kucing. Data yang digunakan berasal dari catatan penjualan Ngunut Petshop pada periode bulan Maret 2024 hingga Mei 2024, dengan atribut yang meliputi jenis kucing, umur kucing, jenis makanan, dan jenis kelamin. Proses penelitian dilakukan melalui tahapan data selec-tion, preprocessing, transformation, data mining, hingga interpreta-tion/evaluasi dengan menggunakan aplikasi WEKA sebagai alat bantu analisis. Hasil pengujian menunjukkan bahwa nilai k=41 dengan pro-porsi data latih 50% dan data uji 50% memberikan akurasi tertinggi sebesar 58%. Temuan ini menunjukkan bahwa meskipun metode K-NN dapat digunakan untuk membantu prediksi kebutuhan stok pakan kuc-ing, tingkat akurasi yang diperoleh masih rendah. Oleh karena itu, diperlukan penambahan jumlah data, penggunaan atribut tambahan, maupun penerapan metode klasifikasi lain sebagai pembanding agar hasil prediksi dapat lebih optimal dan mendukung pengambilan kepu-tusan manajemen stok secara lebih efektif di Ngunut Petshop.
Unsupervised Machine Learning Using Fp-Growth in Service and Maintenance Of Asset Management Rozi, Fahrur; Sukmana, Farid
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.436

Abstract

Preventive maintenance is one of effort in manufacturer industry to maintain an infrastructure that has an important thing in the industry. One of module that was provided from this system, like service and maintenance or Work Order (WO). This module has behavior data like brain jobs in human beings. Where is the data that record in memory used to learn to get a solution in the next experienced because the data WO be saved like data in the market basket analysis. The transaction data may be repeated in the next problem. So this data is interesting to be processed to get the best solution by involved it as machine learning like the recommended solution in the brain of human beings. This research will be focused on using fp-growth association rule as unsupervised machine learning to process data as a recommended solution for the technician. A different method like previous research using apriori algorithm. This research has a goal to prove the effect of minimum support with the result of decision support in fp-growth algorithm. The study shows the best condition of the result in this method is between 0.002 until 0.004 for minimum support, because the best precision ,recall, and accuration value more than 50% in that range of minimum support.
Pelabelan Klaster Fitur Secara Otomatis pada Perbandingan Review Produk Rozi, Fahrur; Wijoyo, Satrio Hadi; Isanta, Septiyan Andika; Azhar, Yufis; Purwitasari, Diana
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 1 No 2: Oktober 2014
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (711.042 KB) | DOI: 10.25126/jtiik.201412112

Abstract

Abstrak Penggunaan review produk sebagai suatu sumber untuk mendapatkan informasi dapat dimanfaatkan untuk mengoptimalkan pemasaran suatu produk. Situs belanja online merupakan salah satu sumber yang dapat digunakan untuk pengambilan review produk. Analisa terhadap produk dapat dilakukan dengan membandingkan antara dua buah produk berbeda berdasarkan fitur produk tersebut. Fitur dari suatu produk didapatkan melalui ekstraksi fitur dengan metode double propagation. Fitur yang terdapat dalam sebuah review sangat banyak serta terdapat beberapa kata yang memiliki arti yang sama yang mewakili suatu fitur tertentu, sehingga diperlukan suatu pengelompokan terhadap fitur tersebut. Pengelompokan suatu fitur produk dapat dilakukan secara otomatis tanpa memperhatikan kamus kata, yaitu dengan menggunakan teknik clustering. Hierarchical clustering merupakan salah satu metode yang dapat digunakan untuk pengelompokan terhadap fitur produk. Pengujian dengan metode hierarchical clustering untuk pengelompokan fitur menunjukkan bahwa metode average linkage memiliki nilai recall dan f-measure yang paling tinggi. Sementara untuk pengujian pelabelan menunjukkan bahwa semantic similarity antar fitur lebih berpengaruh dari pada kemunculan fitur di dokumen. Kata kunci: clustering, fitur produk, pelabelan Abstract Product review can be used as a source for acquire information and to optimize the marketing of product. Online shopping sites are one of source that can be used to get product reviews. Analysis of the product can be done by comparing two different products based on product’s features. Features of a product can be obtained through extraction of features with double propagation method. In the product review there are many feature that can be found, and there are some words that have the same meaning which represents a particular feature, so we need a grouping on the feature. Hierarchical clustering is one method that can be used for grouping the features of the product. Based on testing, hierarchical clustering method for grouping feature indicate that the average linkage method has the highest recall and f-measure. As for testing in labeling indicates that the semantic similarity between features is more influential than the appearance of features in the document. Keywords: clustering, features of the product, labeling
Optimasi Suffix Tree Clustering dengan Wordnet dan Named Entity Recognition untuk Pengelompokan Dokumen Wijoyo, Satrio Hadi; Herlambang, Admaja Dwi; Rozi, Fahrur; Isanta, Septiyan Andika
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4 No 4: Desember 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (644.179 KB) | DOI: 10.25126/jtiik.201744400

Abstract

AbstrakSemakin meningkatnya jumlah dokumen teks di dunia digital mempengaruhi banyaknya jumlah informasi  dan menyebabkan kesulitan dalam proses temu kembali informasi (information retreival). Clustering dokumen merupakan suatu bidang text mining yang penting dan dapat digunakan untuk mengefisienkan dalam pengelolaan teks serta peringkasan teks. Namun beberapa permasalahan muncul dalam clustering dokumen teks terutama dalam dokumen berita seperti ambiguitas dalam content, overlapping cluster, dan struktur unik yang terdapat dalam dokumen berita. Penelitian ini mengusulkan metode baru yaitu optimasi Suffix Tree Clustering (STC) dengan WordNet dan Named Entity Recognition (NER) untuk pengelompokan dokumen. Metode ini memiliki beberapa tahap, yaitu prepocessing dokumen dengan mengekstraksi named entity serta melakukan deteksi sinonim berdasarkan WordNet. Tahap kedua adalah pembobotan term dengan tfidf dan nerfidf. Tahap ketiga adalah melakukan clustering dokumen dengan menggunakan Suffix Tree Clustering. Berdasarkan pengujian didapatkan rata-rata nilai precision sebesar 79.83%, recall 77.25%, dan f-measure78.30 %.Kata kunci: Clustering dokumen, Named Entity Recognition, Suffix Tree Clustering, WordNetAbstractThe increasingnumber oftext documentsin the internet, influence on the number of information and lead to difficulties in the process of information retrieval. Documents clustering is main field of text mining and can be used to stream line the management of text and summarization of text. However, some problems a risein documents clustering, especially in news documents such as ambiguity in the content, overlapping clusters, and theuniquestructure ofthe news thatcontained inthe document. Inthisresearch, we proposea newmethodfor documents clustering, optimization Suffix Tree Clustering (STC) with WordNet and Named Entity Recognition (NER). In this method there are several step, step one is prepocessing documents with named entity extraction and synonym detection based on WordNet. Step two is term weighting with tfidf and nerfidf. For the last step is document clustering using Suffix Tree Clustering. Based on testingwe obtained 79.83% for precision, 77.25% for recall, and78.30% for F-measureKeywords: Documents Clustering, Named Entity Recognition, Suffix Tree Clustering, WordNet
Co-Authors Admaja Dwi Herlambang, Admaja Dwi Aishwanda Azizah Resanti Anggara Sukma Ardiyanta Ansor, Mohamad Khoirul Arganis Ratna Furi Ariyanto, Sudirman Rizki Ayunda Kristari Chastine Fatichah Diana Purwitasari Ellyfiana Nikmahtus Sholikah Ema Mahayati Farid Sukmana, Farid Frans Ahkilal Firmansyah Hapsari Assasanaim Hartono, Fabyo Aryasena Hasyim, Yusuf Istiqomah, Nur Dwi Kamalin, Azza Niela Khalimatul Khomsatun Khasanah, Ana Meilyani Khusnatul Khasby Khoirul Atok Khomsatun, Khalimatul Kristari, Ayunda Malika, Himatul Askin Moch Iklil Putra Irgian Muhammad Nabil Adani Muhyiddin, Sulthon Muna, Fika Nailul Muslimah, Ammana Baiti Nurhadi Puji Restiawan Ramadhani, Wafiq Azizah Rezal Ridlo Kurniawan Rikie Kartadie Romadhoni, Sugeng Sari, Feni Windiyan Sari, Yayak Kartika Satrio Hadi Wijoyo Septiyan Andika Isanta Setyo Hartanto Sukardi Sukardi Sukardi Sukardi Sukardi Supriono, Nanang Syamsoe, Rafif Mallow Dwi Tomi Listiawan Vertika Penggayuh Wafiq Azizah Ramadhani Yandria Elmasari Yufis Azhar Yusuf Hasyim Zulfa, Ella Dwiyanti