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Journal : IJISTECH

K-Means to Determine the e-commerce Sales Model in Indonesia Ririn Restu Aria
IJISTECH (International Journal of Information System and Technology) Vol 3, No 2 (2020): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i2.47

Abstract

Sales of e-commerce in Indonesia are currently experiencing a pretty good increase by starting to switch sales that are done traditionally or offline to online sales using the use of internet media to facilitate trade transactions between sellers and buyers can be done anywhere and anytime. In this study using the K-means clustering method algorithm. The data source used in this study is based on sales using e-commerce based on provinces in Indonesia in 2018. The criteria used in the calculation are divided into 3 clusters, namely seller, reseller and dropship. Centroid data for cluster 1 = 68.30,33,58,4.95 namely Aceh, Riau, West Kalimantan, East Kalimantan, and Maluku. Centroid data for cluster 2 = 78.58,22,25.4,22 i.e. North Sumatra, West Sumatra, Jambi, Bangka Belitung Islands, D.K.I Jakarta, Central Java, East Java, Banten, Bali, Central Kalimantan, South Kalimantan, South Sulawesi and Papua  and Centroid data for cluster 3 = 86.36,13.34,4.38 namely South Sumatra, Bengkulu, Lampung, Riau Islands, West Java, D.I Jogyakarta, West Nusa Tenggara, East Nusa Tenggara, North Kalimantan, Central Sulawesi, Gorontalo, West Sulawesi, North Maluku and West Papua.
Design Warehouse Management Inventory System Based On The Website Ririn Restu Aria; Indra Riyana Rahadjeng
IJISTECH (International Journal of Information System and Technology) Vol 1, No 2 (2018): May
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v1i2.8

Abstract

Warehouse management system is one of the most important parts of manufacturing companies in order to monitor all the supplies owned by the company for incoming goods and goods out. PT. Arista Latindo, is still using manual way to know the inventory they have today, so it will take a lot of time to be able to process the results of the use of raw materials, the resulting production, when using the system there are many mistakes that often occur in the process of recording thus affecting the overall system. Therefore, with technological advances to improve the existing system from the manual will be converted into computerized. For making these applications can use the website as a form of view that can be accessed by administrators more easily, quickly and effectively. When the design is done to better understand the needs of the user, the process is done and the output to be used, the testing process is done by waterfall method and black box testing method to check the errors associated with the display in applications that have been made and will be used in the company.
Classification of Generation By Population by Region in Indonesia Using K-Means Algorithm Ririn Restu Aria; Susi Susilowati
IJISTECH (International Journal of Information System and Technology) Vol 5, No 4 (2021): December
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i4.160

Abstract

Population growth caused by the year of birth led to the classification of population groups into several generations. Classification is important because in each generation there is based on population growth has different characteristics and traits in each generation. This research was conducted to try to group generations based on provinces in Indonesia based on the number of residents owned. When researchers analyzed the data obtained from population census data conducted by the central statistics agency (BPS). The method used in generation classification grouping uses the K-Means algorithm method based on 3 clusters. Based on the results of calculations carried out for 3 clusters obtained cluster 1 has 25 provinces, cluster 2 has 3 provinces and cluster 3 has 6 provinces. Based on the 2020 census that has been conducted, the current population is generation Z, generation and Pre Boomer generation is last in line so that from the available data can provide information about mapping in 34 provinces to be able to improve communication patterns between generations and fulfill public facilities that can be used every generation
Implementation of the K-Medoids Algorithm for Data Clustering of Covid 19 Cases in West Java Ririn Restu Aria
IJISTECH (International Journal of Information System and Technology) Vol 5, No 1 (2021): June
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v5i1.109

Abstract

The Covid 19 pandemic has hit Indonesia for almost 15 months since March 2020. The virus has spread to all provinces in Indonesia. Various efforts were made to be able to reduce or prevent the spread of the coronavirus, including the implementation of the PSBB in various areas including in West Java province. In this study, the objective of this research is to cluster the data on cases of Covid 19 in West Java which are recapitulated daily based on districts/cities that occurred on May 20, 2021. For the clustering process, the K-medoids algorithm is used which determines 3 clusters based on the variables used, namely discarded close contact, suspects discarded, probable completed, probable died, totally positive, positive recovered, and positive died. For data processing, a calculation analysis was carried out using the stages in the K-medoids algorithm and the Rapidminer application with high cluster mapping of 6 districts/cities, medium clusters there were 19 districts/cities, while low clusters had 2 districts/cities. The results of the analysis are expected to provide information about the distribution and mapping of clusters in West Java province.  
Application of Economic Order Quantity and Reorder Point Methods in Improving the Efficiency of Coffee Raw Material Supply (Case Study At PT. Herbal Salam) Susi Susilowati; Ririn Restu Aria
IJISTECH (International Journal of Information System and Technology) Vol 6, No 1 (2022): June
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v6i1.213

Abstract

The food industry sector is currently getting tighter competition, especially in the form of food in the form of herbal drinks in the form of powders and liquids. That way it is necessary to control the supply of the right raw materials for the smooth production process. The purpose of this study is to find out and analyze the control of coffee raw material supplies applied by PT. Herbal Salam. So that it can improve the efficiency of raw material supply and can improve the performance of raw material management at PT. Herbal Salam.  The research methods used are the EOQ and ROP methods. Research results show that the company's raw material inventory has not been optimal and has not shown a minimum inventory cost. Based on analysis and policy calculations the company produces a total inventory of 72.000 per Kg in a year with an average purchase of 30 times a year, while the Economic Order Quantity (EOQ) method produces a total inventory of 5.280 per kg in a year with an average purchase of at least 14 times a year. This indicates that the EOQ method is smaller or there are savings of more than 50% compared to the company's policies.
Classification of Domestic Flight Passengers at Main Airports Using the K-Means Clustering Method Syaoqiyah, Syifa Siti; Anisa, A; Selvina, Yudhi Yulianti Selvina; Rahmadenti, Nadhia Ayu; Aria, Ririn Restu
IJISTECH (International Journal of Information System and Technology) Vol 8, No 1 (2024): The June edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i1.340

Abstract

The aviation business in Indonesia has recently experienced quite significant growth, which can be seen from the fact that many people tend to choose air transportation to travel and connect them to cities in Indonesia. With air transportation, the time spent traveling to one area or city can be reduced. accomplished in a short time. This causes the number of passengers per flight to be quite high, especially in domestic flights which occur at the main airport. This research will use the K-Means Clustering algorithm to find out the schedule for the busiest month for the highest domestic airlines at major airports. The data source for this research comes from the central statistics agency regarding the number of domestic airline passengers at major airports. The criteria used in this research are divided into 3 clusters, namely high, medium, and low. The results of this research show that the highest number of passengers (C1) occurs in January to April, while the moderate number of passengers (C2) occurs in May to December, and the lowest number of passengers (C3) occurs in August to November.