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Implementation of Scrum Method in ERP-Based Employee Performance Evaluation System Chandra, Darren Denisson; Tobing, Fenina Adline Twince; Kusnadi, Adhi; Nainggolan, Rena; Hassolthine, Cian Ramadhona
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp201-209

Human capital is a key factor in realizing an organization’s vision and mission. To ensure optimal performance, employee output must be evaluated consistently through a well-organized appraisal process. Although PT Kompas Media Nusantara has adopted such evaluations, they are still carried out using traditional methods, such as distributing physical documents. To address these inefficiencies, an ERP-based Employee Performance Evaluation System has been designed to streamline workflows, enhance accessibility, and support a more standardized and systematic assessment process. This system utilizes Key Performance Indicators (KPIs) aligned with individual job responsibilities to measure performance. The development process adopts the Scrum methodology, while system validation is carried out through Black Box Testing. The test results reveal that the system performs reliably, achieving a 100% accuracy rate in matching inputs and expected outputs. To assess user satisfaction, the End User Computing Satisfaction (EUCS) framework combined with a Likert scale was employed. The evaluation produced high satisfaction scores across various dimensions: content (89.12%), accuracy (87.02%), layout and design (88.07%), user-friendliness (89.12%), and timeliness (86.84%). These findings indicate strong user acceptance of the ERP-based system, reinforced by consistently positive user feedback regarding its effectiveness and ease of use

E-Commerce Product Review Sentiment Analysis: A Comparative Study of Naïve Bayes Classifier and Random Forest Algorithms on Marketplace Platforms Hassolthine, Cian Ramadhona; Haryanto, Toto; Adline Twince Tobing, Fenina; Ikhwani Saputra, Muhammad
IJNMT (International Journal of New Media Technology) Vol 12 No 1 (2025): Vol 12 No 1 (2025): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v12i1.4246

Achieving customer satisfaction and trust is a major challenge for success in the business world. Entrepreneurs must identify problems that arise from reviews given by customers. However, reading and sorting each review is time-consuming and considered inefficient. In order to overcome this, a study was conducted that aims to analyze sentiment on products sold in the Shopee marketplace using the Naïve Bayes Classifier and Random Forest algorithms. The focus of this study is on product reviews from XYZ Store. The main objective of this study is to determine a more accurate and efficient algorithm in classifying review sentiment, which can help companies in marketing strategies and product development. The results of this study can provide insight for companies about consumer responses to marketed products, so that they can be used as a basis for making strategic decisions to improve the quality of services and products. The results of the Random Forest method classification produce superior predictions compared to the Naïve Bayes Classifier method with an accuracy value of 92.5%, precision of 93%, Recall of 92.5% and F1-Score of 90%.

Pendekatan Sistem Pendukung Keputusan dalam menentukan Komisi Sales Dengan Metode FUZZY SAW (Simple Additive Weighting) di PT. Normal Global Indonesia Nugroho, Catur; Abdullah, Syahid; Ramadhona Hassolthine, Cian
Jurnal Ilmu Siber (JIS) Vol 1 No 4 (2022): JIS
Publisher : LPPM, Universitas Siber Asia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Sistem komisi penjualan merupakan hal diperlukan dalam suatu organisasi dalam memperlancar proses bisnis, mengunakan sistem komisi penjualan akan diperoleh hasil yang tepat dalam pengelolan datanya, pengunaan SPK dapat membantu menangani keraguaan dalam pengambilan suatu keputusan. Untuk itu perlu dikembangan dengan pengunaan SPK dan metode yang tepat untuk dipilih salah dalam pengembangan SPK ini dengan Fuzzy SAW (Simple Additive Weighting) yang dapat digunakan dalam penentuan nilai bobot yang dimiliki oleh kriteria yang sudah ditentukan, proses selanjutnya membuat pemeringkatan dengan hasil untuk mendapatkan alternatif terbaik beberapa alternatif. Perusahaan Normal Global Indonesia memiliki karyawan penjualan yang akan memperoleh komisi jika target penjualan tercapai, untuk pengelolaanya di tangani oleh manajemen yang dinilai kurang efisienya dalam menghitung komisi, serta sering terdapat masalah dalam perhitungan, sehingga dirasakan perlunya untuk membuat sistem yang akan memberikan hasil untuk dapat menentukan komisi berdasarkan peringkat dengan berdasarkan hasil penjualan, penelitian ini dibuat dengan menerapakan metode Fuzzy untuk memudahkan pengunaanya mengunakan dengan efektif dan berdasarkan perhitungan penjualan yang tepat bagi karyawan bagian penjualan, hasil nilai berdasarkan perangkingan didapat terbesar ada pada A1 dan A4.

Implementation of Scrum Method in ERP-Based Employee Performance Evaluation System Chandra, Darren Denisson; Tobing, Fenina Adline Twince; Kusnadi, Adhi; Nainggolan, Rena; Hassolthine, Cian Ramadhona
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp201-209

Human capital is a key factor in realizing an organization’s vision and mission. To ensure optimal performance, employee output must be evaluated consistently through a well-organized appraisal process. Although PT Kompas Media Nusantara has adopted such evaluations, they are still carried out using traditional methods, such as distributing physical documents. To address these inefficiencies, an ERP-based Employee Performance Evaluation System has been designed to streamline workflows, enhance accessibility, and support a more standardized and systematic assessment process. This system utilizes Key Performance Indicators (KPIs) aligned with individual job responsibilities to measure performance. The development process adopts the Scrum methodology, while system validation is carried out through Black Box Testing. The test results reveal that the system performs reliably, achieving a 100% accuracy rate in matching inputs and expected outputs. To assess user satisfaction, the End User Computing Satisfaction (EUCS) framework combined with a Likert scale was employed. The evaluation produced high satisfaction scores across various dimensions: content (89.12%), accuracy (87.02%), layout and design (88.07%), user-friendliness (89.12%), and timeliness (86.84%). These findings indicate strong user acceptance of the ERP-based system, reinforced by consistently positive user feedback regarding its effectiveness and ease of use

Prediksi Harga Steel Hot-Rolled Dengan Model Recurement Neural Network Teguh Yuhono; Cian Ramadhona Hassolthine; Riad Sahara
JEKIN - Jurnal Teknik Informatika Vol. 4 No. 1 (2024)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jekin.v4i1.634

Steel Hot-rolled Coil atau yang biasa disebut dengan sebutan Baja Canai Panas merupakan sebuah produk baja yang dihasilkan dengan proses penggulungan di dalam suhu yang sangat tinggi. Sebagai bahan baku utama dunia yang sering dipakai dalam pembuatan konstruksi bangunan, jembatan, rel kereta api, dan keperluan otomotif sehingga harga Steel Hot-rolled Coil sangat fluktuatif dan sering kali membuat perencanaan pembelian menjadi tidak efektif. Oleh karena itu, diusulkan sebuah metode prediksi harga Steel Hot-rolled Coil dengan mempelajari pola dan tingkah laku pada data time series harga yang sudah lampau. Metode yang direkomendasikan pada penelitian ini yaitu prediksi harga Steel Hot-rolled Coil dengan menggunakan salah satu arsitektur Artificial Neural Network (ANN) yaitu Recurrent Neural Network (RNN). Dengan semakin optimal model yang dibangun maka semakin tinggi akurasi yang didapatkan. Parameter RNN yang optimal dapat diperoleh dengan algoritma optimasi RMSProp (Root Mean Square Propagation). Dari proses pelatihan dan pengujian, didapatkan akurasi terbaik sebesar 90.90% pada data latih dan 91.02% pada data uji.

KLASIFIKASI PRESTASI AKADEMIK PESERTA DIDIK DENGAN METODE MACHINE LEARNING DI SMP X Fandi Chriswantoro Putro; Ahmad Chusyairi; Cian Ramadhona Hassolthine
Jurnal Teknologi Informasi dan Komputer Vol. 11 No. 1 (2025): JUTIK : Jurnal Teknologi Informasi dan Komputer, Edisi April 2025
Publisher : LPPM Universitas Dhyana Pura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36002/jutik.v11i1.3751

Machine learning (ML) is a field of science that focuses on designing and developing algorithmic models to create behavior based on available data. Academic achievement is a metric used for the assessment of quality educational institutions. By using academic data of students in SMP X and machine learning classification algorithms such as Random Forest, NaÃ¯ve Bayes, k-Nearest Neighbors (k-NN), and Support Vector Machine (SVM), so that this research can classify the academic achievement of students in SMP X optimally seen from the comparison of the best accuracy rate among classification algorithms. The accuracy of an algorithm is a measure of how precisely it classifies a sample. Evaluation results are compared in the form of validation accuracy and standard deviation. The comparison is done to determine the best algorithm based on accuracy and stability. The results showed that the SVM algorithm has the highest validation accuracy with a value of 0.987410 which shows the best performance in predicting classes and the lowest standard deviation value of 0.005132 which shows a more stable and consistent performance, compared to other algorithms. This indicates that SVM excels in predicting the correct class with stable performance. Based on the results and analysis, it is concluded that the selected SVM algorithm is used to develop a classification model of students' academic achievement in the form of a python program that is still simple but has high accuracy, stable and consistent. This program has become a tool for SMP X in identifying students' academic achievement and as a material for reporting students' learning outcomes to parents.

Implementation of Gamification Method and Fisher-Yates Shuffle Algorithm for Design and Development Django Learning Application Kiswara, Ade; Tobing, Fenina Adline Twince; Hassolthine, Cian Ramadhona; Saputra, Muhammad Ikhwani
ULTIMATICS Vol 16 No 2 (2024): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v16i2.3874

The web framework emerges as a solution to enhance web development efficiency. Django, an open-source web framework written in the Python programming language, is one of the popular frameworks. Currently, there are not many programming learning platforms that provide specific programming learning materials for Django, implementing a method to boost user interest in using the platform. This research aims to design and build a web-based Django learning application using gamification methods designed based on the octalysis framework to enhance user learning interest. It also incorporates the Fisher-Yates shuffle algorithm to randomize questions for more variety. The application was tested by several users by filling out a questionnaire prepared using the Hedonic Motivation System Adoption Model (HMSAM). The evaluation results of the application obtained an average percentage of 84,15% in the aspect of behavioral intention to use, which means users strongly agree that the djangoing application generates a desire to use it again in the future. Furthermore, the results in the aspect of immersion were 81,44%, which means users agree that the djangoing application creates an immersive learning experience for the Django framework.

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