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Journal : International Journal of Information Technology and Computer Science Applications (IJITCSA)

K-Means Cluster Algorithm for Grouping Inequality in Regional Development Munandar, Tb Ai; Handayani, Dwipa
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 1 (2023): January - April 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (495.534 KB) | DOI: 10.58776/ijitcsa.v1i1.20

Abstract

Unsupervised learning is a subset of machine learning. Many unsupervised learning algorithms are used to solve various problems, especially the extraction of hidden data patterns. One of the problems that concerns unsupervised tasks is clustering. Clustering techniques are widely used for data grouping needs, one of which is development inequality clustering. The classification of development inequality is an important consideration in a country's regional development strategy. However, development groupings often do not pay attention to the hidden information aspects of the data, so they do not get the appropriate results. This research was conducted to provide an additional alternative in the realm of development inequality clustering, namely by classifying development data using the k-means algorithm. The data used is GRDP data for 41 regions in the western part of Java Island for the 2010–2021 range. The results show that the forty-one regions are grouped into four clusters. The first cluster (C1) contains 35 regions, the second cluster (C2) contains three regions, the third cluster (C3) contains four regions, and the fourth cluster (C4) contains three regions. Based on the cluster results, it can be seen that all members of cluster C4 are areas with the best level of development, while cluster C1 is the area with the lowest level of development. As for clusters C2 and C3, these are areas with development levels between clusters C1 and C4. The grouping results can be used by policymakers or local governments to determine the direction of future development priorities based on the cluster with the lowest level of development.
Comparative Study of Classification Algorithms for Customer Decisions on Telecommunication Products Using Supervised Learning Kristian Vieri, Jhon; Munandar, Tb Ai; Srisulistiowati, Dwi Budi; Handayani, Dwipa; No’eman, Achmad; Sri Lestari, Tyastuti
International Journal of Information Technology and Computer Science Applications Vol. 1 No. 2 (2023): May - August 2023
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (801.899 KB) | DOI: 10.58776/ijitcsa.v1i2.34

Abstract

Customers are the main goal of all business fields, without customers the company will not be able to continue or compete in the business field it is in, even though the company has brilliant products, if it does not have an increase in the number of customers the business will not be able to develop or even go bankrupt. Therefore, it is necessary to make observations and make applications that are able to predict customers who will subscribe so that companies can predict customers who will subscribe correctly without having to wait for confirmation from customers whose possibilities are still unknown. This can be very useful for any company because companies no longer need to look for random customers where it only takes time to find customers. PT. Telekomunikasi Indonesia with its product (Indihome) which is struggling to compete in the business world in the telecommunications and internet sector. Therefore research and development of this application are carried out so that PT. Indonesian telecommunications can get its customers quickly without having to spend a lot of money and effort. Making this application uses a classification method from machine learning technology based on customer historical data. The classification method has many strong algorithms for predicting variables that have more than 1 label. Some of the algorithms used are Logistic Regression, Random Forest Classifier, Support Vector Machine and Decision Tree which are provided by modules in the python programming language, namely SkLearn. The four algorithms will be tested with data balanced using the Oversampling method from the Smote algorithm to get optimal results in automatically predicting customers.
Bayadome Geotours (BATOUR) Prototype for Geosite Management at Bayah Dome Geopark, Banten Munandar, Tb Ai; Sri Lestari, Tyastuti; Handayani, Dwipa; Noe’man,, Achmad; Fathurrazi, Ahmad; Priatna, Wowon; Karyaningsih, Dentik; Kapriadi, Engkap
International Journal of Information Technology and Computer Science Applications Vol. 2 No. 1 (2024): January - April 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v2i1.119

Abstract

The objective of this study is to create a technology-driven application prototype, named "Bayadome Geotours," as a cutting-edge solution to enhance geotourism governance and environmental conservation in the Bayah Dome Geopark, Banten. This research advances the utilisation of information and geospatial technology to improve visitor experiences and bolster local community involvement. It achieves this through an emphasis on needs analysis, prototype design, implementation, and testing. The Bayadome Geotours prototype is specifically engineered to offer a dynamic and engaging tourism encounter. Geospatial navigation capabilities enable users to digitally explore geosites, while an intuitive user interface assures accessibility for visitors with different levels of knowledge. This programme offers precise and comprehensive geological information, providing a novel method to enhance comprehension of the geological resources found in the Bayah Dome Geopark. Bayadome Geotours is a good example of the value of local community involvement in geotourism administration. This application serves as both a travel guide and a venue for the exchange of knowledge, local narratives, and cultural heritage. Engaging the public in sharing information fosters a stronger connection between tourists and the environment, resulting in a beneficial influence on the preservation of geosites and the overall management of destinations. Prototype testing conducted using a unit testing methodology demonstrates the successful execution of all system functionalities. The JEST tool's test results confirm that the Bayadome Geotours application is prepared for distribution to the general user base. Nevertheless, there are obstacles in the way of effectively managing and modernising the application, as well as achieving general acceptance, that must be addressed in order to guarantee the ongoing triumph of this prototype. However, Bayadome Geotours has created significant opportunities for advancing sustainable geotourism governance.
DSS Decision Support System for Best Employee Evaluation Using the SMART Algorithm. Handayani, Dwipa; Rasim, Rasim
International Journal of Information Technology and Computer Science Applications Vol. 2 No. 3 (2024): September - December 2024
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v2i3.167

Abstract

The use of information technology has permeated all areas, including employee performance evaluation, which plays a crucial role in company management. The success of a company is largely dependent on human resources, which are considered valuable assets due to their strong link to employee performance. This study focuses on the application of the SMART Algorithm in a Decision Support System designed for the evaluation of the best employees at PT Raharja Jaya Mandiri Bekasi. The main objectives of the study are to develop an employee evaluation system, apply the SMART Algorithm to make the evaluation process more objective, and improve the security and reliability of evaluation data through a digital system. The research employs the SMART Algorithm to evaluate and select the best option based on predetermined goals and criteria. This approach is implemented using the waterfall model of system development. The results of the study indicate that the implementation of a web-based Decision Support System utilizing the SMART Algorithm enhances the accuracy and efficiency of employee performance evaluations at PT Raharja Jaya Mandiri Bekasi. Moreover, it reduces subjective bias in the decision-making process and ensures that the best employees are chosen based on measurable and transparent criteria.
Co-Authors Abrar Hiswara Achmad Noeman Achmad Noeman Achmad Noeman Adi Muhajirin Agus Hidayat Akbar Rafni Rafsan Jani Andy Achmad Hendharsetiawan Ardhiyanto, Ozzi Asep Ramdhani Mahbub Asghor, Ali Asrika, Sukwati Dewi Ayu Diah Rositawati Bayu Pratama Caroline Julyana Magdalena S. Chan, Muhammad Nauval Damara, Rian Dani Yusuf Dani Yusuf Dani Yusuf Deo Pratama Putra Dian Hartanti Dimas Permadi Dwi Budi Srisulistiowati Dwidayanto, Ardiansyah Dwijayanthi Nirmala, Indah Fadhillah, Muhammad Fahmi Fadilah, Fikki Arsyi Nur Fadillah P, Yoga Fathurrazi, Ahmad Fathurrozi, Ahmad Febian, Guruh Putra Fitriyani, Linda Fransisco Leo Sinema Gea Fried Sinlae Ginting, Andre Saputra Ginting, Brian Permana Haikkal, Mochammad Hanif, Farhan Abiyyu Hantoro, Kusdarnowo Hariyanto Hasri, Sutan Keysar Gifari Hendarman Hendarman Hendarman, Hendarman Hendarman Lubis Hendharsetiawan, Andy Achmad Herdiansyah, Dafa ISNAWATI Isyadi, Muhammad Zhidan Jani, Akbar Rafni Rafsan Kapriadi, Engkap Karyaningsih, Dentik Kristian Vieri, Jhon Kurnia, Ferdi Kurniawan, Kelvin Kusnadi, Aldiansyah Kustanto , Prio Kusumah, Muhammad Assegaf Raja Larasati, Gabriella Putri Lestari, Tyastuti Sri Lubis, Hendarman Mahbub, Asep Ramdhani Maulana, Muhammad Ismam Mayadi Mhammadin, Habib Mugiarso Mugiarso, Mugiarso Muhammad Yasir Muhammad Yasir Muhammad Yazid Mukhlis Nafianto, Dwi Noe'man, Achmad Noeman, Achmad Noe’man,, Achmad No’eman, Achmad Nur Afifah Nurfirdaus, Muh. Iqbal Rizky Pamungkas, Arya Panca Priatna , Wowon Prio Pamungkas, R Wisnu Pujiono, Krisna Dimas Rabbani, Nizar Bagoes Rafi, Athala Rahelliana Tinambunan Rahma Vadilla Raihan, Abdul Muhammad Rasim, Rasim Ratna Salkiawati Rawinto, Irsyad Retno Wulandari Retno Wulandari Robertus Suraji RR. Ella Evrita Hestiandari Santi Noviyanti Saputra, Virga Hendra Siti Setiawati Sri Lestari, Tyastuti Sri Marini Tb Ai Munandar Tb Ai Munandar Tb Ai Munandar, Tb Ai Triawati, Hervira Tyastuti Sri Lestari Verdi Ganda Manalu WAHYUDI, DIKI Wicaksono, Ahmad Bayu Widyanto, Abdillah Prayoga Wiwiet Yuliana Putri Yogaswara, Nadhif Zahir, Muhammad Rafli Alta Zebua, Yedija Salomo