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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of ICT Research and Applications 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) Jurnal Teknologi Informasi dan Multimedia DedikasiMU: Journal of Community Service
Farid Sukmana, Farid
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Religion Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Social Sciences

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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.
Evaluasi Kualitas User Interface Pada Situs Website Booking System ‘Kantoor’ Menggunakan ISO/IEC 25010 Dan Metode Fuzzy Ardana, Savira Auliya; Sukmana, Farid; Bakti, Henny Dwi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 8, No 4 (2023)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v8i4.4763

Abstract

Website merupakan sebuah sistem yang dipresentasikan dalam bentuk hypertext yang dapat diakses oleh perangkat lunak yang dikenal dengan browser. Situs website yang memiliki kualitas baik dari segi perangkat lunak sangat penting dalam mempertahankan umur dan memberikan kepuasan dari segi pengalaman pengguna. Penelitian ini bertujuan untuk mengukur serta menganalisis kualitas user interface pada situs website booking system Kantoor sebagai perbaikan pengembangan sistem yang lebih baik. Oleh karena itu, dibutuhkan model evaluasi kualitas perangkat lunak yaitu dengan menggunakan ISO/IEC 25010 dengan melibatkan tiga dari delapan karakteristik diantaranya functional suitability, usability, dan reliability. Selain itu terdapat metode fuzzy yang juga digunakan sebagai metode pendukung dalam meningkatkan akurasi dalam menilai kualitas perangkat lunak. Hasil penelitian menunjukkan bahwa maturity level kategori sangat baik sebesar 92,0. Nilai error rendah sebesar 0,5% dan nilai accuracy tinggi sebesar 99,5% yang mejelaskan bahwa website booking system “Kantoor” dari sisi user interface sudah masuk dalam kategori sangat baik.
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%.
CRICKET PRODUCTION FORECASTING USING THE MOVING AVERAGE METHOD Suseno, Pangki; Junianto, Dwi; Sukmana, Farid; Pamungkas, Bian 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.v9i4.7066

Abstract

Cricket production in Indonesia has promising business potential, particularly in rural areas. However, production variability is often a major challenge for farmers to maintain economic stability. Therefore, production forecasting methods are needed for better management. This study aims to predict cricket production using Moving Average (MA) and Weighted Moving Average (WMA) methods and compare their accuracy. The research was conducted in Rejotangan District, Tulungagung, using 12 weeks of cricket production data from May to August 2024. The accuracy of the method was measured using Mean Absolute Deviation (MAD), Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). From this research, the best model that can be used to predict the amount of cricket production is the Weighted Moving Average (WMA) model with n = 4 with the lowest prediction accuracy value (MAD, MSE and MAPE) of 16.05, 514.513 and 10.985% respectively. From the forecasting results, the total production of crickets in the existing farm for one period ahead with the WMA model n = 4 is 150.9 kg.
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.
Rekomendasi Solusi pada Computer Maintenance Management System Menggunakan Association Rule, Fisher Exact Test One Side P-value dan Double One Side P-Value Sukmana, Farid; Rozi, Fahrur
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 (898.096 KB) | DOI: 10.25126/jtiik.201744368

Abstract

AbstrakPerkembangan pengambilan keputusan telah semakin cepat dan metode yang digunakan beragam. Sehingga perlu adanya pengambilan keputusan yang tidak hanya cepat tapi juga tepat. Salah satunya yaitu penerapan sistem pendukung keputusan pada Computer Maintenance Management System (CMMS). Penelitian ini melakukan uji data dengan menggunakan Association Rule, Fisher Exact One Side P-Value dan double one side p-value dalam satu permasalahan yang sama pada Computer Maintenance Management System (CMMS). Dengan tujuan mencari pola hubungan antara gejala dan akar permasalahan, untuk membuktikan adanya hubungan kedua variabel. Pada penelitian yang dilakukan sebelumnya (Sukmana, Bulaili) tentang Association Rule dan Pearson Chi-Square pada CMMS menunjukkan adanya beberapa rule yang tereliminasi karena adanya beberapa rule yang tidak masuk dalam kriteria untuk penerapan pada Chi-Square. Sehingga dalam penelitian ini bertujuan menggunakan metode Chi-Square lain dengan maksud membuktikan dan memperkuat adanya hubungan atau relasi antara gejala dan akar permasalahan dalam CMMS. Dan diharapkan pembuktian ini akan menunjukkan hasil lebih baik dalam hal hubungan antara gejala dan akar permasalahannya memiliki korelasi.Kata kunci: Association Rule, Fisher Exact TestAbstractDecision-making has been growth rapidly and many methods can used. Thus, how to apply that methode not only fast but also right. One of implementation decision making is decision support system in Computer Maintenance Management System (CMMS). This research using data test with Association Rule and Fisher Exact One Side P-Value from same problems in Computer Maintenance Management System (CMMS). Object from this research to get pattern of association between symptom and root cause, to prove relation those variable. Previous research (Sukmana, Bulaili) about Association Rule and Pearson Chi-Square in CMMS show some rule was elimanated from calculation, becaise that is rule out of way from criteria in Chi-Square. So this research has objective to use another methode to observe and get strength evidence about correlation between symptom and root cause in CMMS. And hope with this result of test can make strength hypothesis about relation between symptom and root cause.          Keywords: Association Rule, Fisher Exact Test
Co-Authors Adryan Firdaus Ardana, Savira Auliya Ayunda Kristari Bagus Firmansyah Bakti, Henny Dwi Desiyarotur Risykiyana Dwi Junianto Ervin Setyawan Ezra Amelia Fahrur Rozi Fahrur Rozi Fahrur Rozi Gading Tri Prameswari Hartono, Fabyo Aryasena Harunur Rosyid Khoirul Wafiq Mega Arisia Dewi Muhammad Iqbal Waliyuddiin Muhammad Kevin Bhaktiar Muhammad Nabil Adani Muhammad Yusril Bahtiar Muhyiddin, Sulthon Noviarani, Khurin In Pamungkas, Bian Dwi Pangki Suseno Puji Restiawan Rezal Ridlo Kurniawan Rochdianingrum, Widhi Ariestianti Rozi, Fahrur Sari, Yayak Kartika Wardatus Yudha Arya Prasaja