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All Journal Dinamik GEMA TEKNOLOGI Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Syntax Jurnal Informatika Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Mahasiswa FEB Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Berkala Epidemiologi Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri InComTech: Jurnal Telekomunikasi dan Komputer Prosiding Seminar Nasional Teknoka JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jiko (Jurnal Informatika dan komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Telematika STRING (Satuan Tulisan Riset dan Inovasi Teknologi) CCIT (Creative Communication and Innovative Technology) Journal Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Ilmu Komputer dan Bisnis Syntax Idea Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Mnemonic Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Journal of Computer Science and Engineering (JCSE) SKANIKA: Sistem Komputer dan Teknik Informatika Media Gizi Kesmas Jurnal Teknik Informatika (JUTIF) Jurnal Pewarta Indonesia JURNAL KOMUNIKASI DAN BISNIS Ascarya: Journal of Islamic Science, Culture and Social Studies Jurnal PkM (Pengabdian kepada Masyarakat) Humantech : Jurnal Ilmiah Multidisiplin Indonesia Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Journal Of Human And Education (JAHE) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Algoritma Jurnal Ticom: Technology of Information and Communication Berita Kedokteran Masyarakat Journal of Systems Engineering and Information Technology J-Icon : Jurnal Komputer dan Informatika Jurnal Teknik Indonesia Research Horizon Jurnal Relawan dan Pengabdian Masyarakat REDI Jurnal Pengabdian Masyarakat Nasional Health Dynamics Jurnal Ticom: Technology of Information and Communication The Indonesian Journal of Computer Science Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Prosiding SeNTIK STI&K Journal of Medical and Health Science Jurnal Ilmu Kesehatan Immanuel Jurnal Analogi Hukum
Arief Wibowo
Universitas Budi Luhur
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SURVEI METODE PENGUKURAN APLIKASI CHATBOT BERBASIS MEDIA SOSIAL Ratna Ayu Sekarwati; Ahmad Sururi; Rakhmat Rakhmat; Miftahul Arifin; Arief Wibowo
Gema Teknologi Vol 21, No 2 (2021): October 2020 - April 2021
Publisher : Vocational School Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/gt.v21i2.36170

Abstract

The design of Chatbot aims to facilitate social activities in all areas to be considered. Chatbot is one type of machine that can communicate with humans using natural language. Communication happening via chat is a written conversation. Chatbot is a form of application implementation from Natural Language Processing (NLP) that belongs to one branch of artificial intelligence or Artificial Intelligent (AI). Social Media now provides a service that allows developers to process and integrate chatbot applications. This paper aims to review the papers that build chatbot applications in various social media using various testing methods. The contribution of this paper is to determine which method is able to measure the level of chatbot accuracy well. This review paper will choose the equation of the most widely used test methods and social media from various papers so that further research is expected to implement the right testing methods and use better social media in terms of user experience, features, and services. The review paper shows that the Black-box and System Usability Scale testing methods are most used in the review paper. This testing method is a type of method that performs testing of the flow and how the chatbot works to achieve functional validation throughly.
Prediction of Feasibility of Entrepreneurial Proposals in Student Creativity Program Harun Nasrullah; Endah Sarah Wanty; Arief Wibowo
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.7253

Abstract

Student Creativity Program is a program organized by the Directorate of Learning and Student Affairs, Directorate General of Higher Education, Research, and Technology, Ministry of Education, Culture, Research and Technology as a national level student creativity event as an effort to grow, accommodate, and realize students' creative and innovative ideas. Based on 2017-2021 data, each year an average of 63,337 proposals are received, administrative and substance evaluations involve complex assessment components and are carried out manually so that it takes a relatively long time in the calculation process. Then a special method is needed that speeds up the processing of assessment data. This research was conducted on the substance of the Entrepreneurship Sector to predict the feasibility of a proposal to get funding applying data mining with the Naive Bayes Classifier (NBC) and K-Nearest Neighbor (K-NN) algorithms with a comparison between Euclidean Distance and Manhattan Distance. From the results, it is known that NBC produces 96.49% accuracy and 0.912 Kappa. K-NN with the largest Euclidean Distance calculation in K-5, K-7 and K9 with an accuracy of 99.04% and Kappa 0.975, K-NN Manhattan Distance calculation produces the greatest accuracy of all the methods used by researchers, namely 100% and Kappa 1,00 categorized as Excellent. So the conclution is that the K-NN method with K-5 which produces the greatest accuracy and Kappa can be recommended to PKM stakeholders in funding feasibility algorithms.
Analisis Sentimen Opini Masyarakat Terhadap Keefektifan Pembelajaran Daring Selama Pandemi COVID-19 Menggunakan Naïve Bayes Classifier Ari Wibowo; Firman Noor Hasan; Luthfi Akbar Ramadhan; Rika Nurhayati; Arief Wibowo
Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa dan Inovasi Volume 4 Nomor 2 Tahun 2022
Publisher : Fakultas Teknik Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/asiimetrik.v4i1.3577

Abstract

Since Indonesia was affected by the Covid-19 pandemic, one of the sectors affected was Education. The government makes an online learning system policy where the system is run with an online process. Not a few of them complained about the limitations of activities issued by the government. Twitter social media is often used to express opinions about concerns about programs issued by the government. The Twitter data crawling process was carried out using the hashtag "learning from home" to get as many as 1,000 datasets, followed by the process of removing duplicates which left 524 datasets and then carrying out the implementation stage of the Naïve Bayes Classifier Algorithm. The purpose of this study was to determine the number of positive and negative sentiments from the dataset labeling classification and to determine the accuracy results of using the Naïve Bayes Classifier method as well as the results of evaluation tests on positive and negative sentiment datasets. Based on the experiment, positive sentiment was obtained as many as 480 and negative sentiment as many as 44 out of 524 datasets. The accuracy results in the evaluation test process get results of 88.5% where negative sentiments get a precision value of 12%, recall 17%, and f1-score 14%, while positive sentiments get a precesion value of 95%, recall 93%, and f1 -score 94%.
Data Mining Klasterisasi dengan Algoritme K-Means untuk Pengelompokkan Provinsi Berdasarkan Konsumsi Bahan Bakar Minyak Nasional Arief Wibowo; Indah Rizky Mahartika
Prosiding SISFOTEK Vol 3 No 1 (2019): SISFOTEK 2019
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (517.822 KB)

Abstract

Petroleum is one of the natural resources that play an important role in human life, mainly used as the fuel needed by all levels of society. The distribution of fuel oil (BBM) in Indonesia is carried out by the Downstream Oil and Gas Regulatory Agency (BPH Migas). With the availability of data on fuel consumption in each province, it can be seen that the pattern of fuel consumption in Indonesia is beneficial for regulators in the management of fuel distribution. To find out the pattern of national fuel consumption, we need a model of grouping regions in Indonesia based on the level of fuel consumption in each province. This study analyzes data on national fuel consumption throughout Indonesia using the Data Mining Clustering technique, and the Euclidean Distance measurement method. The final results of this study indicate that the K-Means algorithm can group provinces based on national fuel consumption levels into three clusters with their respective specifications. Modeling results were evaluated using the Davies Bouldin Index (DBI) instrument, with a value of 0.32. The results of testing using DBI approaching 0 indicate that the clusters formed are relatively very good and ideal.
Pemodelan Sistem Prediksi Kelayakan Pengajuan Kredit Kepemilikan Rumah Dengan Metode C4.5 Dan Naive Bayes Lingga Desyanita; Arief Wibowo
Elkom : Jurnal Elektronika dan Komputer Vol 13 No 2 (2020): Desember: Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

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Abstract

A house for every human being is the main and most important need compared to others needs in general. A financial institution is an institution engaged in the financial sector where its customers are people from various walks of life with various behaviors. Lending is a business activity that carries a high risk and affects the business continuity of a banking company. The problem that is often faced in providing home loans is determining the decision to extend credit to prospective customers, while another problem is that not all home loan payments by customers can run well or commonly known as bad credit. One of the causes of bad credit is an assessment error in making credit decisions. Data mining is a process used to analyze cases in order to find the best performance of an algorithm being tested. One way to get information or patterns from a large data set is to use techniques in data mining. There are many classification methods that can be used to produce precise accuracy values. In this study, two classification algotihm methods are used in classifying the home crediting dataset, namely the C4.5 decision tree algorithm and the Naïve Bayes algorithm. The comparison of the two algorithms produces an accuracy value fo the Naïve Bayes algorithm of 36.36% and the Decision Tree C4.5 algorithm has an accuracy rate of 59.54%.
Pengembangan Knowledge Management System Berbasis Cloud Pada Kelas Karyawan Universitas Pramita Indonesia Hadidtyo Wisnu Wardani; Arief Wibowo
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 19, No 1 (2022): APRIL 2022
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/bit.v19i1.1757

Abstract

Knowledge Management System (KMS) is very important to manage knowledge and tacit to have added value for the organization, especially the Pramita Indonesia Employee Class, related to the routines of all employees in the work unit who are expected to provide solutions in solving problems that occur. With conditions that often occur at this time, knowledge and experience have not been documented, the socialization of standard operating procedures is not running properly and the tenure of employees is unknown so when there is a change of employees in the organizational structure, it will result in the loss of knowledge and experience possessed by an employee, confusion or incomplete information received to create misunderstandings between employees in communicating. Based on the results of research that are following the conditions that exist in the class work unit of Pramita Indonesia employees, the author tries to develop a KMS model. By using the Tiwana model framework, and the Becerra-Fernandez progress structure research methodology, as well as using the SECI Nonaka model development, to test the framework model using the Gathering Conversation (FGD) and Black Box Testing strategies, and using a Likert scale for scoring the system test results. , and the quality of the KMS software prototype is 72% with the Very Appropriate category, so the results show that the overall KMS prototype has been running well so that the proposed system can be used in managing knowledge to provide maximum service solutions efficiently and effectively
Penerapan Algoritma Stemming Nazief & Adriani Pada Proses Klasterisasi Berita Berdasarkan Tematik Pada Laman (Web) Direktorat Jenderal HAM Menggunakan Rapidminer Septian Firman S Sodiq; Wahyu Desena; Arief Wibowo
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.7192

Abstract

Abstract. Website is a medium used to convey information. Currently the news on the website of the Directorate General of Human Rights is not well categorized. there are only three news categories, namely news highlights, news, activities, and regional office info, but there is no information related to news categories based on thematics. this study aims to cluster news on the ham.go.id website based on the thematic using rapidminer, in rapidminer there is a stemporter feature but it is not yet available in Indonesian, therefore the author carried out the stemming process by utilizing the Nazief & Adriani stemming algorithm to improve clustering performance. To determine the best number of clusters, the author uses the lowest DBI value and performs external testing using the Confusion Matrix. From this study, the DBI value without going through the stemming process was 4,351 with an accuracy of 81.58%, recall 83.15%, precision 80.59%. After stemming using the Nazief & Adriani algorithm, the DBI value was 3,935 with an accuracy value of 86.84%, recall 85.71%, precision 82.50%.
Penerapan Algoritma Forward Chaining Untuk Mendiagnosa Penyakit Pernapasan Pada Klinik Mitra Bhakti Bayu Sadewo; Arief Wibowo
Jurnal Ticom: Technology of Information and Communication Vol 11 No 1 (2022): Jurnal Ticom: Technology of Information and Communication
Publisher : Asosiasi Pendidikan Tinggi Informatika dan Komputer Provinsi DKI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Klinik setiap harinya selalu mengakomodir serta mengelola data pasien yang berkonsultasi dan berobat dengan dokter. Namun, dalam konsultasi diklinik masih dirasa kurang baik, karena pendataan yang manual sehingga menghambat waktu dan menyebabkan antrean pada saat ingin berkonsultasi sehingga membuat lambatnya pasien saat ingin menemui dokter. Pada wawancara penelitian fasilitas pada klinik Mitra Bhakti menjelaskan bahwa memiliki keluhan yang banyak pada pasien penyakit pernapasan. Pasien yang merasakan sakit pada sistem pernapasan ingin secepatnya berobat dan berkonsultasi dengan dokter karena dari penyakit tersebut memiliki gejala yang mengganggu pada kegiatan sehari-hari contohnya pada gejala batuk, ada batuk berdahak dan batuk tidak berdahak. Dengan masalah yang dijabarkan penelitian ini menggunakan metode forward chaining yang digunakan untuk mendiagnosis penyakit pernapasan dengan gejala-gejala yang dirasakan oleh pasien. Penelitian ini bertujuan untuk membangun aplikasi Sistem pakar Diagnosis Penyakit Pernapasan Menggunakan Metode Forward Chaining berbasis web. Berdasarkan permasalahan tersebut maka penliti ingin menyelesaikan masalah antrian yang biasa terjadi pada Klinik Mitra Bhakti, Khususnya pada penyakit pernapasan yang mana pada saat dilakukan penelitian sedang marak penyakit covid-19 yang mana orang sering beranggapan jika memiliki gejala batuk adalah penyakit covid-19. Sistem Pakar ini menggunakan metode Forward Chaining dengan data penelitian berupa gejala yang diberikan oleh pakar sebagai acuan dalam menentukan hasil diagnosis dari penyakit yang diderita pasien.Dari hasil pada pengujian 10 pasien dapat disimpulkan sistem ini dapat mendiagnosis penyakit pernapasan dengan keakuratan 70%. Oleh karena itu sistem ini diharapkan dapat membantu keefektifan dalam mendiagnosis serta konsultasi juga membantu dokter untuk menentukan kesimpulan akhir dari gejala-gejala pasien sesuai fakta dan yang ada, dan juga diharapkan agar dapat membantu pasien mengenali gejala penyakit pernapasan tanpa harus datang ke Klinik Mitra Bhakti.
Pemodelan Prediksi Status Keberlanjutan Polis Asuransi Kendaraan dengan Teknik Pemilihan Mayoritas Menggunakan Algoritma-Algoritma Klasifikasi Data Mining Dyah Retno Utari; Arief Wibowo
Prosiding Seminar Nasional Teknoka Vol 5 (2020): Prosiding Seminar Nasional Teknoka ke - 5
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

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Abstract

Motor vehicle insurance is a type of business that covers loss or risk of damage that can arise from various potential events that happen to vehicles. Competition in the insurance business, especially for motorized vehicles, demands innovation and strategies to guarantee business continuity. One of the efforts that companies can make is to predict vehicle insurance policies' sustainability status by analyzing customer profile and transaction data. Prediction of the policyholder's decision is essential for the company because it can determine the marketing strategy that influences its decision to renew the insurance policy. This study has proposed a prediction model for vehicle insurance policies' sustainability status with the majority selection technique from the classification results using data mining algorithms such as Naive Bayes, Support Vector Machine, and Decision Tree. The test results using the confusion matrix show that the best accuracy value is obtained at 93.57%, whatever for the precision value reaches 97.20%, and the recall value is 95.20%, and the F-Measure value is 95.30%. The best model evaluation scores are generated using the majority voting approach, outperforming a single classifier-based prediction model's performance.
Comparative Analysis of Naïve Bayes and Decision Tree Algorithms in Data Mining Classification to Predict Weckerle Machine Productivity Fried Sinlae; Anugrah Sandy Yudhasti; Arief Wibowo
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 1 No 2 (2022): September 2022
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.093 KB) | DOI: 10.29207/joseit.v1i2.3439

Abstract

The level of data accuracy in everyday life is necessary because it is reflected in the ever-advancing development of information technology. Analysis of data processing in information that can provide knowledge with the help of data mining systems. Algorithms commonly used for prediction are Naive Bayes and Decision Trees. The purpose of this study is to compare the Nave-Bayes algorithm and the decision tree algorithm in terms of the accuracy of predicting the productivity of the Weckerle machine at PT XYZ. The method used is a literature study from various related sources and understanding of the data in the source related to the subject of the classification method of the Naive Bayes algorithm and the decision tree into the data mining system. The results of this study are a classification using the Nave-Bayes algorithm with a higher level of confidence than the decision tree algorithm.
Co-Authors - Arientawati - Sumardianto Adita, Ita Afifah Khaerani Afifatussalamah, Rizka Ahmad Sururi Ahmad Sururi Akbar, Ahmad Aldizar Al Fatach, M Khabib Anggraini, Julaiha Probo Anita Diana Anugrah Sandy Yudhasti Apriati Suryani Ardhianto, Angga Ardianah, Eva Ari Wibowo Arief Umarjati Asep Permana Atik Ariesta Bayu Sadewo Bayu Satria Pratama Binarto, Antonius Jonet Boerhan Hidayat, Boerhan Danar Wido Seno Darki, Ni Wayan Yustika Agustin Diah Indriani Didik Hariyadi Raharjo Didin Muhidin Dwi Kristanto Dwi Yulianti Dyah Retno Utari Dyah Retno Utari, Dyah Retno Endah Sarah Wanty Fajar Siddik Chaniago Farah Chikita Venna Farid Setiawan Farid Setiawan, Farid Febrilliani, Jihan Sastri Fenny Irawati Fernando, Donny Firman Noor Hasan Firmanty Mustofa, Vina Fitri Nur Masruriyah, Anis Fitri Rachmilah Fadmi Fitriadi, Rifqi Fitriani, Netty Fransiska Vina Sari Frenda Farahdinna Fried Sinlae Ghapur, Abdul Gurdani Yogisutanti Hadidtyo Wisnu Wardani Hananto, Agustia Handoko, Andy Rio Hanindita, Meta Herdiana Hari Basuki Notobroto Haris Achadi, Abdul HARIYANTO HARIYANTO Harun Nasrullah Hayatul Khairul Rahmat Henry Henry Hidayat, Manarul Hidayat, Sarifudlin Huda, Ratu Najmil I MADE MINGGU WIDYANTARA, I MADE MINGGU Indah Rizky Mahartika Inge Virdyna Irfan Hadi Irfan Nurdiansyah Istiqoomatun Nisaa Iwan Irawan Jasmine, Meuthia Joko Sutrisno Jovansgha Avegad Jumaryadi, Yuwan Kanasfi, Kanasfi Karma, Ni Made Sukaryati Karyaningsih, Dentik Kresno Yulianto KRESNO YULIANTO KUNTORO Kuntoro Kuntoro Kurnia Setiawan Kutanto, Haronas Larasati, Pamela Linda Lingga Desyanita Luthfi Akbar Ramadhan Mahmudah Mahmudah Mailana, Agus Maria Adiningsih Marlina, Hesti Maskur A, Moch Riyadi Megananda Hervita Permata Sari Megawati, Rina Miftahul Arifin Miftahul Arifin Mochammad Rizky Royani Moh Makruf Muhamad Fadel Muhammad Febrian Rachmadhan Amri Muhammad Risky Mulyati Mulyati Nendi, Nendi Ningrum, Yogi Ajeng Nugroho, Angelika Pratiwi Widya Nur Aisiyah Widjaja, Nur Aisiyah Nur Rohman Nurcahya, Gelar Nurfidaus, Yasmine Nursyi, Muhamad Pattipeilohy, William Frado Pattipeilohy, William Frado Pebriaini, Prisma Andita Poppy Ruliana Pradiptha, Anindya Putri Probo Anggraini, Julaiha Purwadi Purwadi Putra, Andi Agung Putra, Rinaldi Febryatna Duriat Rachmah Indawati Rahman, Reza Rahmawati, Nur Anisah Rakhman, Abdulah Rakhmat Rakhmat Rakhmat Rakhmat RAMAYU, I Made Satrya Rangkuti, Muhammad Yusuf Rizqon Ratna Ayu Sekarwati Ratna Ayu Sekarwati Relawanto, Bowo Ria Puspitasari Rika Nurhayati Riki Ramdani Saputra Rina Megawati Ririh Yudhastuti Risaychi, Diva Ajeng Brillian Ristiana, Ina Riza, Yeni Rizkiyanto, Muhamad Ardiansyah Roedi Irawan Rojakul, Rojakul Rosita Dewi, Erni Ruliana, Poppy Rusdah Ryo Tanaka Sabirin, Sahril Sadewo, Bayu Santoso, Febrina Mustika Saptari Wijaya Mulia Sari Anggar Kusuma Melati Sari, Fransiska Vina Sasongko, Raden Satiri Satiri, Satiri Selly Rahmawati Selly Rahmawati Septian Firman S Sodiq Septiani, Riska Setya Haksama Setyowati, Erlin Shofinurdin Shofinurdin Siddik Chaniago, Fajar Sigit Ari Saputro Sigit Budi Nugroho Siregar, Sutan Syahdinullah SITI NURUL HIDAYATI Sitti Aliyah Azzahra Soenarnatalina Melaniani Sudewo, Andika Hasbigumdi Sugiyarta, Ahmad Sujiharno Sujiharno Sumarna, Presma Dana Scendi Suntoro, Dimas Fahmi Tiaharyadini, Rizka TRISNAWATI, WULAN Tulus Yuniasih Umam, Mohamad Hafidhul Vasthu Imaniar Ivanoti Wahyu Cesar Wahyu Desena Wahyudi, Widi Wahyuni, Chatarina Unggul Wangsajaya, Yosia Heartha Dhalasta Wasis Budiarto Wibiyanto, Alif Dewan Daru Widiyaningrum, Diyah Kiki Widyanto, Tetrian Windhu Purnomo Yahya Darmawan Yudanto, Satyo Zakaria Anshori Zaqi Kurniawan