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All Journal JOIV : International Journal on Informatics Visualization Jurnal Informatika Universitas Pamulang Journal of Information System, Applied, Management, Accounting and Research MULTINETICS JISA (Jurnal Informatika dan Sains) Lensa
Henny Yulianti
Universitas Siber Asia, Jakarta
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Rancang Bangun Sistem Informasi Pengorderan Air Minum RO dengan Metode Waterfall Integrasi UML di PT Gajah Tunggal Tbk Yulianti, Henny
Jurnal Informatika Universitas Pamulang Vol 6, No 3 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v6i3.11780

Abstract

The increasingly high level of competition in the tire industry encourages companies to manage their human resources well. Human resources are the company's main asset which is an important element in achieving company goals and maintaining company sustainability. Every employee is an important factor that drives a high-performing compan, therefore the company strives to provide facilities for all its employees. The facilities provided by PT. Gajah Tunggal Tbk is healthy drinking water for all its employees. The problem is the process of ordering healthy drinking water is still manual, each division goes to the RO section to order drinking water and reports often do not match the needs in the field. This makes the division lose a lot of time and effort. Because of this, with the development of information technology, the solution is to build a web-based RO drinking water ordering application system. The website design method uses the Waterfall method which is integrated with the UML software development method. With Black box testing, it is proven that the design of this RO drinking water ordering application can help the activities of employees in the company in meeting the needs of drinking water and accurate reports so that it becomes effective and efficient. in the working time of employees and this can improve the performance of employees of PT. Gajah Tunggal Tbk
The Design of a Monitoring Application System for The Production of Foam Products Using the UML And Waterfall Methods Henny Yulianti; Gatot Tri Pranoto
JISA(Jurnal Informatika dan Sains) Vol 4, No 2 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i2.1045

Abstract

The development of information technology, which is followed by a higher level of competition in the foam product industry, encouraging companies to manage their company's resources properly and to plan effective, systematic and mature activities within the company. As a company with a variety of products, the most dominant problem is in the productivity process. Production is the most important part of a manufacturing company, where in carrying out its production activities this company produces based on orders from customers (Job Orders). And the problems that often occur are planning revisions in the midst of production and changing production schedules between groups (lines), delays in production planning in terms of prioritizing planning, and still being done manually in making daily reports. By implementing monitoring, which is the supervision and control of an activity where measurements and evaluations are completed repeatedly from time to time, monitoring is carried out for the purposes of the company and to maintain ongoing management. Monitoring will provide information about the status and trend of production activities towards the company's goals. The solution to this production problem is to build a web-based foam product production monitoring system application using the Waterfall method which is integrated with UML the method used is use case diagrams, activity diagrams, sequence diagrams, class diagrams and component diagrams and software development with PHP and MySQL technology. With Black box testing, it is proven that the design of this foam production monitoring system application can assist the company's foam product production activities in fulfilling customer orders and accurate reports so that it becomes effective and efficient. in improving the productivity and performance of the company.
COMPARISON OF NAIVE BAYES ALGORITHM AND DECITION TREE FOR EMPLOYEE CLASSIFICATION PREDICTIONS TENDING TO CHANGE WORK Henny Yulianti
Jurnal Informatika Universitas Pamulang Vol 7, No 3 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v7i3.20777

Abstract

In recent years due to the uncertain economic conditions and situation of a country, many employees with a certain level of education, work experience, countries with different levels of development and income per capita of the country and several other factors, causing many employees tend to change places of work. Due to the various factors that cause employees to change jobs and advances in information technology, it is also difficult to predict what factors influence employee decision making to move to a new place. Therefore, it is necessary to know what factors and conditions are in employees so that they have a tendency to change jobs, this is necessary so that companies can prevent, anticipate and immediately find other solutions as early as possible if this condition should occur to their employees. Based on the problems and objectives that have been described, this study predicts the classification of employees who have a tendency to change workplaces by integrating the Naive Bayes algorithm and Decision Tree. The aim is to identify the dominant factors that influence employees to change places of work. From the results of the research conducted, it was found that there are three (3) dominant factors that influence employees to change jobs, namely employees with STEM (Science Technology Engineering Mathematical) expertise, company size and education level as well as the highest level of accuracy from the Naive Bayes Algorithm 80.79 and the highest AUC from the Decision Tree Algorithm. 0.822.
Sistem Informasi Administrasi Keuangan Berbasis Web Di Madrasah Tsanawiah Nurul Yaqin Henny Yulianti
Lensa Vol 15 No 1 (2021)
Publisher : LPPM Universitas Pramita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58872/lensa.v15i1.1

Abstract

Teknologi informasi juga mampu melakukan efisiensi di berbagai bidang, terutama bidang pendidikan. Sekolah adalah suatu aktifitas besar yang di dalamnya ada empat komponen yang saling berkaitan yaitu staf tata usaha, staf teknisi pendidikan, komite, dan peserta didik. Selama ini sistem informasi administrasi keuangan di MTs Nurul Yaqin masih menggunakan format penulisan manual. Sehingga timbul permasalahan dalam hal keefektifan dan efisiensi pengolahan data menjadi informasi dalam proses manajemen sekolah. Untuk itu dibutuhkan suatu sistem yang lebih baik dan mampu mengatasi permasalahan karena hal tersebut maka solusinya dibangun aplikasi sistem Informasi ini yang dirancang dengan metode UML dan penelitian dengan metode Waterfall.Terbukti aplikasi ini mampu memudahkan petugas administrator yang ada sehingga pengolahan administrasi keuangan lebih maksimal.
Comparison of Naive Bayes Algorithm and Decition Tree for Employee Classification Predictions Tending to Change Work Henny Yulianti
Jurnal Informatika Universitas Pamulang Vol 7, No 3 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v7i3.20777

Abstract

In recent years due to the uncertain economic conditions and situation of a country, many employees with a certain level of education, work experience, countries with different levels of development and income per capita of the country and several other factors, causing many employees tend to change places of work. Due to the various factors that cause employees to change jobs and advances in information technology, it is also difficult to predict what factors influence employee decision making to move to a new place. Therefore, it is necessary to know what factors and conditions are in employees so that they have a tendency to change jobs, this is necessary so that companies can prevent, anticipate and immediately find other solutions as early as possible if this condition should occur to their employees. Based on the problems and objectives that have been described, this study predicts the classification of employees who have a tendency to change workplaces by integrating the Naive Bayes algorithm and Decision Tree. The aim is to identify the dominant factors that influence employees to change places of work. From the results of the research conducted, it was found that there are three (3) dominant factors that influence employees to change jobs, namely employees with STEM (Science Technology Engineering Mathematical) expertise, company size and education level as well as the highest level of accuracy from the Naive Bayes Algorithm 80.79 and the highest AUC from the Decision Tree Algorithm. 0.822.
Automated Matching Skills to Improve the Accuracy of Job Applicant Selection Using Indonesian National Work Competency Standards Ajhari, Abdul Azzam; Priambodo, Dimas Febriyan; Yulianti, Henny
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2017

Abstract

The high number of cyberattack anomalies and data leaks in Indonesia increases the need for cybersecurity in various companies. Cybersecurity capabilities and skills in Indonesia are divided into three categories based on the Indonesian National Work Competency Standards (SKKNI), namely Security Operation Center (SOC), Cybersecurity test/Penetration testing (Pentest), and Information Security Audit. Although various approaches have been applied in different companies to select job applicants, a new method with automated matching is explored in this study. This method matches the skills possessed by prospective job applicants with the profile of their job task requirements based on the SKKNI Decree of the Minister of Manpower of the Republic of Indonesia using Machine Learning (ML) models. The empirical comparison of results comes from automated matchmaking processed by Multinomial Naive Bayes (MNB) and Decision Tree algorithm models. Before modeling, the data is trained and evaluated for testing. Then to assess the most optimal algorithm between MNB and Decision Tree, a confusion matrix is proposed and used to find the best model. From the evaluation results, both models performed well and were highly accurate during training and test evaluation. The Decision Tree model performs slightly better than the MNB model, but both still provide satisfactory results in classifying data based on the Indonesian National Work Competency Standards (SKKNI) categories. This study offers a solution to minimize the number of potential applicants who are not competent in the three SKKNI cybersecurity job categories due to the mismatch of their abilities and skills.
PENERAPAN DATA MINING TERHADAP DATA PENJUALAN DENGAN MENGGUNAKAN ALGORITMA APRIORI PADA TOKO CITRA UTAMA Triyanto, Triyanto; Yulianti, Henny; Ikhwani, Muhammad
Journal of Information System, Applied, Management, Accounting and Research Vol 8 No 2 (2024): JISAMAR (March-May 2024)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v8i2.1485

Abstract

Citra Utama Store is a retail and wholesale business aimed at meeting the needs of local residents for their daily household shopping. The problem lies in the difficulty of identifying consumer shopping trends for products in the store, and the inefficiency of the stock placement system. In a competitive business environment, it is crucial for us to obtain information that can help develop our business. One source of such information is the sales transaction history. Using data mining with the apriori algorithm and association rule, we can extract sales transaction data to derive information that can be used to identify frequent itemset combinations, which can then be analyzed to determine products frequently sold together, the most popular items, and customer preferences. The analysis of association rules formed from the apriori algorithm calculation yielded the highest itemset combination pattern, namely EGGS → AQUA GLN, with a support value of 2.84% and a confidence value of 34.13%. By setting minimum support >1.5% and minimum confidence >30%, this research can assist the store in devising sales strategies and managing stock inventory, and uncover association rules that can be used as purchasing patterns by consumers
PREDIKSI KEBUTUHAN BERAS DENGAN METODE NEURAL NETWORK DI PULAU SUMATERA INDONESIA Yulianti, Henny
MULTINETICS Vol. 11 No. 02 (2025): Vol. 11 No. 2 (2025): MULTINETICS Nopember (2025)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v11i02.7477

Abstract

Rice is a strategic food commodity that provides more than 21% of global human caloric needs and up to 76% in Southeast Asia, including Indonesia. This study aims to analyze the dynamics of rice production and consumption on the island of Sumatra, predict annual rice demand, identify the dominant factors affecting production, and determine the leading rice-producing provinces in Sumatra. The method employed is a Neural Network integrated with the CRISP-DM research methodology to predict annual rice demand, identify key production factors, and determine the top rice-producing provinces. This study uses a dataset from the Central Bureau of Statistics (BPS) covering the years 1993–2020, consisting of six variables: province, year, production, harvested area, rainfall, humidity, and average temperature. The results show that harvested area is the most dominant factor influencing rice production across all provinces in Sumatra. The provinces with the highest rice production are Lampung, South Sumatra, and West Sumatra. The Neural Network model used has an architecture comprising six input nodes, five hidden layers, and one output layer. Model evaluation using Root Mean Square Error (RMSE) yielded a value of approximately ± 636.267 grams (0.636267 tons), indicating the predicted annual change in rice production per province. These findings are expected to assist the government and stakeholders in formulating strategies to stabilize rice production and distribution in Sumatra, thereby reducing price fluctuations and addressing supply imbalances that impact national food security
Rancang Bangun Applikasi Pemesan Tiket Shuttle Bus Berbasis Android Pada Putra KJU Karawaci Banten Indonesia Yulianti, Henny
MULTINETICS Vol. 6 No. 2 (2020): MULTINETICS Nopember (2020)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v6i2.3441

Abstract

Putra. KJU merupakan perusahaan yang bergerak dalam bidang jasa trasnportasi shuttle bus, dimana pemesanan tiket, informasi jadwal keberangkatan, dan transaksi pembayaran masih bersifat manual yakni mendatangi langsung loket penjualan tiket, yang menjadi salah satu permasalahannya adalah ketika jam sibuk sore dan pagi sering terjadi antrian di loket penjualan tiket, sehingga calon penumpang kurang mendapat pelayanan yang baik dari petugas. Seiring dengan perkembangan teknologi yang semakin pesat dimana segala sesuatu dilakukan secara mobile maka perlu adanya penerapan teknologi pada perusahaan guna mempermudah calon penumpang untuk mendapatkan pelayanan pembelian dan mengakses informasi jadwal keberangkatan Shuttle, perusahaan pun dapat mengelola penjualan tiket dengan lebih cepat dan mudah. Maka karenanya penulis berinisiatif untuk membuat suatu Aplikasi tentang Pemesanan Tiket Shuttle Bus dengan sistem berbasis Android secara online.Dalam penelitian ini untuk membangun aplikasi tersebut menggunakan metode perancangan perangkat lunak dengan model UML (Unfied Modelling Language).Aplikasi terdiri dari dua bagian yakni, admin berbasis web dan pengguna (user) yang berbasis mobile android. Sistem admin dibangun dengan bahasa pemograma PHP dan code igniter sebagai kerangka kerjanya. Sedangkan sistem pengguna dibangun menggunakan bahasa java dan XML dengan bantuan software Android studio. Dalam penelitian ini dilakukan pengujian, berjalan baik secara Black box lalu  pengujian alfa dengan hasil skor total rata-rata 39 dan presentasi keberhasilan 88,2% dan dilakukan pengujian beta dengan skor total rata-rata 123,3 dengan presentasi keberhasilan 91,3%.
Pemanfaatan Sistem Pelatihan E-Learning Pada Pengembangan Kinerja Karyawan di Masa Pandemi Covid-19 Dengan Pengujian ISO 9126 Yulianti, Henny
MULTINETICS Vol. 7 No. 1 (2021): MULTINETICS Mei (2021)
Publisher : POLITEKNIK NEGERI JAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32722/multinetics.v7i1.3769

Abstract

Pembelajaran merupakan strategi dan sekaligus sebagai solusi bagi suatu perusahaan atau instansi pemerintah maupun individu untuk beradaptasi dalam mengambil tindakan yang efektif untuk menciptakan keunggulan daya saing bisnis zaman ini. Perusahaan perlu meningkatkan kinerja karyawannya agar berprestasi dan sukses dalam pencapaian tujuan  strategis organisasi. PT Kobe Boga Utama menyadari bahwa pengembangan dan pelatihan adalah upaya untuk menciptakan SDM yang bekerja dengan performace baik dan berkualitas. Maka, e-learning adalah solusi terbaik untuk metode pembelajaran yang digunakan dalam pengembangan dan pelatihan di perusahaan ataupun instansi pemerintahan apalagi di saat kondisi dunia pandemi Covid-19. Penelitian ini bertujuan untuk membangun sistem aplikasi pelatihan E-Learning karyawan berbasis Web secara online dengan feature yang sesuai dengan kebutuhan dan mendukung kemajuan kompetensi karyawan serta mengatasi permasalahan pelatihan karyawan yang dihadapi pada PT. Kobe Boga Utama. Perancangan sistem Applikasi pelatihan E-Learning karyawan dengan metode penelitian ADDIE dan perangkat lunaknya dengan metode UML.Dan berdasarkan hasil pengujian perangkat lunak yang dilakukan dengan metode Black Box berjalan baik dan juga diukur kualitasnya dengan metode ISO 9126, dihasilkan bahwa tingkat kualitas perangkat lunak secara keseluruhan dalam kriteria Sangat Baik, dengan persentase 88,04%. Aspek kualitas tertinggi adalah berdasarkan aspek Usability dengan persentase sebesar 91,87%, selanjutnya aspek Functionality dengan 90,22%. Aspek Reliability dengan persentase sebesar 83,2%, sedangkan aspek Efficiency dengan persentase sebesar 79,33%.
Co-Authors Ajhari, Abdul Azzam Catur Nugroho Dimas Febriyan Priambodo Gatot Tri Pranoto Muhammad Ikhwani