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CLASSIFICATION OF MYPERTAMINA APP REVIEWS USING SUPPORT VECTOR MACHINE Fadlurohman, Alwan; Yunanita, Novia; Rohim, Febrian Hikmah Nur; Wardani, Amelia Kusuma; Ningrum, Ariska Fitriyana
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page223-228

Abstract

Indonesia is rich in natural resources, including oil and gas, and it manages these strategic assets through state-owned enterprises, one of which is PT Pertamina. Pertamina is responsible for domestic fuel production, distribution, and price stabilization. To improve efficiency and transparency, Pertamina developed the MyPertamina application that enables cashless fuel purchases, stock monitoring, and up-to-date price information. The application aims to streamline distribution and control fuel prices, thus helping to stabilize the cost of goods and services. MyPertamina also ensures subsidized fuel distribution is more effective and targeted by identifying and verifying subsidy recipients, reducing the potential for abuse. A sentimental analysis of subsidized fuel user reviews using this application is needed to understand the public's views. This research uses the Support Vector Machine (SVM) method to analyze the sentiment of MyPertamina app reviews. This research produced a stable model. Out of 200 reviews, 190 were negative, and nine were positive, with an SVM model accuracy of 97%. Wordcloud visualization shows the words that appear frequently in each sentiment. Positive reviews appreciated the photo verification feature, easy payment, and good service. Negative reviews included verification difficulty, app error, and feature failure.
Implementation of Back Tracking Algorithm in The Scheduling of Mathematics Study Program Faculty of MIPA Unsoed Amariesta, Tiara; Wardani, Amelia Kusuma; Adila, Raisa Naura; Nurshiami, Siti Rahmah
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.129

Abstract

The complicated case of scheduling courses at the Mathematics and Natural Sciences Faculty of Mathematics Study Program, Universitas Jenderal Soedirman, is a topic that is quite interesting to discuss and find a solution to using a mathematical method. In fact, manual course scheduling without a method is prone to scheduling errors such as class schedule clashes, clashes in the use of lecture rooms and so on, so a more efficient method of scheduling courses is needed. Scheduling lectures with the backtracking algorithm is a systematic and efficient method of scheduling lectures with influencing factors such as the number of courses, number of sessions, number of rooms, and lecture time. Algorithm backtracking is an algorithm based on Depth First Search to find solutions to problems more efficiently. The back tracking algorithm performs a systematic search for solutions to all possible solutions at each node based on recursive Depth First Search. Depth First Search is a search method that is carried out at one node in each level from the far left. If a solution has not been found, then the search continues on the right hand node. And so on until a solution is found or if you find a dead end it will backtrack to the previous position. If a solution is found, the search will stop even if there are nodes that have not been traced. The implementation of the backtracking algorithm pays close attention to the factors that become obstacles in scheduling courses. The course schedule function with the backtracking algorithm can meet every influencing factor such as the number of courses, rooms, classes, and lecture time so that scheduling lectures with this method is very helpful because the method used is more efficient and can avoid errors in scheduling.
Data Visualization Excellence: Google Data Studio Workshop At Sekolah Indonesia Kuala Lumpur Amri, Saeful; Fadlurohman , Alwan; Ningrum, Ariska Fitriyana; Purwanto, Dannu; Amri , Ihsan Fathoni; Wardani, Amelia Kusuma; Dhani, Oktaviana Rahma
Journal Of Human And Education (JAHE) Vol. 5 No. 1 (2025): Journal of Human And Education (JAHE)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jh.v5i1.2178

Abstract

The development of information technology and the entry of the industrial revolution 4.0 era has led to the inseparability of human activities related to the use of technology. In today's rapidly growing information age, data is one of the most valuable assets. The ability to collect, analyze, and interpret data is becoming a very important skill not only in the world of work but also in education. Education is the foundation for preparing future generations for increasingly complex global challenges, and a good understanding of data can provide a significant competitive advantage. In schools, the ability to analyze and interpret data is becoming an invaluable skill for students. Along with the development of technology, data visualization has become an effective method to convey information in a more comprehensible manner. In this context, Google Data Studio offers a powerful and easy-to-use tool for creating interactive dashboards that help in analyzing and presenting data. Indonesian Migrant Workers (TKI) are Indonesian citizens who live and work abroad. TKI provide a large contribution of foreign exchange to the country of Indonesia. However, there are problems in the field of education for children whose parents work as TKI in Malaysia, especially education that is relevant to success in terms of opening their own jobs abroad. This is considered important because to get jobs in government agencies or companies in Malaysia, the children of TKI working in Malaysia must compete with job seekers who are Malaysian citizens. One alternative that can be taken to overcome competition in getting jobs is to create your own jobs. Opening your own jobs is not an easy thing. Knowledge and insight about this are needed which are given early on to the children of TKI in school. By teaching Google Data Studio in the form of data visualization to students, they not only learn how to read and interpret graphs and diagrams, but also how to present their own data in a more interesting and informative way. This ability will be very useful in the future, both in academic and professional environments. By providing insight into Google Data Studio to students in schools, these students have the provisions to be able to read data and have the opportunity to work and get decent jobs. As a Community Service activity with an international scope, this activity takes partners in Malaysia, namely the Indonesian School-Kuala Lumpur - SIKL which is located in Sentul, Kuala Lumpur, Federal Territory of Kuala Lumpur. The Community Service Team of Muhammadiyah University of Semarang is very receptive to criticism and suggestions so that the implementation of Community Service in the future can be even better.