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All Journal International Journal of Electrical and Computer Engineering MATEMATIKA SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Jurnal Matematika Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Mahasiswa Pasca Sarjana Proceeding SENDI_U Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science (JOINTECS) Jurnal Matematika: MANTIK Jurnal Penelitian Pendidikan IPA (JPPIPA) Indonesian Journal of Artificial Intelligence and Data Mining BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) JURNAL INSTEK (Informatika Sains dan Teknologi) Gema Wiralodra Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Jurnal Teknik Informatika (JUTIF) Journal of Soft Computing Exploration International Journal of Social Service and Research Interdisciplinary Social Studies Jurnal Sosial dan Sains
Juwanda, Farikhin
Departemen Matematika FSM UNDIP
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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PERBANDINGAN METODE TRUST-REGION DENGAN METODE NEWTON-RAPHSON PADA OPTIMASI FUNGSI NON LINIER TANPA KENDALA Yully Estiningsih; farikhin farikhin
Jurnal Matematika Vol 3, No 4 (2014): JURNAL MATEMATIKA
Publisher : MATEMATIKA FSM, UNDIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.026 KB)

Abstract

Optimization is the best decision of  the objective functions for  produce a satisfactory solution. Optimization of multi variables unconstraints is to optimize the the objective functions which contains multi variable function freely without any specific requirements that restrict its function. Trust-Region methods methods is used to optimize multi variables unconstraint , Trust-Region methods quadratic approach of optimizing non linear the objective functions with a certain radius as the limit of the step size according to the quality of the approach. Newton-Raphson methods is a root search method with the the objective functions approaches a point, where the objective functions has a derivative. In this final will be talking about Trust-Region methods will compared with Newton-Raphson methods, and rendered example problem in which only be solved using Trust-Region methods.Keywords : Trust-Region Methods, Optimization, Newton-Raphson Methods 
SUATU KAJIAN PADA BCI-ALJABAR YANG TERKAIT DENGAN SIFAT DERIVASI KIRI Carolin Carolin; farikhin farikhin
Jurnal Matematika Vol 3, No 4 (2014): JURNAL MATEMATIKA
Publisher : MATEMATIKA FSM, UNDIP

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (342.165 KB)

Abstract

Setiap-Derivasi kiri pada BCI- Aljabar X dapat dikatakan regular jika hasil derivasinya sama dengan nol atau setiap X idealnya merupakan D-invarian. Suatu himpunan dikatakan ideal pada X dengan -ideal jika , hal serupa dengan (-ideal jika ). Selain itu, himpunan  dikatakan ideal pada X dengan D-invarian jika. - Derivasi kiri BCI- Aljabar positif semisederhana merupakan hasil operasi biner antara endomorfisma dengan derivasinya. Himpunan  dikatakan torsi bebas BCI-aljabar jika kuadrat derivasinya atau komposisi derivasi pertama dan derivasi kedua sama dengan nol.Kata kunci :BCI-aljabar, BCI-aljabar p-semi sederhana, -Derivasi kiri,        D-invarian
ANALISIS KONSISTENSI MATRIKS KEPUTUSAN : SUATU PERBANDINGAN NUMERIK Farikhin Farikhin
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 9 No 1 (2017): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2017.9.1.2850

Abstract

In this paper, we study some algorithms to improve consistency of resiprocal pairwise matrix. The algorithm is proposed by using relationship with multiplicative preference relation and fuzzy preference relation. An example is presented to evaluate these algorithms.
Pengayaan Yodium dan Kadar NaCl pada Garam Krosok menjadi Garam Konsumsi standar SNI Enrichment of Iodium and Sodium Cloride in the Traditional Salt become Consumtion Salt INS Standard M. Nur; I. Marhaendrajaya; Sugito Sugito; T. Windarti; Arnelli Arnelli; R. Hastuti; A. Haris; W. H. Rahmanto; Didik Setiyo Widodo; F. Ariyanto; Z. Muhlisin; J. E. Suseno; E. Setiawati; H. Sutanto; Priyono Priyono; M. Izzati; R. Hariyati; S. Tana; B. Raharjo; D. Ispriyanti; Farikhin Farikhin; A. Rusgiyono; Suhartono Suhartono
JURNAL SAINS DAN MATEMATIKA Volume 21 Issue 1 Year 2013
Publisher : JURNAL SAINS DAN MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3994.464 KB)

Abstract

This research has been carried out in the quality improvement of traditional salt (krosok salt) into salt consumption for the Indonesian National Standard. This report is devoted to the elevated levels of NaCl and KIO3. Increased levels of NaCl and Iodine (represented by KIO3) is done by washing the salt with the traditional clothes washer with two rounds and by using water with saline solution at 22-24 Be (known as the old water). Traditional salt taken from three districts, such as Pati District, Jepara District, and Rembang District. We found that the concentration of NaCl in the treatment salt maximum is  96 % and Iodium or present of KIO3 is 40 ppm.   Key words: Salt,  traditional, INS, Consumtion, NaCl, KIO3
Application of The Naïve Bayes Classifier Algorithm to Classify Community Complaints Keszya Wabang; Oky Dwi Nurhayati; Farikhin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 5 (2022): Oktober 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i5.4498

Abstract

Unsatisfactory public services encourage the public to submit complaints/ reports to public service providers to improve their services. However, each complaint/ report submitted varies. Therefore, the first step of the community complaint resolution process is to classify every incoming community complaint. The Ombudsman of The Republic of Indonesia annually receives a minimum of 10,000 complaints with an average of 300-500 reports per province per year, classifies complaints/ community reports to divide them into three classes, namely simple reports, medium reports, and heavy reports. The classification process is carried out using a weight assessment of each complaint/ report using 5 (five) attributes. It becomes a big job if done manually. This impacts the inefficiency of the performance time of complaint management officers. As an alternative solution, in this study, a machine learning method with the Naïve Bayes Classifier algorithm was applied to facilitate the process of automatically classifying complaints/ community reports to be more effective and efficient. The results showed that the classification of complaints/ community reports by applying the Naïve Bayes Classifier algorithm gives a high accuracy value of 92%. In addition, the average precision, recall, and f1-score values, respectively, are 91%, 93%, and 92%.
Prediction of Indonesia School Enrollment Rate by Using Adaptive Neuro Fuzzy Inference System Bibit Waluyo Aji; Neza Zhevira Septiani; Wyne Mumtaazah Putri; Bambang Irawanto; Bayu Surarso; Farikhin Farikhin; Yosza Dasril
Indonesian Journal of Artificial Intelligence and Data Mining Vol 6, No 1 (2023): Maret 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v6i1.21839

Abstract

The study aimed to predict the school enrollment rate in Indonesia using the Adaptive Neuro Fuzzy Inference System (ANFIS). ANFIS is a combination of fuzzy inference system and artificial neural networks. The study used the Gaussian and Gbell membership functions to make the predictions. The results were evaluated using the R square score (coefficient of determination) and Mean Square Error methods. The results showed that the model performed well in predicting the school enrollment rate, particularly in the age categories of 7-12 years and 13-15 years. The R square score for these categories was 0.981551771 and 0.989081085, respectively, while the Mean Square Error was 0.023947290 and 0.3675162695238, respectively. The performance of the model in the age categories of 16-18 years and 19-24 years was also good, but with a slightly lower R square score and Mean Square Error compared to the younger age categories. When using the Gaussian membership function, the model performed even better, particularly in the age categories of 13-15 years and 19-24 years. The R square score for these categories was 0.99020792 and 0.9883091, respectively, while the Mean Square Error was 0.32958834 and 0.31523466571, respectively. Overall, the study demonstrated that ANFIS is a suitable method for predicting school enrollment rate in Indonesia. The results from this study can provide useful information for decision makers in the education sector, who can use the model to make informed decisions about future educational policies and programs.
Sentimen Analisis Aplikasi Belajar Online Menggunakan Klasifikasi SVM Adi Ariyo Munandar; Farikhin Farikhin; Catur Edi Widodo
JOINTECS (Journal of Information Technology and Computer Science) Vol 8, No 2 (2023)
Publisher : Universitas Widyagama Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/jointecs.v8i2.4747

Abstract

Google Play Store adalah tempat berbagai macam aplikasi tersedia, baik berbayar ataupun tidak. Halaman Google Play Store menjadi tempat pengguna aplikasi untuk menyampaikan pendapat, ulasan dan penilaian. Ruang Guru, Zenius dan Quipper tersedia di platform tersebut. Data pada ulasan, menjadi sangat bermanfaat untuk dianalisa. Analisa dilakukan dengan menggunakan sentimen analisis dan algoritma SVM. Data diperoleh dengan menggunakan teknik scraping data, dengan menggunakan bantuan library google-play-scraper. Proses web Scraping, dibagi menjadi 3 tahap yaitu Fetching, Extraction, dan Transformation. Data dikumpulkan sebanyak 30.000 data, yang dibagi menjadi 10.000 data Ruang Guru, Zenius dan Quipper. Peneltian diawali dengan Tahap preprocesing data meliputi normalisasi, case folding, cleaning, tokenizing, dan  Stopword. kemudian data dibagi menjadi 90% data latih dan 10% data uji. Data latih diberi label dengan nilai 1, 0, dan -1. Nilai 1 berarti positif, nilai 0 berarti netral dan -1 berarti negatif. Hasil sentimen klasifikasi menggunakan SVM, menunjukkan bahwa Ruang Guru memiliki nilai positif tertinggi dibandingkan Zenius dan Quipper. Akan tetapi, respon pengguna sama-sama memberikan nilai positif untuk aplikasi tersebut. Nilai akurasi dari penelitian menunjukkan bahwa, data Klasifikasi sentimen dengan SVM, mempunyai akurasi rata-rata untuk Ruang Guru sebesar 99%, Zenius sebesar 96%, dan Quipper sebesar 82%.
Analisis Sentimen Berbasis Aspek Ulasan Pelanggan Restoran Menggunakan LSTM Dengan Adam Optimizer Wardianto Wardianto; Farikhin Farikhin; Dinar Mutiara Kusumo Nugraheni
JOINTECS (Journal of Information Technology and Computer Science) Vol 8, No 2 (2023)
Publisher : Universitas Widyagama Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31328/jointecs.v8i2.4737

Abstract

Consumers believe that restaurant reviews are very important when choosing a restaurant. Due to the fact that reviews have become one of the most effective ways to influence customer decisions, research that has been done on restaurant customer reviews is about sentiment analysis. Previous studies have only used sentiment analysis at the sentence or document level, while a better level uses Aspect-Based Sentiment Analysis (ABSA), or a type of aspect-based sentiment analysis. LSTM is a variant of RNN that stores long-term information in memory cells. Use of global max pooling to reduce output resolution features and prevent overfitting. In addition, the optimization method used by Adam Optimizer is an adaptive learning rate optimization algorithm specifically designed to train deep neural networks. This study aims to classify restaurant customer opinions based on aspects (food, place, service, and price) based on restaurant customer reviews on Indonesian-language TripAdvisor with LSTM and global max pooling for sentiment classification (negative, half negative, neutral, half positive, positive). The results of this study indicate that the ABSA in restaurant customer reviews for sentiment classification accuracy is 78.7% and the aspect category accuracy is 78%, both are interconnected and can help understand restaurant customer opinions on TripAdvisor.
ANALISIS KONSISTENSI MATRIKS KEPUTUSAN : SUATU PERBANDINGAN NUMERIK Farikhin Farikhin
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 9 No 1 (2017): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2017.9.1.2850

Abstract

In this paper, we study some algorithms to improve consistency of resiprocal pairwise matrix. The algorithm is proposed by using relationship with multiplicative preference relation and fuzzy preference relation. An example is presented to evaluate these algorithms.
Acceptance and Success of Oss Rba (Online Single Submission Risk Based Approach) Information System Using the Utaut Ii and Delone & Mclean Models Prantiastio; Farikhin; Rinta Kridalukmana
Jurnal Penelitian Pendidikan IPA Vol 9 No 11 (2023): November
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v9i11.5958

Abstract

This research, conducted in South Sumatra Province, employs the Unified Theory of Acceptance and Use of Technology II (UTAUT II) and the DeLone & McLean Model to assess user satisfaction and system success in the OSS RBA implementation. This study utilized PLS-SEM software to model the research, employing a quantitative approach through Likert-scale questionnaires. The research focused on business actors in South Sumatra who registered their permits on the OSS RBA platform, where 41.129 businesses completed registration in 2022. Adhering to sampling criteria, the sample size was set at 250 samples to ensure credibility, balancing the number of parameters and indicators for latent variables, as 25 indicators were present. This research findings reveal that Performance Expectancy, Price Value, System Quality, and Service Quality significantly influence User Satisfaction, subsequently User Satisfaction significantly influence Net Benefit. Conversely, Effort Expectancy, Social Influence, and Information Quality do not significantly affect User Satisfaction. These insights provide a comprehensive understanding of the evolving business licensing landscape in South Sumatera Province
Co-Authors A. Haris A. Rusgiyono Acep Irham Gufroni Adi Ariyo Munandar Adi Suliantoro Ahmad Abdul Chamid Ahmad Lubis Ghozali Aprilia, Maita Aris Sugiharto Arnelli Arnelli B. Raharjo Bambang Irawanto Bambang Irawanto Bambang Subeno Bayu Surarso Bayu Surarso Beta Noranita Bibit Waluyo Aji Budi Warsito Carolin Carolin Catur Edi Widodo D. Ispriyanti Didik Setiyo Widodo Dinar Mutiara Kusumo Nugraheni Djuwandi Djuwandi DONNY IRAWAN MUSTABA Dwinta Rahmallah Pulukadang, Dwinta Rahmallah E. Setiawati Erikha Feriyanto Erlin Dwi Endarwati, Erlin Dwi Esti Wijayanti, Esti F. Ariyanto Faozi, Safik Fauzi, Irza Nur Feriyanto, Erikha Ferry Jie, Ferry Fitika Andraini H. Sutanto Heny Maslahah, Heny I. Marhaendrajaya Iswahyudi Joko Suprayitno J. E. Suseno Kartono . Keszya Wabang Kusworo Kusworo Laily Rahmania, Laily LM Fajar Israwan, LM Fajar M. Izzati M. Nur Madani, Faiq Mansur Mansur Meryta Febrilian Fatimah, Meryta Febrilian Mustafid Mustafid Neza Zhevira Septiani Nikken Prima Puspita Nikken Prima Puspita Nur Khasanah Oky Dwi Nurhayati Pangestika, Vidya Dwi Pradana, Fadli Dony Prantiastio Prastio, Wahyu Tedi Priyono Priyono Purwanto Purwanto R. Hariyati R. Hastuti Rachmat Gernowo Ratri Wulandari Retno Kusumaningrum Rezki Kurniati, Rezki Rinta Kridalukmana Robertus Heri Sulistyo Utomo S. Tana Safik Faozi, Safik Satriani, Rineka Brylian Akbar Siti Khabibah Siti Khabibah Sri Wahyuni Sugito Sugito Suhartono Suhartono Sunarsih . Suparti Suparti T. Windarti Titi Udjiani SRRM Toni Prahasto Udjiani , Titi Udjiani S.R.R.M, Titi Usman, Carissa Devina Uswatun Khasanah W. H. Rahmanto Wardani, Novita Koes Wardianto, Wardianto Warsito , Budi Wicaksono, Mahad Wyne Mumtaazah Putri Yosza Dasril Yully Estiningsih Z. Muhlisin