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SAFITRI JUANITA
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Idealis : Indonesia Journal Information System
Published by Universitas Budi Luhur Jakarta
ISSN : -     EISSN : 26847280     DOI : -
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Jurnal Indonesia Journal Information System (Idealis) adalah jurnal penelitian Program Studi Informasi, Fakultas Teknologi Informasi, Universitas Budi Luhur. Topik pada Jurnal ini adalah Decision Support System, E-Commerce/E-Business, Datawarehouse/BI, Enterprise System, Data Mining, Sistem Penunjang Keputusan selamat membaca,  Admin Jurnal Idealis
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 901 Documents
 87   88   89   90   91 
IMPLEMENTATION OF TOPSIS METHOD IN SUPPLIER SELECTION SYSTEM WITH RAPID APPLICATION DEVELOPMENT Mangunsong, Ikhwanda Buyung; Irawan, Muhammad Dedi
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 1 (2025): Jurnal IDEALIS Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i1.3361

Abstract

Technology in creating web-based information systems is developing very quickly. The ease of accessing informationand communicating has had a major impact on industry, pushing it towards digital systems. CV. Berjaya Jaya Abadi, acontractor company which operates in the field of providing various types of paint, faces the challenge of selecting the bestsupplier among several alternatives so as to enable a system development process that is faster, iterative, and focuses on userneeds, resulting in optimal and efficient solutions. in supplier selection. This research aims to build and develop a system basedon previous research using Rapid Application Development (RAD). This research also updates the criteria and adds sub-criteriato maximize the effectiveness of the TOPSIS method in the supplier selection process. By adopting the TOPSIS system, companiescan make more effective, efficient and data-driven decisions, which ultimately helps improve competitiveness and performance.This system is designed to simplify decision making in selecting suppliers by considering six main criteria, namely Delivery,Performance History, Price, Quality, Loyalty and Service. This research shows that the system developed can provide supplierrankings based on predetermined criteria, so that it can help companies choose suppliers that best suit their needs. The researchresults show th
SISTEM INFORMASI PENJADWALAN DAN REKOMENDASI VENDOR MENGGUNAKAN METODE ROUND ROBIN PADA MANAJEMEN FOTOINKITA Aidil, Elqi Rahmat; Triase, Triase
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 1 (2025): Jurnal IDEALIS Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i1.3363

Abstract

Efficient schedule management and vendor selection are crucial aspects of the photography service industry, especially in FotoinKita’s management, which is experiencing growing demand. The previously used manual system had limitations in schedule management and vendor allocation, often leading to scheduling conflicts and customer dissatisfaction. This research employs the Round Robin method for scheduling and vendor recommendations. The method distributes tasks evenly among available vendors, ensuring a balanced workload and reducing the risk of capacity imbalances. The system is designed to integrate vendor recommendations based on the Round Robin algorithm to achieve a fair and equitable task distribution. Utilizing web-based technology, the system allows users to make bookings and schedule tasks online while receiving vendor recommendations based on specific criteria. Testing was conducted using the black-box method to ensure all features function as required. Additionally, system performance was evaluated through scheduling simulations with realistic scenarios. The implementation results showed that the system could reduce scheduling conflicts by up to 85% and increase task distribution efficiency by 90%. This system improves operational efficiency and customer satisfaction by reducing wait times and ensuring equitable task allocation. The system ensures fair task distribution among vendors and provides vendor recommendations that meet predefined criteria. The implementation of the Round Robin method in this system demonstrates that fair and efficient scheduling can be achieved, delivering significant benefits to FotoinKita’s service management.
DAMPAK PROGRESSIVE WEB APPLICATION (PWA) TERHADAP PENINGKATAN ENGAGEMENT DAN DWELL TIME PADA APLIKASI E-COMMERCE Putro, Dwi Purnomo; Suprianto, Joko; Suryani, Puput Eka
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 1 (2025): Jurnal IDEALIS Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i1.3369

Abstract

The advancement of digital technology encourages businesses to adopt e-commerce applications. However, the successful implementation of e-commerce applications still faces challenges in improving key indicators such as user engagement and dwell time. Progressive Web App (PWA) offers a technological solution with fast performance, high stability, and easy access across various devices, which is expected to address these challenges in e-commerce. While many e-commerce applications are available, not all of them have adopted PWA. Although PWA has the potential to address these challenges, its impact on engagement and dwell time has not been widely studied, particularly using a quantitative approach based on web analytics data. Previous research on PWA has largely focused on technical aspects and general user experience surveys. This study aims to measure the impact of PWA on user engagement and dwell time in e-commerce applications. It employs a quantitative method with a quasi-experimental approach, involving 50 participants divided into an experimental group (using PWA) and a control group (without PWA). Data were collected through Google Analytics and analyzed using the Shapiro-Wilk normality test and parametric analysis. The results show that PWA significantly increases engagement and dwell time, with pageviews rising by 48.79%, session duration increasing by 67.26%, and dwell time growing by 55.56%. These findings demonstrate that PWA not only enhances application efficiency but also improves user experience. This study contributes to the e-commerce literature and recommends the adoption of PWA to optimize user interaction and support sustainable business growth.
TOMATO CLASSIFICATION BASED ON VARIETY WITH RGB FEATURE EXTRACTION AND NAÏVE BAYES ALGORITHM Widyastuti, Evi; Hermawan, Arif; Avianto, Donny
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 1 (2025): Jurnal IDEALIS Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i1.3370

Abstract

Tomato is a fruit-category vegetable plant that is easy to cultivate in various locations. The diversity of tomato varieties, such as Red Zebra Tomato, Green Zebra Tomato, and Kumato, often makes rapid and accurate variety identification challenging. Misclassification can impact the selection of environmental conditions and pest or disease management, ultimately leading to suboptimal cultivation results. Currently, research primarily focuses on tomato shape, diseases, and ripeness levels, while cultivar classification based on color characteristics remains limited. This study aims to develop a method for classifying tomato cultivars based on RGB color features using the Naïve Bayes algorithm. The research was conducted by collecting 45 tomato images with similar shapes but different colors (red, green, and dark red). The research stages include RGB feature extraction, data rounding, splitting training and test data with a 70:30 ratio, and classification using Naïve Bayes. A re-evaluation was performed by removing specific color attributes to assess their impact on accuracy. This study is expected to support rapid and accurate tomato variety identification, enhance efficiency in modern agriculture, and expand the application of technology in the agricultural industry to achieve advanced, self-sufficient, and modern farming. The results show that the RGB feature extraction method and the Naïve Bayes algorithm can classify tomato cultivars with an accuracy of up to 78.57%. The RG color attributes have the most significant impact on accuracy, reaching 85.71%.
PENGUKURAN KEAMANAN PENGGUNA ANDROID MENGGUNAKAN EXPECTACY BASED MODEL DAN ALTERNATIVE THREAT BASED MODEL Tanjung, Dio Febrillian; Wella, Wella
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 1 (2025): Jurnal IDEALIS Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i1.3180

Abstract

Saat ini, 132,7 juta smartphone digunakan di Indonesia, menunjukkan bahwa smartphones merupakan perangkat penting bagi masyarakat Indonesia. Jumlah pengguna yang terus meningkat setiap tahunnya, dan popularitas smartphone dengan sistem operasi Android menunjukkan bahwa pengguna Android juga rentan terhadap ancaman. Setelah melihat kerentanan ini, dianggap penting untuk melacak tindakan pengguna untuk meningkatkan kesadaran pengguna akan tindakan yang salah. Metode yang digunakan dalam penelitian ini adalah Expectacy Based Model dan Alternative Threat Based Model. Model pertama memiliki variabel dependen perilaku dan variabel independen seperti susceptibility, severity, susceptibility x severity, efficacy, cost, trust, dan user shopiscation. Model kedua memiliki variabel dependen perilaku dan variabel independen seperti malware, data leakage, data theft, biaya sosial, kepercayaan, dan pengguna perdagangan. Analisis akan dilakukan menggunakan tools SPSS.
PERAMALAN PENJUALAN SAHAM NIKEL MENGGUNAKAN ALGORITMA LONG SHORT TERM MEMORY (LSTM) Mahbubi, Firhan Abdillah; Hermanto, Teguh Iman; Lestari, Chandra Dewi
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 1 (2025): Jurnal IDEALIS Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i1.3254

Abstract

Indonesia has the world's largest nickel resources, with production of 1.6 million tons out of a global total of 328 million tons by 2022. In 2020, the Indonesian government imposed a ban on nickel ore exports to increase domestic processing and attract investment. Nickel supply reached 26 billion tons with reserves of 11,887 million tons. Mineral and coal investment in 2021 reached US$35 billion. The government plans 53 smelters until 2024, with 19 operating in 2021. PT Resource Alam Indonesia Tbk is active in the industry and faces fluctuations in nickel stock prices, which create problems, namely uncertainty for investors in making investment decisions due to fluctuations in nickel prices on the world market. So, effective stock price forecasting is needed using time series data analysis. This research uses a deep learning algorithm approach: Long Short Term Memory (LSTM). The research method uses CRISP-DM, which includes business understanding, data understanding, data preparation, model building, model evaluation, and deployment. Experimentation uses Python, and visualization uses the Streamlit Framework. This study uses optimal technical parameters to evaluate the LSTM model's effectiveness in predicting Nickel stock prices at PT Resource Alam Indonesia Tbk. The results showed that the Long Short Term Memory (LSTM) model could predict the sale of Nickel shares at PT. Resource Alam Indonesia Tbk (password: KKGI.JK) well, with an MAE value of 33.15, RMSE value of 48.14, MSE value of 2317.33, and MAPE value of 7.39. The best combination of the parameter combinations tested is with batch size 32, epochs 150, and optimizer Adam. The findings provide valuable insights for investors in making more informative and effective investment decisions.
SISTEM PENJUALAN BAHAN KEBAB PADA TOKO YUMNA KEBAB MENGGUNAKAN FRAMEWORK CODEIGNITER Carudin; Khusurur Fauziah, Miftah; Fitriani, Rina
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 2 (2025): Jurnal IDEALIS Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i2.3394

Abstract

Perkembangan teknologi informasi telah memberikan dampak signifikan terhadap berbagai sektor, termasuk sektor perdagangan. Dalam era digital ini, adaptasi terhadap sistem informasi berbasis web menjadi suatu keharusan bagi pelaku bisnis untuk tetap kompetitif.  Yumna Kebab adalah toko yang menyediakan berbagai jenis bahan kebab. Transaksi penjualan saat ini pada toko Yumna Kebab masih menggunakan nota penjualan yang dicatat dan diserahkan ke pembeli sebagai bukti transaksi dengan kondisi saat ini toko Yumna Kebab terdapat beberapa kendala seperti, kurang efisien dalam proses transaksi penjualan, monitoring stok yang sulit dan sering terjadi selisih stok, bahkan minus stok serta pembuatan laporan penjualan yang sering ditemukan tidak balance. Penelitian ini bertujuan untuk merancang sistem informasi penjualan yang efisien dan efektif menggunakan Framework CodeIgniter. CodeIgniter dipilih karena kemudahan dalam pengembangan, dokumentasi yang lengkap, dan kemampuan untuk membangun aplikasi web yang responsif. Metode dalam pengembangan sistem menggunakan Agile meliputi tahap Plan, Design, Develop, Test, Deploy, Review dan Launch. Dari hasil pengembangan sistem dilakukan pengujian desain, tingkat kemudahan dan tingkat responsibilitas sistem dengan menggunakan metode User Acceptance Testing (UAT). Hasil pengujian sebesar 84,4%, yang menunjukan bahwa sistem penjualan bahan kebab pada toko Yumna Kebab masuk dalam kategori sangat baik, kesimpulannya sistem mampu meningkatkan efisiensi proses penjualan, mempercepat pengambilan keputusan, serta meminimalkan kesalahan dalam pencatatan data.
Deteksi Penyakit Daun Kapas Dengan Deep Learning Berbasis Convolutional Neural Network (CNN) Bhagawanta, Bajra; Budy Santoso, Cahyono
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 2 (2025): Jurnal IDEALIS Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i2.3517

Abstract

Penelitian ini mengembangkan model kecerdasan buatan dengan algoritma Convolutional Neural Network (CNN) untuk mendeteksi penyakit pada daun kapas secara akurat dan otomatis. Metode konvensional seperti observasi visual seringkali tidak efektif dalam mengidentifikasi penyakit tanaman. Dengan menggunakan pendekatan deep learning, khususnya CNN, penyakit seperti Fusarium Wilt dan Bacterial Blight dapat diidentifikasi secara otomatis dan akurat melalui analisis citra daun kapas. Teknologi ini memungkinkan tindakan pencegahan lebih cepat untuk meminimalisir kerugian serta mendukung pengambilan keputusan berbasis data. Penelitian ini dilakukan melalui tahapan: pengumpulan data gambar daun kapas, preprocessing, modelling, analisis, dan evaluasi model menggunakan confusion matrix dan kurva ROC. Dengan dataset berisi 4.778 gambar dari enam kelas kondisi daun, model mencapai akurasi pelatihan 97% dan validasi 90% setelah 20 epoch, serta hasil evaluasi menunjukkan kinerja klasifikasi yang sangat baik dengan nilai precision, recall, f1-score yang tinggi, dengan nilai Area Under Curve (AUC) mendekati 1. Model ini mampu mendeteksi penyakit berdasarkan fitur visual dan memberikan hasil klasifikasi real-time, membuktikan bahwa CNN efektif dalam membantu identifikasi dini penyakit tanaman kapas.
ANALISIS TREN LOWONGAN PEKERJAAN SOFTWARE ENGINEERING DI INDONESIA DENGAN CLUSTERING DAN SOCIAL NETWORK ANALYSIS Harahap, Tiara Amanda Jullet; Santoso, Cahyono Budy
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 2 (2025): Jurnal IDEALIS Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i2.3518

Abstract

Pertumbuhan ekonomi digital di Indonesia mendorong permintaan tinggi terhadap tenaga kerja software engineering. Namun, distribusi spasial dan keterkaitan antar entitas dalam ekosistem lowongan kerja digital belum dianalisis secara komprehensif. Penelitian ini bertujuan untuk menjawab permasalahan kurangnya pemetaan struktur dan tren lowongan pekerjaan software engineering di Indonesia. Untuk itu, digunakan dua pendekatan analitik: K-Means Clustering untuk segmentasi spasial dan fungsional berdasarkan atribut lokasi dan posisi, serta Social Network Analysis (SNA) untuk menganalisis struktur hubungan antara lokasi, perusahaan, dan posisi pekerjaan. Data dikumpulkan melalui web scraping dari 12 platform daring terkemuka di Indonesia, menghasilkan 5.272 entri yang disaring menjadi 2.303 entri unik. Hasil clustering menunjukkan bahwa posisi Software Engineer (85 koneksi), Data Engineer, dan Frontend Developer mendominasi di Jakarta dan Tangerang. Jakarta tercatat sebagai lokasi dengan Degree Centrality tertinggi (1.396), menandakan dominasinya sebagai pusat rekrutmen digital nasional. Dari sisi perusahaan, PT Telkom Indonesia (degree = 62) dan Shopee (degree = 58) merupakan aktor strategis. Posisi Product Manager dan DevOps Engineer memiliki nilai betweenness tertinggi, menunjukkan fungsi lintas tim yang krusial. Penelitian ini memberikan kontribusi terhadap pemahaman spasial dan struktural pasar tenaga kerja digital Indonesia. Temuan ini dapat dimanfaatkan untuk strategi rekrutmen, perencanaan pendidikan vokasional, dan pengembangan karier. Penelitian selanjutnya disarankan untuk mengintegrasikan dimensi temporal dan variabel keahlian atau gaji guna memperluas cakupan analisis.
ANALISIS DAN PERANCANGAN APLIKASI PENGENALAN KAMPUS DENGAN MENERAPKAN TEKNOLOGI AUGMENTED REALITY Yunita, Maria; Darkel, Yohanes Brekmans M; Lodan, Maria Wihelmina
IDEALIS : InDonEsiA journaL Information System Vol. 8 No. 2 (2025): Jurnal IDEALIS Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/idealis.v8i2.3519

Abstract

Sebagai kampus yang ingin lebih maju, diperlukan promosi yang lebih baik. Didukung dengan adanya media informasi yang interaktif. Beberapa teknologi dewasa ini yang digunakan di berbagai Universitas sebagai media informasi, mulai dari teknologi cetak seperti koran, audio visual, komputerisasi, sampai tekonologi gabungan antara cetak dan komputerisasi di Universitas Nusa Nipa. Namun memerlukan perangkat eksterior tambahan, hal ini dapat meningkatkan biaya tambahan dan keterbatasan mahasiswa mengakses informasi membuat media cetak kurang diperhatikan, Hal ini menyebabkan informasi yang diperoleh kurang lengkap dari kampus sendiri. Untuk mendukung dalam memberikan informasi tentang kampus Universitas Nusa Nipa kepada publik, diperlukan media tambahan berupa aplikasi pengenalan kampus sebagai layanan dalam menginformasikan fasilitas kampus dengan tampilan desain 3D atau Augmented Reality (AR). Tujuan dilakukannya penelitian ini adalah merancang aplikasi berbasis mobile dengan menerapkan teknologi AR. AR memiliki potensi besar sebagai media promosi yang menggunakan teknologi digital untuk meningkatkan pengalaman pengguna. Penelitian ini menggunakan metode pengembangan sistem dari gabungan (Multimedia Development Life Cycle) MDLC dan UCD pada proses product of design dan evaluate design againts. Aplikasi ini dapat di install melalui smartphone yang menmpilkan fasilitas kampus dan gedung di Universitas Nusa Nipa Maumere. Hasil dari penelitian ini memungkinkan semua mahasiswa untuk mengetahui informasi kampus melalui aplikasi yang ada pada smartphone.

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