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Intelmatics
Published by Universitas Trisakti
ISSN : -     EISSN : 27758850     DOI : https://doi.org/10.25105/itm
Core Subject : Science,
Computer Science & IT
The IntelMatics Journal is a scientific journal published by the department of informatics engineering at Trisakti University. The purpose and objective of the publication of the IntelMatics journal are as a means of dissemination of international standard science in the field of software engineering, information security, and business analysis in the scope of data intelligence and visualization. Journal will be published every sixth month
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 6 Documents
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Search results for , issue "Vol. 3 No. 1 (2023): Januari-Juni" : 6 Documents clear
DEVELOPMENT OF PUSKESMAS LOCATION SEARCH APPLICATIONS IN DKI JAKARTA USING HARVESINE METHOD Difa Bagas Atmaja; Syaifudin; Teddy Siswanto
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.5040

Abstract

The development of this application aims to produce information from the raw data of health centers in the DKI Jakarta province in 2017 which are still in the form of datasets for later data sets to be processed into an information center where this application focuses on searching the location of the puskesmas. This application uses the harvesine formula as the method of searching for the nearest health center and the waterfaal model as its development method. Using Puskesmas spatial data in the form of latitude and longitude coordinates and non-spatial data in the form of names, addresses and so on are processed into useful information for the Indonesian people, especially those in the DKI Jakarta province to make it easier for people to access information on community health centers.
A “DOSPEMKU” CHAT APPLICATION PROTOTYPE WITH THREADING FEATURE USING CORDOVA FRAMEWORK FOR ANDROID-BASED COMPETENCY CONSULTATION: Chat Application With Threading Feature Using Cordova Framework For Android-Based Anwar Ibrahin Dana; Ahmad Zuhdi; Gatot Budi Santoso
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.14848

Abstract

Abstract—In this days, human communication that is efficient and easy is through a system of social media chat application devices. By relying on internet signals, users can carry out meeting activities between one party using social media without the need to use face-to-face meetings, one of which is in communicating consultations on competency issues in the world of education. The reference for this final project is based on the author's thoughts to form a web-based media Halodoc, which is the formulation of the core problem of this final project. With DOSPEMKU, the author can hope to solve some case examples. As for examples of cases such as difficulties coming because there is no time to go (in busyness), determining a time schedule that is not suitable, being inflexible, and so on. DOSPEMKU is a chat application based on the Android operating system, implementing Usecase Diagrams and Activity Diagrams as a designer for functionality requirements that are implemented into DOSPEMKU. The Cordova network is used as an Integrated Development Environment (IDE) platform with html, javascript programming languages ​​and uses the phpMyAdmin database as the database base. Design Implementation uses several methods, ranging from interface design, database, to functionality design in determining what features are contained in DOSPEMKU. The implementation process is tested both in terms of functionality and non-functionality to test whether the application is in accordance with the design stage. So that the process of designing, implementing and testing it was found that the application was made according to and accommodated the conversation according to the discussion.
Prediction of Inefficiency in Health Insurance Administration Institutions in Indonesia using Light Gradient Boosting Machine Kevin Valerian Ninia; Binti Sholihah; Abdul Rochman
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.15985

Abstract

Everyone understands that health is something that must be considered and should not be ignored. Therefore, the government seeks to form institutions that can organize health social security for the community. However, in practice it is not often found that there are cases of waste in the services provided (inefficiency). So that research was carried out using the Light Gradient Boosting Machine (LightGBM) to provide solutions for solving cases of waste (inefficiency) in health social security administering institutions.
An ANALYSIS OF OIL SENTIMENT SENTIMENTS ON TWITTER USING SUPPORT VECTOR MACHINE: ANALISIS SENTIMEN SUBSIDI BAHAN BAKAR MINYAK (BBM) DI TWITTER MENGGUNAKAN SUPPORT VECTOR MACHINE Ibnu Bilal Marta Prawira; Binti Solihah; Syandra Sari
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.16187

Abstract

Twitter is one of the social media platforms used by people in Indonesia. Twitter is often used by its users to express opinions regarding a product, institution or event. From the keyword fuel, fuel subsidy is a keyword that is currently a trending topic because changes in fuel subsidies affect the prices of other staples, to find out the value of sentiment in public opinion, sentiment analysis is one of the methods used is the support vector machine and lexicon based. Lexicon is a labeling method by matching the words contained in the document with the words contained in the dictionary. After labeling, the data is tested using the classification method, the classification stage is carried out after going through the preprocessing phase, where the tweet classification results tend to be positive or negative, using the Support Vector Machine method and validated by K-Fold Cross Validation.This research produced 50,001 data which were divided into 21,561 positive sentiments, 9206 neutral sentiments and 19234 negative sentiments. From these results it can be concluded that the data shows public support for rising fuel prices or changing fuel subsidy prices.
Paper Visualisasi Data Pembelian Barang dan Jasa Pada PT. Transcoal Pacific Menggunakan Exploratory Data Analysis: Visualization of Goods and Services Purchase Data at PT. Transcoal Pacific Using Exploratory Data Analysis Chandra Ganda Manuel Malau; Binti Sholihah; Agus Salim
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.16302

Abstract

The comfort and safety of the ship's crew in carrying out the voyage relies on the goods facilities and ship maintenance in carrying out shipping operations. In this case PT. Transcoal Pacific as a company engaged in logistics delivery services monitors with vendors engaged in the supply of goods in providing services in the form of ship crews and ship crews. However, in the implementation of business processes, there is no visual data that can provide information for companies regarding the purchase of goods and comparisons from 2 other branches. In this study, the preprocessing stage was carried out to eliminate inaccurate parts of the dataset and tables to create data visualization. After that, Exploration Data Analysis was carried out to obtain graphs to strengthen the analysis carried out. The expected result of this research is to form a dashboard as a place to visually process information to make the right decisions to improve business performance more effectively.
Recommendation System for Mental Health Article on Circle Application Gading Sectio Aryoseto; Is Mardianto; Anung B. Ariwibowo
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.16343

Abstract

Healthy mental health is a condition when minds are in a state of peace and calm and not disturbed, thus enabling us to enjoy our daily lives with respect for others. In Indonesia, there are quite a number of sufferers of mental health disorders, approximately 19 million people over the age of 15 experience mental and emotional disorders, both at mild to severe levels. These data show that the Indonesian state has not been able to properly address mental health problems and that the existence of a pandemic tends to increase sufferers of mental health disorders, which if left unchecked will have a negative impact. Based on this problem, the Circle application, that focuses on mental health using Android technology that supports self-help with several services, one of which is an article service. The article service in the Circle application requires a recommendation system that can recommend articles according to the mental health conditions experienced by users so that the articles are able to alleviate the mental health problems currently experienced by users. Topic Modeling is an approach to analyze a collection of text documents and group them into topics. Topic Modeling has several methods that can be applied in making topics, one of which is BERTopic. It is a technique that leverages Transformer and c-TF-IDF to create dense clusters, preserving keywords in topic descriptions while making topics easier to interpret. There are 3 important components of the BERTopic algorithm namely Document Embedding, Document Clustering, Topic Representation. This study uses Topic Modeling with the BERTopic method as the baseline for the mental health article recommendation system in the circle application.

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