Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

8.19

P-Index

This Author published in this journals

All Journal Teika SPEKTRUM INDUSTRI Jurnal Informatika Elementary: Islamic Teacher Journal Jurnal Teknik Elektro E-Dimas: Jurnal Pengabdian kepada Masyarakat Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknoinfo J-SAKTI (Jurnal Sains Komputer dan Informatika) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOISIE (Journal Of Information Systems And Informatics Engineering) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Tekno Kompak Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) JIKA (Jurnal Informatika) Infotek : Jurnal Informatika dan Teknologi Academia Open Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) J-SAKTI (Jurnal Sains Komputer dan Informatika) Indonesian Journal of Education Methods Development Indonesian Journal of Innovation Studies Indonesian Journal of Public Policy Review Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) PELS (Procedia of Engineering and Life Science) Procedia of Social Sciences and Humanities Indonesian Journal of Islamic Studies JOINCS (Journal of Informatics, Network, and Computer Science) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Innovative Technologica: Methodical Research Journal Physical Sciences, Life Science and Engineering Indonesian Journal of Applied Technology Journal of Technology and System Information Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Journal of Electrical Engineering Journal for Technology and Science JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)

Mochamad Alfan Rosid

Unknown Affiliation

Author-ID : 3651921

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

Published : 73 Documents Claim Missing Document

Claim Missing Document

Articles

Title

Expert system diagnosing Android-based lung disease Fahreza Ramadhan; Mochamad Alfan Rosid
JOINCS (Journal of Informatics, Network, and Computer Science) Vol 2 No 2 (2019): November
Publisher : Universitas Muhammadiyah Sidoarjo

This research aims at the medical field utilizing technology to help improve better services to the wider community and be able to create an expert system to diagnose lung disease in children. This study uses the Dempster-Shaferke method in an expert system to diagnose lung disease in children. The lungs are respiratory organs associated with the circulatory system, the function of the lungs themselves is as a place of exchange of oxygen with carbon dioxide in the blood. The results of this study are expected to simplify the process of diagnosing lung disease in children, and also this expert system can help to ease the task of experts

Classification of Student Complaints with the Naive Bayes and Literature Methods Haris Ahmad Gozali; Mochamad Alfan Rosid; Sumarno
JOINCS (Journal of Informatics, Network, and Computer Science) Vol 3 No 1 (2020): April
Publisher : Universitas Muhammadiyah Sidoarjo

E-Complaint Data is a collection of data which contains comments or complaints from students towards the University. Lots of comments - comments that occur in the university environment about the performance facilities of lecturers etc ... Text mining is also known as text data mining or knowledge search in a textual database is a semi-automatic process of extracting data patterns. The purpose of text mining is to get useful information from a collection of documents. In this study using the naïve Bayes method with TFIDF weighting features. The stages will be taken to determine its classification. First is taking data from the E-Complaint System then the data will go through the preprocessing stage using literary libraries, after going through the preprocessing stage the data will be divided into 2 namely training data and testing data. Then the training data will be carried out the TF-IDF weighting process up to the probability, if it has, the next is to process the testing data by determining priors. Next is the data testing stage between the testing data and the training data, the results of the testing data will come in the form of a predetermined category. The trial results show that the classification of complaints with the naïve Bayes algorithm and with the TF-IDF feature and literary libraries in the preprocessing process has an average accuracy that is quite high at 82%.

Analysis of Community Sentiments Regarding Plans to Relocate National Capital Using the Naïve Bayes Method Tomi Eko Hidayat; Mochamad Alfan Rosid; Ika Ratna Indra Astutik
JOINCS (Journal of Informatics, Network, and Computer Science) Vol 3 No 2 (2020): November
Publisher : Universitas Muhammadiyah Sidoarjo

This study aims to analyze sentiment towards the transfer of new capitals derived from comments on the tweeter. The method used in this research is Naïve Bayes Classifier, a classic method that has a pretty good accuracy. Naive Bayes Classifier is a probabilistic classification based on the Bayes theorem, taking into account naïv independence assumptions. In addition to using the naïve bayes method, in this study the researchers also used word weighting. The weighting word used is TF-IDF, which is a combination of term frequency and inverse document frequency. By using 3 testing methods, namely Confusion matrix, Precission and Recall, and K-Fold Cross Validation. The results obtained in this study are 3 document classifications, namely Positive, Negative and Neutral. Testing is done by dividing the document into 2 subsets, namely training data and test data and the resulting accuracy of 64.6%.

JSON Implementation to Minimize the Use of the Number of Columns of a Table in a PostgreSQL Database Mochamad Alfan Rosid
JOINCS (Journal of Informatics, Network, and Computer Science) Vol 1 No 1 (2017): April
Publisher : Universitas Muhammadiyah Sidoarjo

On the development of the database currently has become a very important thing, each will plan something, consider any thing we will need and use existing data in a database, The development of the database currently has become a very important thing, when we want to plan something and consider everything, we will need and use existing data in a database, PostgreSQL is one Object Relational Database Management Systems (DBMS) open source with a lot of features that are not less sophisticated to commercial databases. On daily use, it sometimes occurs a case that requires a dynamic column, therefore we should make the new columns to meet those needs. However, if each row of the table column requires different column and potentially need another ones, then it is going to be useless. On the research of utilizing the technology of JavaScript Object Notation (JSON),Json_encode PHP programming language can simplify the use of the column so that a new column is no longer needed when we want to create a new column on the table, we only need a new column that stores an array that has been converted into a JSON string forms the result of json_encode that represents the column name and the content of the columns of a table.

Sarcasm Detection in News Headline Dataset with Ensemble Deep Learning Method: Deteksi Sarkasme Pada Dataset News Headline Dengan Metode Ensemble Deep Learning Mochamad Alfan Rosid; Siti Nur Haliza; Yulian Findawati; Uce Indahyanti
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 6 No. 2 (2023): November
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v6i2.1628

Sarcasm, a prevalent linguistic device, is frequently used in public discourse, often causing offence and distress to the listener. The complexity inherent in detecting sarcasm is a significant and ongoing challenge in the field of sentiment analysis research. The widespread use of this phenomenon in diverse conversational contexts further complicates its identification in data sets full of human interactions. Deficiencies in methodologies for distinguishing such statements adversely affect the performance of sentiment analysis, especially in distinguishing negative, positive or neutral sentiments. Inaccuracies in sarcasm detection can affect the classification results of sentiment analysis. Therefore, sentiment analysis seeks to categorise sarcastic sentences that, despite appearing positive, actually contain negative meanings. This research aims to build a deep learning ensemble stack model. The basic deep learning methods used are Bidirectional Gated Recurrent Unit (BiGRU) and Convolutional Neural Network (CNN). LightGBM is used to perform stack ensemble of deep learning methods. The dataset used comes from the Kaggle website and consists of English headlines. The findings show that the stack ensemble method outperforms BiGRU and CNN, evidenced by an accuracy rate of 91.2% and an F1 score of 90.2%. Therefore, from the above discussion, it can be concluded that the LightGBM method emerges as the optimal solution for sarcasm detection

Co-Authors Ade Eviyanti Adi Putra, Lutfi Agoeng Dwi Djoelianto Ahmad Syaichul Hadi aini firdausi nuzulla Aisha Hanif Alifiyah Rohmatul Hidayati Alim, Kholqi Aminy, Ritzana Aisyah Anjasmara, Dimas Bayu ARDIANSYAH ARDIANSYAH Ardiansyah, Alfinas Ardilah, Diamond Heris Arief Senja Fitrani Arif Senja Fitrani Arif Senja Fitriani Astutik, Ika Ratna Indra Azizah, Nuril Lutvy Bagus Dwi Kurniawan, Bagus Dwi Bagus Dwi Yulianto Burnama, Zendhi Yuna Busono, Suhendro Damasta, Ifanda Reza Danu Pamungkas Darmawan, Dikky Putra Diana Cindy Agustin Dina Dwi Oktavia Rini Dony Rakhmad Hidayat Dwi Saka Dharmawan Edwin Pramana Fahmi Anggara Santosa Fahreza Ramadhan Fajar Muharram Fauzan, Mochamad fil ardi, Mochamad kholifatu Fitriani, Arif Senja Ghozali Rusyid Affandi Gunawan Gunawan Gunawan Hadi, Miftakhul Hamzah Setiawan Haris Ahmad Gozali Hasan Basri Hasan, Jamal Hindarto Ika Ratna Indra Astutik Ika Ratna Indra Astutik Imanudin, Giri Fajar Irwan Alnarus Kautsar Kurniawan, David Hogy Tri Mabrur, Moh Faris Ghossani Mardiono, Adimas Prasetyo Moch. Bahak Udin By Arifin Mochamad Rifqi Aminudin Mohamad Haris Muzadi Muhammad Fachruddin, Muhammad Muhammad Jamilul Iman Muhammad Muzany Mulyoutomo Novia Ariyanti Nurdyansyah Nursapdahi, Nursapdahi Pamungkas, Nicky Ibrahim Pandi Rais Prasetio, Aga Dandi Prasetyo, Agbar Pratama, Nikko Enggaliano Rachmadany, Andry Ramadhan, Aldo Reghan Ramadhan, Mochammad Hisyam Syah Ratih Puspitasari Resa Rakhman Ribangun Bamban Jakaria Rizaldi, Dedy Robby Firmansyah Ardha Rohman Dijaya Rukhi Alfian, Muhammad Ruri Aditya Pratama Sambada, Muhammad Arginanta Kafi Setiawan, Hamzah Shiddiq, Zulfian Syahril Siti Nur Haliza Soni Abdala Sukma Aji Sumarno Sumarno . Sumarno Sumarno Syaichul Hadi, Ahmad Syaifudin, Hilmi Fajar Syamsiar, Syamsiar Taurusta, Cindy Tomi Eko Hidayat Triwahono, Handi Uce Indahyanti Utama, Bagas Riski Witno, Kasaifi Al Qurdhowi Bin Yulian Findawati Yunianita Rahmawati, Yunianita Yusuf, Farid Maulana Zahputra, Aldy Trisza

Title Search

Found 5 Documents Search Journal : JOINCS (Journal of Informatics, Network, and Computer Science)

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 5 Documents
Search
Journal : JOINCS (Journal of Informatics, Network, and Computer Science)