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All Journal Dinamik International Journal of Artificial Intelligence Research SMARTICS Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Applied Information System and Management METIK JURNAL Jusikom: Jurnal Sistem Informasi Ilmu Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Pendidikan dan Teknologi Indonesia Djtechno: Jurnal Teknologi Informasi KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer J-Intech (Journal of Information and Technology) Jurnal Informatika Teknologi dan Sains (Jinteks) Malcom: Indonesian Journal of Machine Learning and Computer Science
Hilabi, Shofa Shofiah
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science

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IMPLEMENTATION OF SUPPLY CHAIN MANAGEMENT AT CV.TINGGAR JAYA FOR WEB-BASED STOCK MONITORING Ramadan, Mohamad Rizqulloh; Hilabi, Shofa Shofiah; Nurapriani, Fitria; Priatna, Bayu
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i2.4764

Abstract

Implementation of Supply Chain Management at CV. Tinggar Jaya is a company warehouse system designed for company needs to coordinate company resources. The problem that occurs at CV. Tinggar Jaya still uses manual methods, from ordering to checking or monitoring stock in the warehouse. Therefore, the solution to this problem is implementing supply chain management at CV. Tinggar Jaya will organize and monitor the warehouse's stock amount using the waterfall system design method with the expected goal of implementing supply chain management to monitor the stock of goods to be more efficient in carrying out this process. Keywords: Warehouse, Supply Chain Management, Goods, Monitoring, Stock, Website
PREDICTION OF POPULATION GROWTH IN KARAWANG CITY USING MULTIPLE LINEAR REGRESSION ALGORITHM METHOD Desfianthy, Fatiya Hanifah; Hilabi, Shofa Shofiah; Priyatna, Bayu; Novalia, Elfina
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 2 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

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

Abstract

Currently, Indonesia is experiencing population growth. The factors influencing this growth are the rates of births and deaths. Every year, the population in an area keeps growing. This growth can have various negative impacts on the region. That's why taking action and making predictions about population growth is crucial. The objective of this study is to use a regression algorithm to estimate how fast the population will grow in Karawang City. The data used for this research comes from population records collected by the Karawang City Statistics Agency between 2017 and 2022. To clean, transform, and analyze this data, we employ the Knowledge Discovery in Database (KDD) approach to data mining. By applying linear regression methods with assistance from RapidMiner tools, we have successfully generated predictions based on data that reveal patterns and relationships between variables that influence population growth rates. According to our predictions, there will increase of 338,011 people from 2022 to 2027. This research will assist the Karawang City government in developing plans to minimize negative impacts while optimizing resource utilization such as energy, food, water, and services. Keywords: Multiple Linear Regression, Data Mining, BPS, Rapid Miner
Implementation of UI/UX Using Design Thinking Method in Tomsufood Application Sunarya, Edwin Yohanes; Huda, Baenil; Hananto, Agustia; Hilabi, Shofa Shofiah
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5026

Abstract

Tomsufood is one of the online food ordering applications. To provide the best experience in ordering food, Tomsufood designed a new application product. An approach called Design Thinking was used in this study. The Design Thinking method is a software product design approach that is based on innovation and relies on problem-solving techniques. After identifying and understanding the problem obtained through the process of identifying the problem, describing the solution, empathizing with the user, and prototyping and testing. So that the Tomsufood application is able to solve problems that occur in society. The results of the study showed that the application of the Design Thinking method was able to produce a UI/UX design that was more intuitive and responsive to user needs. Users reported increased satisfaction in using the application, which included ease of navigation, clarity of information, and efficiency in the food ordering process. Keywords: UI/UX, Design Thinking, Tomsufood, User Experience
Prediksi Angka Kelahiran dalam Berbagai Kelompok Umur Ibu Menggunakan Metode K-Nearest Neighbor: Prediction of Birth Rates in Different Age Groups of Mothers Using the K-Nearest Neighbor (K-NN) Method Syafana, Vinka; Hilabi, Shofa Shofiah; Novalia, Elfina; Huda, Baenil
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 4 No. 3 (2024): MALCOM July 2024
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v4i3.1392

Abstract

Studi ini bertujuan untuk mengembangkan prediksi angka kelahiran dalam berbagai kelompok umur ibu melalui pendekatan metode K-Nearest Neighbors (K-NN) dalam suatu sistem informasi. Penelitian ini difokuskan pada analisis dinamika kelahiran dalam konteks kelompok umur ibu, yang merupakan informasi kritis dalam perencanaan kebijakan kesehatan dan pengembangan sosial. Metode K-NN digunakan sebagai pendekatan analisis utama untuk meramalkan angka kelahiran, memanfaatkan pola kemiripan dalam karakteristik kelompok umur ibu. Integrasi metode K-NN dalam sistem informasi memungkinkan pengelolaan dan analisis data yang lebih efisien untuk mendukung kebijakan perencanaan keluarga. Data yang digunakan mencakup variabel demografis, ekonomi, dan sosial yang dapat memengaruhi tingkat kelahiran. Hasil prediksi angka kelahiran diharapkan dapat memberikan wawasan mendalam tentang perubahan dinamis dalam struktur kelahiran, memungkinkan pemahaman yang lebih baik untuk mengarahkan kebijakan kesehatan dan strategi intervensi yang lebih terarah. Penelitian ini menghadirkan kontribusi pada pengembangan sistem informasi yang dapat mendukung analisis prediktif dalam konteks kelahiran. Implikasi temuan ini relevan untuk kebijakan kesehatan, demografi, dan perencanaan keluarga, serta dapat membantu merancang langkah-langkah intervensi yang lebih efektif dan tepat sasaran.
Sistem Pemilihan Supplier Obat Menerapkan Metode Additive Ratio Analysis (ARAS) Al Khadzik, Fahmi; Huda, Baenil; Novalia, Elfina; Hilabi, Shofa Shofiah
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 3 (2024): Maret 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7499

Abstract

Qita Sehat pharmacy provides a wide range of medicines that are supplied by more than 30 suppliers and 100 buyers every month, but not all suppliers can meet the criteria set by pharmacies and suppliers are often late in the process of supplying drugs to pharmacies so that the stock in pharmacies is running low. From these problems, a solution is made, namely a drug supplier selection system is made by determining the priority order of drug suppliers with several criteria that match the availability of drugs at Qita Sehat pharmacies. The method used is the method of ARAS (Additive Ratio Analysis). The criteria considered are price, quality, lead time, communication systems, performance history and repair services. The result of this method is the order of priority of drug suppliers and knowing the results of the questionnaire through the sensitivity test that is the influence of changes in the value of the importance of the criteria. From the data generated in research using the ARAS method, the results obtained are that PT Javas Karya is the best supplier with the first rank of alternative A6 with a total value of 0.120.
Application of the K-Nearest Neighbor Method to Predict Demand for Goods from Customers at PT Sinergi Prima Enjineering Angraeni, Rahmah Nur; Priyatna, Bayu; Hananto, Agustia; Hilabi, Shofa Shofiah
Bahasa Indonesia Vol 16 No 02 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i02.200

Abstract

PT Sinergi Prima Enjineering, which is engaged in services, has been trusted as a contractor in several companies facing challenges in handling the large number of requests for goods and stock inventory management. This research aims to improve the prediction of demand for goods and inventory management using the calculation of the K-Nearest Neighbor (KNN) method and RapidMiner tools. With the comparison of calculations between KNN and RapidMiner using ten test data, the results are appropriate where the categorical grouping is often ordered totaling five data, moderately ordered totaling two data and rarely ordered totaling three data. The test results show that K = 3 produces a prediction accuracy of 91.98%. These results show that K-Nearest Neighbor can accurately anticipate future stock inventory and items that will be ordered by customers and it is hoped that the company can improve customer satisfaction and overall operational performance.
Analisis User Experience dan Usability Aplikasi Canva dalam mendukung Kemudahan Pembelajaran Siswa di SMPN 3 Karawang Barat Desfianthy, Fatiya Hanifah; Rosalina, Elsa; Pratama, Daffa Agung; Hilabi, Shofa Shofiah
Dinamik Vol 30 No 1 (2025)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v30i1.9702

Abstract

Canva salah satu platform yang digunakan untuk mendesain, yang dapat digunakan melalui web maupun aplikasi mobil. Canva menyediakan beragam fitur dan template yang mempermudah pengguna untuk membuat desain, seperti desain poster, brosur, kartu ucapan, info grafis dan presentasi dalam waktu singkat. Penelitian ini bertujuan untuk menganalisis usability aplikasi canva dengan fokus untuk memahami pengalaman pengguna, khususnya dari kalangan Siswa Kelas VIIIB di SMPN 3 Karawang Barat. Metode yang digunakan untuk mengumpulkan data yaitu observasi dan kuesioner. Analisa aplikasi menggunakan poin Usability berkaitan dengan learnability, efficiency, memorability, error dan satisfaction untuk mengetahui pengalaman pengguna. Hasil penelitian menunjukkan bahwa 77,5% responden merasakan kemudahan dalam penggunaan aplikasi canva, 65% merasa cepat dalam menggunakan fitur-fiturnya, dan 72,5% mampu mengingat langkah-langkah penggunaannya dengan baik. Namun, masih terdapat kendala pada aspek memorability, di mana 47,5% responden mengalami kesulitan dalam mengenali ikon atau simbol dalam aplikasi. Pada aspek error, 62,5% responden menemukan error saat menggunakan canva, dan hanya 50% yang dapat memperbaikinya dengan mudah. Meskipun demikian, tingkat kepuasan pengguna sangat tinggi, dengan 92,5% responden merasa senang menggunakan canva dan 94,3% menyatakan bahwa canva membantu mereka dalam menyelesaikan tugas sekolah. Dengan demikian, canva memiliki peran penting dalam mendukung kemudahan pembelajaran siswa di SMPN 3 Karawang Barat.
Pemanfaatan Data Analitik dalam Big Data: Studi Kasus Implementasi di Pemerintahan Hilabi, Shofa Shofiah; Savina, Savina; Khairunisa, Sabnabila
JATISI Vol 12 No 1 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i1.10916

Abstract

This study examines the use of Big Data in public health management in Indonesia, with a special emphasis on the opportunities, problems, and impacts of using evidence-based data on decision-making. This research was conducted using a descriptive qualitative approach, which involved the analysis of secondary data from a number of relevant journal articles. The results of the study show that big data improves health policy, decision-making processes, and understanding of public health trends. Examples of practices that occurred during the COVID-19 pandemic show how big data analytics helps governments monitor vaccine deployment and distribution in real time. However, major issues such as lack of technological infrastructure, limited human resources, and data privacy issues continue to emerge. Research shows that with strengthened technology infrastructure, employee training, and better data security policies, the implementation of Big Data has great potential to improve the efficiency of public health management. According to this study, investment in information technology must be made, and also a policy framework that supports data integration between government agencies must be created.
Penggunaan Algoritma K-Means Clustering CRISP-DM Dalam Mengelompokkan Drama Korea Sebagai Rekomendasi Film Fatlun, Aulia; Hilabi, Shofa Shofiah; Priyatna, Bayu; Hananto, April Lia
JATISI Vol 12 No 1 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i1.11347

Abstract

This study classifies Korean dramas based on popularity and ratings using K-Means Clustering within the CRISP-DM framework. The dataset from Kaggle includes title, release year, rating, vote count, duration, and genre. The Elbow Method determined that 2 clusters were optimal, with a Silhouette Score of 0.35, indicating a fairly good grouping. Recommended dramas have high ratings and vote counts, showing strong popularity, while less recommended dramas have lower ratings and fewer votes, indicating limited appeal. This model can enhance recommendation system accuracy, assist viewers in content selection, and help streaming platforms understand user trends and marketing strategies. Future improvements may involve alternative clustering methods (DBSCAN, Hierarchical Clustering) and additional features like actors, directors, and release year to refine accuracy.
KLASIFIKASI DAN PREDIKSI ULASAN APLIKASI DANA PADA GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES Hayati, Cucu; Tukino; Hilabi, Shofa Shofiah; Hananto, April Lia
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.5691

Abstract

Di era digital saat ini, kemajuan teknologi yang pesat telah mendorong masyarakat beralih ke transaksi digital melalui financial technology (Fintech), salah satu inovasi fintech yaitu aplikasi DANA. Penelitian ini bertujuan untuk mengklasifikasi dan prediksi ulasan aplikasi DANA menggunakan Naïve Bayes. Dengan jumlah data 1.500 ulasan kemudian dilabeli berdasarkan kategori transaksi, keamanan, kinerja Aplikasi, pelayanan, serta aktivasi dan verifikasi. Tahapan penelitian ini dilakukan mulai dari pengumpulan data, pelabelan manual , preprocessing , pembobotan kata, model Naïve Bayes , dan evaluasi. Berdasarkan hasil analisis, tingkat akurasi yang diperoleh adalah sebesar 87%, dengan presisi mencapai 88%, recall sebesar 84%, dan f1-score sebesar 85%. Akurasi mengacu pada persentase prediksi yang benar dari keseluruhan data. Presisi menunjukkan seberapa tepat model dalam memprediksi suatu kelas tertentu, recall mengukur kemampuan model dalam menemukan seluruh data termasuk dalam suatu kelas tertentu, dan f1-score menggambarkan keseimbangan antara presisi dan recall. Maka, dapat disimpulkan model bawah pada penelitian ini mampu dalam mengklasifikasikan seluruh kategori dan dapat memberikan prediksi yang akurat, meskipun terdapat perbedaan nilai presisi, recall , dan f1-score . Diharapkan penelitian ini dapat bermanfaat bagi pengembang aplikasi DANA, dan juga dapat memberikan informasi mengenai efisiensi dan efektivitas algoritma Naïve Bayes dalam klasifikasi dan prediksi.
Co-Authors Al Khadzik, Fahmi Angraeni, Rahmah Nur April Lia Hananto Desfianthy, Fatiya Hanifah Fatlun, Aulia Fauzi Ahmad Muda Hananto, Agustia Hayati, Cucu Huda, Baenil Khairunisa, Sabnabila Kurnia, Nisa Muhamad Bayu Aditya Pratama Nijunnihayah, Uktupi Novalia, Elfina Nurapriani, Fitria Nurfauzi, Oka Muhamad Pratama, Daffa Agung Priatna, Bayu Priyatna, Bayu Ramadan, Mohamad Rizqulloh Rosalina, Elsa Saputri, Arini Sari, Fitria Ratna Sari, Nurnilam savina, savina Shidiq, Faisal Sunarya, Edwin Yohanes Syafana, Vinka tukino, tukino Tukino, Tukino Yovika Aprianti Zulfiana, Rizka