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All Journal Research Report - Engineering Science JOIV : International Journal on Informatics Visualization Jurnal Pendidikan Informatika dan Sains IICS JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Cecilia Esti Nugraheni
Jurusan Matematika, Fakultas Teknologi Informasi Dan Sains Universitas Katolik Parahyangan, Bandung
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Physics

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Perangkat Lunak untuk Penghitungan Manfaat Program Pensiun Normal di Unpar Farah Kristiani; Cecilia Esti Nugraheni
Research Report - Engineering Science Vol. 2 (2009)
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (896.461 KB)

Abstract

Tidak sedikit dosen dan karyawan Unpar saat ini masih mengalami kesulitanuntuk mengetahui perkiraan besaran tunjangan pensiun yang akanmereka terima pada saat mereka memasuki usia pensiun. Hal ini disebabkankurangnya pengetahuan mereka tentang aturan yang mengatur besarannyadan juga karena perhitungannya cenderung rumit. Beberapa unsur yangmempengaruhinya antara lain adalah asumsi suku bunga, kenaikan gaji secaraberkala dan kenaikan pangkat. Orientasi waktu yang berubah-ubah antaramasa lalu, masa sekarang dan masa yang akan datang juga mempengaruhinilai uang.Selain itu juga beberapa karyawan terkadang tidak bisa melakukan perencanaandengan baik terkait dengan kondisi keuangannya. Berdasarkan permasalahan-permasalahan di atas, maka dibutuhkanlah bantuan yang berupakonsultasi yang didukung dengan perangkat lunak yang dapat digunakan untukmenghitung perkiraan besarnya tunjangan pensiunnya, dan dapat jugadigunakan untuk membuat perencanaan yang lebih baik terkait dengan alokasidananya.Dilihat dari studi kasusnya, diperoleh perbedaan antara hasil perhitungandengan perangkat lunak yang sudah dibuat dengan hasil real dari datayang diperoleh di Biro Kepegawaian bagi beberapa contoh kasus karyawanyang telah pensiun. Karena masih terdapat adanya error, maka hasil besaranmanfaat pensiunnya disajikan dalam bentuk interval besarannya.Kata kunci : Manfaat, pensiun, perencanaan keuangan
PRE-UNIVERSITY COURSES IN COMPUTER SCIENCE FOR HIGHSCHOOL STUDENTS Joana Helga; Chandra Wijaya; Cecilia Esti Nugraheni
Research Report - Engineering Science Vol. 2 (2014)
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (315.212 KB)

Abstract

Fenomena yang kami amati pada mahasiswa baru, sebagian dari mereka tidak sepenuhnya memahami apa yang akan dipelajari di Jurusan Teknik Informatika. Hal ini disebabkan tidak adanya kurikulum informatika yang baku di jenjang SMA. Seringkali sekolah kesulitan dalam menentukan materi dan mencari pengajar yang berkompetensi di bidang ini. Hal ini juga menyebabkan siswa-siswa Indonesia kurang berprestasi dalam kompetisi-kompetisi informatika. Menyikapi fenomena ini, kami mengusulkan sebuah program pra-kuliah dengan dua topik informatika. Program ini bertujuan mengenalkan informatika pada siswa-siswa SMA. Topik pertama bertujuan khusus untuk membekali siswa yang ingin bertanding di kompetisi pemrograman, sedangkan topik kedua bertujuan khusus untuk membekali siswadengan pengetahuan dasar tentang perangkat keras dan jaringan komputer. Kegiatan pra-kuliah diperuntukan bagi siswa SMA kelas X dan XI, dan diadakan sepanjang semester dengan bertempat dikampus UNPAR.  
Customer Segmentation: Transformation from Data to Marketing Strategy Luciana Abednego; Cecilia Esti Nugraheni; Adelia Salsabina
IAIC International Conference Series Vol. 4 No. 1 (2023): SEMNASTIK 2023
Publisher : IAIC Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/conferenceseries.v4i1.645

Abstract

Customer segmentation plays a crucial role in modern business strategies, enabling organizations to effectively target and personalize their marketing efforts and enhance customer relationships. Clustering algorithms have emerged as a powerful tool for segmenting customers based on their similarities and differences. We complement the data with an RFM model to support the clustering results. RFM, which stands for Recency, Frequency, and Monetary, is a model for segmenting customers based on their historical transaction data. This study aims to explore the concept of customer segmentation and the application of the RFM model combined with clustering algorithms in the real customer dataset of a company. It presents an overview of datasets, and introduces the RFM model and its components, emphasizing the significance of recency (how recently a customer made a purchase), frequency (how often a customer makes a purchase), and monetary value (the amount spent by a customer). It highlights the practicality of the RFM model in quantifying customer behavior and categorizing customers into distinct segments. It also explains popular clustering algorithms, analyzes experimental results, and concludes with future remarks on the potential of customer segmentation. We combine unsupervised (K-Means and DBSCAN clustering) and supervised machine learning methods to build customer clusters, label each cluster based on its characteristics, and propose a strategy for each cluster.
Aplikasi Pengelolaan Persediaan Bahan Pada Usaha Kecil Menengah Pakaian Jadi Antonius Susanto; Cecilia Esti Nugraheni; Maria Widyarini
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 3 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i3.4125

Abstract

Clothing is one of the basic or primary needs. With the influence of clothing fashion that continues to grow, many Small and Medium Enterprises (SMEs) have sprung up engaged in the clothing sector. SMEs are one of the driving forces of the Indonesian economy. SMEs engaged in the clothing sector are businesses that produce apparel. The materials used in the manufacture of clothing also vary, so that inventory management and material requirements planning are essential processes in the manufacture of clothing. In this study, a simple mobile application was developed that can be used for material inventory management for SMEs. The primary function of this application is to record materials (inventory) and plan production needs using the Reorder Point (ROP) method. The Reorder Point (ROP) method is an order limit point helpful in knowing when a company holds an order. Program development using Android Studio IDE with Flutter framework and Dart programminglanguage. The results of functional testing on this application are 90% achieved following the expected results. The user acceptance test concludes that this application has the potential to facilitate SMEs in managing the inventory of material.
The impact of computational modeling on student success in algorithm and programming track courses Hakim, Husnul; Natalia, Natalia; Nugraheni, Cecilia Esti
Jurnal Pendidikan Informatika dan Sains Vol. 14 No. 1 (2025): Jurnal Pendidikan Informatika dan Sains
Publisher : IKIP PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v14i1.8875

Abstract

Programming courses, such as Object-Oriented Programming (PBO), Algorithms and Data Structures (ASD), and Design and Analysis of Algorithms (DAA) at Parahyangan Catholic University's Informatics Study Program (IF UNPAR), have shown relatively low passing rates and average grades. To enhance students' problem-solving abilities, IF UNPAR's 2018 Curriculum introduced the compulsory course, Modeling for Computation (PUK). This study aims to analyze the influence of PUK grades on students' academic performance in programming courses. We used linear regression modeling and Naïve Bayes classification to predict student grades. The results show that the regression model yielded a residual standard error between 15.43 and 28.15, while the Naïve Bayes model achieved a Root Mean Squared Error (RMSE) between 1.29 and 1.85. These findings indicate that PUK grades can serve as an early indicator of student success in programming courses, simultaneously supporting the integration of modeling and problem solving capabilities into the informatics curriculum.
A Bee Colony Algorithm based Solver for Flow Shop Scheduling Problem Halim, Yosua; Nugraheni, Cecilia Esti
JOIV : International Journal on Informatics Visualization Vol 5, No 2 (2021)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.2.491

Abstract

Flow Shop Scheduling (FSS) is scheduled to involve n jobs and m machines in the same process sequence, where each machine processes precisely one job in a certain period. In FSS, when a machine is doing work, other machines cannot do the same job simultaneously. The solution to this problem is the job sequence with minimal total processing time.  Many algorithms can be used to determine the order in which the job is performed. In this paper, the algorithm used to solve the flow shop scheduling problem is the bee colony algorithm. The bee colony algorithm is an algorithm that applies the metaheuristic method and performs optimization according to the workings of the bee colony. To measure the performance of this algorithm, we conducted some experiments by using Taillard's Benchmark as problem instances. Based on experiments that have been carried out by changing the existing parameter values, the size of the bee population, the number of iterations, and the limit number of bees can affect the candidate solutions obtained. The limit is a control parameter for a bee when looking for new food sources. The more the number of bees, the more iterations, and the limit used, the better the final time of the sequence of work. The bee colony algorithm can reach the upper limit of the Taillard case in some cases in the number of machines 5 and 20 jobs. The more the number of machines and jobs to optimize, the worse the total processing time.
Co-Authors Adelia Salsabina Antonius Susanto Antonius Susanto Chandra Wijaya Farah Kristiani hakim, husnul Halim, Yosua Joana Helga Luciana Abednego Natalia Natalia