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All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Infotech Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL ILMIAH MATEMATIKA DAN TERAPAN IKRA-ITH Informatika : Jurnal Komputer dan Informatika Jiko (Jurnal Informatika dan komputer) SEINASI-KESI METIK JURNAL Building of Informatics, Technology and Science Jurnal Muara Sains, Teknologi, Kedokteran dan Ilmu Kesehatan Technologia: Jurnal Ilmiah Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics JIKA (Jurnal Informatika) Informatics and Digital Expert (INDEX) International Journal of Global Operations Research Jurnal Ilmiah Wahana Pendidikan Journal La Multiapp Jurnal Locus Penelitian dan Pengabdian Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Jurnal Algoritma Prosiding Seminar Riset Mahasiswa Enrichment: Journal of Multidisciplinary Research and Development Jurnal Informatika Polinema (JIP) Majority Science Journal Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK)
Wina Witanti
Jurusan Teknik Informatika, Universitas Jenderal Ahmad Yani
Religion Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Other

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Analisis Tren dan Prediksi Penjualan Restoran Menggunakan Model Time Series Prophet Hidayat, Kiki; Witanti, Wina; Ramadhan, Edvin
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 2 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/gd8y7q29

Abstract

Daily sales forecasting is a critical component of business planning that must adapt to the dynamics of market demand. While traditional approaches such as Single Moving Average and Trend Moment have been used in previous studies, their predictive accuracy on daily sales often remains suboptimal, with reported MAPE values up to 39.2%. Prophet, a time series model developed by Meta, offers enhanced flexibility in capturing non-linear trends, seasonality, and incorporating external regressors. This study proposes a hybrid forecasting model by combining Prophet with engineered features and external regressors, including calendar effects and recent sales statistics. The dataset consists of daily sales records that have undergone data cleaning, logarithmic transformation, and smoothing. Prophet is configured with additional monthly seasonality, national holiday indicators, and optimized parameters through grid search. Evaluation results demonstrate a substantial improvement, with the final model achieving an R² score of 0.9787 and a MAPE of 3.79%, outperforming conventional methods and aligning with the best results from recent Prophet-based studies. These findings confirm that the integration of external variables within Prophet significantly improves prediction accuracy, making it suitable for time series forecasting in various business domains with similar data patterns.
Livestock Population Map Based on Provinces in Indonesia Using the K-Medoids Method Nurhakim, Riri Qorib; Witanti, Wina; Komarudin, Agus
Journal La Multiapp Vol. 6 No. 5 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i5.2411

Abstract

Indonesia is one of the countries with a large livestock population. A healthy and stable livestock population can affect the production and availability of livestock products, such as meat, milk, eggs, and skin. FAO's Domestic Animal Diversity - Information System (DAD-IS) data (2020) recorded around 206 large farms, small farms, poultry and pigs. Clustering is a technique for grouping data without unknown class labels. Clustering is used to find data that has similarities. The clustering technique is to determine the initial cluster center. This study is intended to determine the best cluster value using the selected method. The purpose of this study is to create a system that can process and group data. With data obtained from the central statistics agency. This study uses the topic of Livestock Population Map in Indonesia using K-Medoids. The algorithm used in this study is K-Medoids. The K-Medoids method is a variation of the K-Means method to retrieve k data, the number of clusters in a data set with n objects. There are several processes carried out in this study including collecting data, then entering the preprocessing stage, grouping data that has similarities between data. After clustering using K-Medoids, it was found that Cluster 0 had 3 provinces with the highest average population with types of livestock such as Dairy cattle, Beef cattle, Sheep and Goats, Cluster 1 had 29 provinces with the lowest average population, Cluster 2 had 2 provinces with the highest average number for types of livestock such as Buffalo, Horse and Pig.
Pembangunan Sistem Customer Relationship Management (Crm) Pada Pt. Fazypcare Putri, Ika Rahmah; Witanti, Wina; Umbara, Fajri Rakhmat
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 5, No 1 (2021): SEMNAS RISTEK 2021
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v5i1.5049

Abstract

PT. FazyPCare merupakan perusahaan yang bergerak dibidang jasa service laptop&PC. Saat ini sebagian besar kegiatan pada perusahaan masih menggunakan sistem lama yaitu pelanggan datang langsung ke perusahaan dan menyerahkan laptop/komputer yang akan di service lalu mencatat jadwal servicenya. Pada sistem lama perusahaan tidak dapat melakukan hubungan secara terus-menerus kepada pelanggan. Hal ini menimbulkan masalah dikarenakan pelanggan tidak dapat membantu pemasaran produk yang dimilikiperusahaan, pelanggan tidak terpantau oleh perusahaan dan akhirnya terjadi penurunan penghasilan dari perusahaan karena terjadinya persaingan, dengan munculnya perusahaan – perusahaan serupa yang baru berdiri dengan kualitas yang baik. Penelitian ini bertujuan untuk membangun sebuah Customer Relationship Management (CRM) yang berbasis website pada PT. FazyPCare agar dapat menjalin hubungan yang baik dan meningkatkan pelayanannya kepada client. Penelitian ini bertujuan untuk menghasilkan sebuah Sistem Customer Relationship Management (CRM) berbasis website. Dengan adanya sistem ini PT. FazyPCare dapat menjalin hubungan yang berkelanjutan, menampung keluhan client, dan dapat meningkatkan layanannya kepada client agar tidak kalah bersaing dengan perusahaan sejenis lainnya.
Pengontrolan Lampu Lalu Lintas Menggunakan Teknologi Deteksi Kendaraan YOLOV4 Wahidin, Farhan Raihan; Witanti, Wina; Ramadhan, Edvin
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 5: Oktober 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025125

Abstract

Deteksi kendaraan adalah aspek kunci dalam pengontrolan lalu lintas yang efisien. Kemacetan lalu lintas bisa terjadi salah satunya akibat pengaturan durasi lampu lalu lintas yang tidak disesuaikan dengan volume kendaraan pada saat itu. Penelitian ini bertujuan mengembangkan sistem pengontorlan lampu lalu lintas adaptif yang menyesuaikan durasi lampu berdasarkan volume kendaraan yang terdeteksi menggunakan YOLOv4, yang dapat mengatasi kekurangan pada sistem pengontrolan lalu lintas konvensional dan mengurangi kemacetan serta meningkatkan efisiensi lalu lintas. Tahapan penelitian dimulai dengan mengumpulkan data video lalu lintas dari CCTV (Closed Circuit Television) yang dipasang di berbagai lokasi strategis untuk mendapatkan gambaran lengkap tentang kondisi lalu lintas. Data tersebut kemudian dianalisis menggunakan algoritma YOLOv4 (You Only Look Once v4) untuk mendeteksi kendaraan secara real-time. YOLOv4 dipilih karena keunggulannya dalam efisiensi dan akurasi deteksi kendaraan secara real-time. Setelah data deteksi kendaraan terkumpul, data tersebut diintegrasikan dengan sistem lampu lalu lintas. Algoritma ini dirancang untuk mengintegrasikan data deteksi kendaraan secara real-time dan menyesuaikan durasi lampu lalu lintas berdasarkan jumlah kendaraan. Selanjutnya simulasi sistem menggunakan library pygame dilakukan untuk mengevaluasi kinerja algoritma di berbagai kondisi lalu lintas. Hasil penelitian menunjukkan bahwa penggunaan YOLOv4 dalam sistem pengontrolan lampu lalu lintas adaptif secara signifikan mengurangi kemacetan. Model YOLOv4 menunjukkan akurasi rata-rata tertinggi sebesar 78% dalam deteksi kendaraan di jalan kedua dengan kualitas video yang cukup baik. Penggunaan YOLOv4 dalam pengontrolan lampu lalu lintas menunjukkan peningkatan efisiensi dan responsivitas terhadap tingkat kepadatan lalu lintas sedang, dengan pengurangan durasi lampu hijau berkisar antara 53% hingga 86%.   Abstract Vehicle detection is a key aspect of efficient traffic control. Traffic congestion can occur, in part, due to traffic light duration settings that are not adjusted according to the volume of vehicles at a given time. This study develops an adaptive traffic light control system that adjusts the duration of the lights based on the detected vehicle volume, aiming to address the shortcomings of conventional traffic control systems and reduce congestion while improving traffic efficiency.The research began with collecting traffic video data from CCTV (Closed Circuit Television) installed at various strategic locations to get a comprehensive overview of traffic conditions. The data was then analyzed using the YOLOv4 (You Only Look Once v4) algorithm for real-time vehicle detection. YOLOv4 was chosen for its advantages in efficiency and accuracy in real-time vehicle detection. Once the vehicle detection data was collected, it was integrated with the traffic light system. The algorithm was designed to integrate real-time vehicle detection data and adjust the traffic light duration based on the number of vehicles. A simulation of the system was then conducted using the Pygame library to evaluate the algorithm's performance under various traffic conditions. The study results showed that the use of YOLOv4 in adaptive traffic light control systems significantly reduced congestion. The YOLOv4 model demonstrated the highest average accuracy of 78.93% in vehicle detection on the second road with fairly good video quality. The use of YOLOv4 in traffic light control showed increased efficiency and responsiveness to moderate traffic density, with a reduction in green light duration ranging from 53% to 86%.
Enhanching Prophet Time Series Forecasting on Sparse Data via Hyperparameter Optimizattion: A Case Study in Retail Atamimi, Fadel Muhamad Hafid; Witanti, Wina; Abdillah, Gunawan
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14804

Abstract

In today’s competitive business landscape, accurate sales forecasting is crucial for retailers to optimize inventory, prevent overstock, and support strategic decision-making. However, many small to medium enterprises operate with sparse and irregular sales data, making conventional forecasting methods less effective. This study aims to evaluate the performance of the Prophet time series model in such non-ideal conditions and to investigate how hyperparameter tuning affects its forecasting accuracy. The research adopts the Prophet algorithm, an additive time series forecasting model developed by Facebook, which incorporates trend, seasonality, and holiday components. The model was implemented in two configurations: one using default parameters, and another with manually tuned hyperparameters, including changepoint prior scale (CP), seasonality prior scale (SP), and seasonality mode. A total of 32 experiments were conducted using historical transaction data from PT Eko Hejo. Results show that the default Prophet model achieved a MAPE of 9.50%, while the best-performing configuration (CP = 0.5, SP = 0.01, additive mode) reduced the MAPE to 6.80%. This indicates that hyperparameter tuning significantly improves forecast accuracy, even in sparse data environments. The study contributes both practically and scientifically by demonstrating that Prophet, when properly configured, is a robust and adaptable tool for business forecasting with limited data. It also highlights the value of manual tuning in enhancing model responsiveness and generalization, offering insights for further research in model comparison, automated optimization, and hybrid forecasting approaches.
Sistem Keamanan Otentikasi Pengguna Pada Modul Single Sign On Menggunakan OAuth 2.0 dan One Time Password Arianto, Ilham Gumeraruloh; Witanti, Wina; Ashaury, Herdi
Jurnal IT UHB Vol 6 No 1 (2025): Jurnal Ilmu Komputer dan Teknologi
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/ikomti.v6i1.1768

Abstract

Keamanan informasi menjadi prioritas utama dalam melindungi data sensitif pada sistem yang menangani transfer data. Penelitian ini mengembangkan sistem Technical Support Assistance (TSA) dengan keamanan yang ditingkatkan melalui kombinasi modul Single Sign-On (SSO) berbasis Open Authentication (OAuth 2.0) dan metode One-Time Password (OTP) berbasis waktu. Pendekatan ini menciptakan autentikasi dua faktor (2FA) yang efektif dalam menghadapi risiko serangan seperti sniffing, brute force attacks, dan man-in-the-middle (MITM). Hasil pengujian menunjukkan bahwa tanpa OTP, tingkat keberhasilan serangan adalah 63% untuk brute force, 50% untuk sniffing, dan 65% untuk MITM. Setelah penerapan Oauth 2.0 dan OTP, angka ini turun signifikan menjadi masing-masing 25%, 5%, dan 10%, membuktikan bahwa kombinasi OAuth 2.0 dan OTP meningkatkan perlindungan sistem secara signifikan. Dibandingkan metode autentikasi terdahulu, TSA menawarkan keunggulan berupa keamanan berbasis token dinamis, pengurangan risiko serangan secara drastis, integrasi yang lebih mudah dengan layanan lain, serta efisiensi autentikasi yang lebih tinggi. Penelitian ini memberikan solusi inovatif untuk meningkatkan keamanan data sensitif dan relevan bagi organisasi yang memerlukan perlindungan tingkat tinggi dalam sistem mereka.
THE ROLE OF CLOUD COMPUTING TECHNOLOGY IN INCREASING WORK FLEXIBILITY IN THE HYBRID ERA Witanti, Wina
MSJ : Majority Science Journal Vol. 3 No. 3 (2025): MSJ-August
Publisher : PT. Hafasy Dwi Nawasena

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61942/msj.v3i3.443

Abstract

Digital transformation post-COVID-19 pandemic has accelerated the adoption of cloud computing technology to support hybrid work models that demand high flexibility, virtual collaboration, and cross-site employee mobility. This study aims to analyze the role of cloud computing technology in increasing work flexibility in the hybrid era through a Systematic Literature Review (SLR) approach to the latest studies for the 2020–2025 period. The results of the analysis show that cloud computing contributes significantly to increasing work flexibility through three main mechanisms, namely providing real-time data and application access, facilitating cross-site collaboration through AI-based platforms, and scalability and resource elasticity capabilities that support cost efficiency and rapid response to changing business needs. Cloud implementations have also been proven to accelerate decision-making, increase team productivity, and strengthen organizational cohesion in a hybrid work environment. On the other hand, challenges such as data security and privacy issues, reliance on internet connectivity, and the complexity of integration with legacy systems remain major obstacles. These findings confirm that cloud computing is not only a supporting technology, but also a strategic enabler for organizations to create an adaptive and sustainable hybrid work ecosystem. This study recommends the implementation of hybrid or multi-cloud architecture, strengthening network infrastructure, and developing human resource capacity so that organizations are able to maximize the potential of cloud computing optimally.
Pengukuran Kualitas Perangkat Lunak Menggunakan Model McCall Pada Sistem Akademik Universitas Jenderal Achmad Yani Abiyoga, Arji; Witanti, Wina; Kania Ningsih, Ade
Informatics and Digital Expert (INDEX) Vol. 3 No. 2 (2021): INDEX, November 2021
Publisher : LPPM Universitas Perjuangan Tasikmalaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36423/index.v3i2.877

Abstract

Di era yang sekarang ini, perangkat lunak dimanfaatkan untuk membantu manusia dalam mempermudah melakukan suatu kegiatan. Perangkat lunak yang telah dikembangkan itu perlu dilakukan pengukuran kualitas perangkat lunak untuk mengetahui kesesuaian harapan pengguna terhadap kemampuan dari perangkat lunak tersebut.  Kualitas perangkat lunak merupakan suatu hal yang penting dan tidak dapat dihindari. adapun model yang dapat digunakan untuk pengukuran kualitas perangkat lunak yaitu model McCall. Berdasarkan permasalahan tersebut, Penelitian ini bertujuan untuk melakukan pengukuran kualitas perangkat lunak berdasarkan teori McCall dengan kategori product operation pada Sistem Akademik Universitas Jenderal Achmad Yani. Dimana terdapat 5 faktor kualitas didalam kategori product operation yaitu correctness, reliability, efficiency, usability, dan integrity. Pengukuran kualitas perangkat lunak terhadap Sistem Akademik Unjani menggunakan kuesioner dengan melibatkan 100 mahasiswa Unjani untuk menilai sistem tersebut. Hasil pengukuran membuktikan bahwa Sistem Akademik Unjani memiliki kualitas perangkat lunak yang baik menurut teori McCall dengan nilai faktor kualitas tertinggi adalah usability dengan nilai 77%.
Decision Support System For Determining Food Menu Using Analytical Hierarchy Process (Ahp) Method Maulina, Ninda; Witanti, Wina; Komarudin, Agus
Enrichment: Journal of Multidisciplinary Research and Development Vol. 1 No. 7 (2023): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v1i7.65

Abstract

Food menus in the culinary and restaurant industries often involve various complex features, such as food origin, food category, diet category, ingredients, and time. This study aims to develop a Decision Support System (DSS) based on the AHP method to assist chefs, restaurant managers and food business owners in compiling a diverse menu, meeting nutritional needs, taking into account certain preferences and limitations, and creating a pleasant dining experience. The Analytic Hierarchy Process (AHP) method can be used as a tool in making more effective and structured decisions. The results of this study indicate that the Analytic Hierarchy Process (AHP) method succeeded in producing relative weights for each criterion and sub-criteria, thus enabling priority in preparing food menus. In testing, this system is able to provide the best recommendations based on global priority values for certain types of food, which are expected to increase the variety and quality of food menus and meet consumer preferences and needs. Through experiments conducted using a Decision Support System, a decision model is formed that determines the priority for the weight of all criteria and alternatives. The results show preferences in the process of determining food menus by producing Cold Coffee with a value of 0.30 (29%), Biscuit Dough Donuts with a value of 0.25 (25%), Chicken Dimsum with a value of 0.21 (21%), Succotash with a a value of 0.15 (15%), and Toffee Banana with a value of 0.10 (10%).
Optimasi Penentuan Vendor Untuk Material Pesawat Menggunakan Algoritma Particle Swarm Optimization Pratiwi, Siska Hutami; Witanti, Wina; Pudjiantoro, Tacbir Hendro
Jurnal Ilmiah Wahana Pendidikan Vol 10 No 4 (2024): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.10537168

Abstract

In the aviation industry, determining vendors for aircraft materials is an important task that can affect the quality, reliability and safety of aircraft. The selection of the right material for the aircraft is crucial, because it is closely related to the operational sustainability and overall performance of the aircraft. However, determining vendors for aircraft materials often involves a variety of complex criteria and requires an efficient and precise approach. In this study, using the Particle Swarm Optimization (PSO) Algorithm to solve the problem of determining aircraft material vendors. The PSO algorithm has proven effective in a variety of optimization problems and offers a population-based approach inspired by group behavior in nature. By utilizing the PSO algorithm, it can optimize the process of determining vendors for aircraft materials by considering criteria such as quality of delivery and average quality score. The results of the research show that the PSO algorithm is able to find the optimal combination of vendors efficiently, thereby helping stakeholders make more informed and result-oriented decisions. In addition, the results of this study also show that the PSO algorithm itself has a weakness, namely being stuck at a local optimum, having difficulty finding global solutions. Particles moving towards a local optimum may reduce exploration effort to find a better solution globally.
Co-Authors Abiyoga, Arji Adhinata Kusuma, Rendy Adzani, Nadhif Nurul Fajri Afifah, Hira Nur Alfarizi, Muhammad Bayu Ardi Andhika, Firza Rafiandi Aranda, Sepri Arianto, Ilham Gumeraruloh Asendra, Irfan Ashaury, Herdi Asrul Atamimi, Fadel Muhamad Hafid Budiman, Firman Nur Budiman, Zillan Taufiq Dewi, Wulan Dian Nursantika Edvin Ramadhan Eka Purnama Rijaludin, Muhamad Fahrezi Ahmad, Rafly Fikri Fahrezi, Rizal Febrian Faiza Renaldi, Faiza Fauzan, Ariq Firdaus, Syahrul Ghozali, Mohamad Aditya Muttaqin Gunawan Abdillah, Gunawan Hadiana, Asep Id Hardianto, Mohamad Aris Hasbia, Muhamad Iqbal Maulana Kania Ningsih, Ade Kasyidi, Fatan Kiki Hidayat, Kiki Komarudin, Agus Komarudin, Agus Liesdiannisa, Mutiara Virgi Lusy Sundary, Lusy Mandala, Muhamad Bintang Maulina, Ninda Melina Melina, M Nabilah, Mitamufida Kusuma Nabilah, Mitamufida Kusuma Nailendra, Septian Yudha Nugraha, Faisal Okta Nugraha, Faisal Okta Nurhakim, Riri Qorib Nurhasanah, Wulandari Nurputra, Windi Raihan Nurul Sabrina, Puspita Pinasty, Syarifudin Yoga Pradana, Muhammad Rifqi Prasetyo, Nur Faid Pratiwi, Siska Hutami Putra, Eddie Krishna Putri, Ika Rahmah Rakhmat Umbara, Fajri Rezki Yuniarti Ridwan Ilyas Rusmana, Hendri Diana Saputri, Intan Vidia Syarafina, Fildzah Tacbir Hendro Pudjiantoro Trianggara, Dhani Umbara, Fajri Rakhmat Wahidin, Farhan Raihan Wahyudiputra, Helmy Fauzan