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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Edulib JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Penelitian Pendidikan IPA (JPPIPA) Technomedia Journal Astonjadro J-SAKTI (Jurnal Sains Komputer dan Informatika) Building of Informatics, Technology and Science Jurnal Teknik Informatika (JUTIF) J-SAKTI (Jurnal Sains Komputer dan Informatika) Journal Of World Science International Journal Of Science Education and Technology Management (IJSETM) The Indonesian Journal of Computer Science
Christina Juliane, Christina
STEI-Institut Teknologi Bandung
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Physics Social Sciences

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Journal : Building of Informatics, Technology and Science

 1 
User Satisfaction Analysis of Paylater Services Using K-Means Algorithm in Campus Anwar, Syahrul; Hikmawati, Nina Kurnia; Juliane, Christina
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2533

Abstract

In the 4.0-based digital era, the use of e-commerce is increasing. The convenience provided to e-commerce users is increasingly being considered by companies engaged in e-commerce. Paylater is a fairly new payment method among Indonesian e-commerce, so research is needed to improve the service and satisfaction of e-commerce users, especially those using the paylater payment method. The purpose of this study is to analyze user satisfaction with paylater services using the k-means algorithm on campuses in region 3 Cirebon. This research is also to find out the benefits of paylater used by students. This research is a type of quantitative research using the k-means algorithm to determine the classification of paylater user satisfaction in several e-commerce applications at several universities in region 3 Cirebon which is then clustered. The results of the study show that Cirebon students in the Campus 3 area are satisfied with services from companies or online shops that have paylater payment facilities
Analisis Algoritma K-Means dan Davies Bouldin Index dalam Mencari Cluster Terbaik Kasus Perceraian di Kabupaten Kuningan Sopyan, Yayan; Lesmana, Agrian Dwi; Juliane, Christina
Building of Informatics, Technology and Science (BITS) Vol 4 No 3 (2022): December 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i3.2697

Abstract

In marriage, the thing that is most avoided is a divorce. Divorce is the termination of the husband and wife relationship which is carried out legally at the time of trial. From year to year, there is an increase in the number of divorces in Indonesia, including the number of divorces in Kuningan Regency. This study analyzes divorce cases in villages in Kuningan Regency, the analysis is carried out by using data mining clustering methods using the K-Means algorithm. The clustering method is grouping data based on the same characteristics. In determining the number of clusters by using the value of the smallest Davies Bouldin Index, it is hoped that the number of clusters formed can be more optimal. The results of this study are that there are 4 clusters consisting of villages or sub-districts with different divorce rates, namely the highest divorce rate, high divorce rate, medium divorce rate, low divorce rate, and lowest divorce rate
Penerapan Forecasting Menggunakan Metode Time Series Untuk Menentukan Proyeksi Sales di Perusahaan Manufacturing Furniture Prasakti, Lukito Angga; Juliane, Christina
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): March 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.2802

Abstract

The large population certainly encourages companies, including manufacturing companies, to continue to develop their production both in terms of quality and quantity, especially since the number of companies with the same focus is quite large. This is because, every certain company wants to get a lot of profit and minimal consumer or customer complaints. One way that is considered to be able to overcome this is by carrying out company policy referring to forecasting product sales in the future. Therefore, researchers want to find out more about the application of forecasting to determine monthly sales projections for the following year at a Furniture Manufacturing Company. The aim is to determine the role of forecasting in making policies on the company's production at a later time by considering sales projections based on the company's forecasting results. The method used is time series by collecting data through documentation at the regular local market in 2022 to be precise 12 months. After the data is collected, it will be analyzed in depth so that it is known from the research results that careful forecasting will produce forecasts that are not far from reality and can help in calculating sales projections for furniture manufacturing companies at a later time, with a MAPE value of 0.06
Market Basket Analysis to Determine Muslim Clothing Supply in Indonesia Ahead of Eid Al-Fitr Indra Gunawan, Gun Gun; Aji, Tri Wahyu; Juliane, Christina
Building of Informatics, Technology and Science (BITS) Vol 6 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i1.5162

Abstract

Enterprise transaction data is a valuable source of insights for companies to increase sales. In preparation for Eid al-Fitr, this study leverages Market Basket Analysis with the FP-Growth algorithm to uncover buying patterns within Indonesia's Muslim clothing market. Market Basket Analysis is one way to explore information through data to find customer buying patterns that are often used as insight into company decision-making. The data processing method uses the FP-Growth algorithm, which generates association rules based on calculating the frequency of occurrence of itemsets. Using the FP-Growth algorithm gives good results in the determination of association rules. From Muslim fashion store transaction data over the last 12 months, it produced 30 item set patterns with a minimum support value of 0.009 and confidence of 0.58. By identifying these in-demand product pairings, businesses can make informed decisions about stock allocation. This ensures they have the right combination of items available to meet customer needs during the surge in demand leading up to Eid al-Fitr. Additionally, these patterns can inform targeted promotional campaigns and strategic bundling initiatives, maximizing sales and customer satisfaction throughout this critical sales period.
Co-Authors AA Sudharmawan, AA Adjani, Kannisa Aji, Tri Wahyu ALAM Alana, Divi Adiffia Freza Alfian, Iqbal Amirulloh, Moch Mumin Anwari, Hidayat Azhar, Rizaldi Bani Riyan, Ade Damayunita, Aina Ernawan Fathah, Adittia Fauzia, Fathia Alisha Fikri Rifai, Mochamad Geo Ginantaka, Prafangasta Hadi Winarto, Hadi Haryanto Haryanto Hermawan, Sari Hikmawati, Nina Kurnia Imron Rosyadi, Iim Indra Gunawan, Gun Gun Irawan Irawan Karsa, Koko Kurniawan, Debby Lesmana, Agrian Dwi Luffi Septian Marlia, Sari Mutia, Acep Sandi NG, Wijaya Nugraha, Anwar Nurhadits, Fitri Nurwijayanti Pascalina, Donna Prasakti, Lukito Angga Pratama, Denni Purwandi Putra, Rendri Ridian Gusdiana Rifqi Syamsul Fuadi Saepulloh, Yusep Setiawan, Kiki SRI RAHAYU Sudartha, Doddi Sukma, Robby Surahman, Adi Syakur, Achmad Teguh Aljauza Widhiastono, Raymondhus Yayan Sopyan Yosep Bustomi