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All Journal Query : Jurnal Sistem Informasi JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Tekinkom (Teknik Informasi dan Komputer) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknologi Informatika dan Komputer Journal of Computers and Digital Business Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Pengabdian Kepada Masyarakat Teknologi Informasi dan Komunikasi
Evta Indra
Universitas Prima Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

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ANALISIS DALAM MENENTUKAN STOK BARANG MASUK DARI SUPPLIER PADA BLIBLI.COM MEDAN MENGGUNAKAN METODE ASSCOATION RULE DENGAN ALGORITMA APRIORI Delima Sitanggang; Oktoberto Perangin-angin; Esther Mayorita Nababan; Meri Natasia Napitupulu; Evta Indra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.936

Abstract

The divisions that support the service production business continue to be developed, so as to provide more benefits for the organizers. One part that continues to be researched is the determination of suppliers of goods for production companies, because a good supplier will not only maximize cooperative relations, but also supply quality raw materials, as well as provide convenience in the process of importing goods. in the previous calculations the minimum support value that had been determined was 3.5%, so the researcher formed 1 itemset where the support value met the percentage in the category (accessories 5.8%), (cigarette 11.4%), (cooking ingredients 23.1%), (electronic 30.9%), (food 28.1%), (gagdet,46.6%), (healthy&beauty 12.4%), and y(kids&baby 4.2%) , in the formation of 2 itemsets where those containing A are combined with those containing item B which fulfill the percentages on (electronics, food 19.3%) , (gadgets, cooking ingredients 23.9%), (gagdet, electronics 37.6%) , and (gagdet, food 19.3%) in the formation of 3 itemsets with support (A,B,C) there is no item value that meets the minimum support value and for the minimum confidence value in this study 40% in the establishment of a rule or association of 2 itemsets that meet confidence (cigarettes, kids baby 52.6%), and (kids babies, accessories 47.6%), for the establishment of a 3 itemset association rule that meets the minimum confidence value (kids babies, electronics, accessories 47.6%), (kids baby, fozen food, accessories 47.6%), (food, gadgets, kids baby 95.2%), (kids baby, fozen food, cooking ingredients 47.6%).
ANALISIS DAN PERANCANGAN SISTEM LAYANAN DAN RESERVASI TIKET BUS ONLINE MELALUI PENDEKATAN BERBASIS WEBSITE Palma Juanta; Windania Purba; Evta Indra; Mario Gota Manalu; Aguan Aritonang
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.944

Abstract

In this day and age the bus is the most common means of transportation used by the community because of the low price and easy way of ordering simple and accurate and still affordable for the economic community middle down. Generaly bus ticket bookings are made with go directly to the point of sale of bus tickets or by calling to the counter office. This ordering process has a weakness, namely the clerk or managers have difficulty recording, and errors often occur when recording ticket reservations. Regarding the time of ordering, usually prospective travelers book tickets a day or two before departure, and some are don't book tickets a few days in advance and buy tickets on the day departures, which often results in them not getting tickets that are society wants. The aim of this work is to design the system online bus ticket reservation developed using an application. Program it is built using Python programming and machine learning to make it easier to generate data automatically and make predictions Accurate. The result of this research is a bus ticket reservation system which offers a new alternative to the bus ticket booking process without distance and time constraints. In addition, the public will also receive information regarding bus schedules, ticket prices, and possible changes to departures bus.
PREDIKSI PENJUALAN OBAT PADA RUMAH SAKIT MENGGUNAKAN METODE DOUBLE EKSPONENTIAL SMOOTHING Winda Yoceva Pane; Nathanael Chrisman Laurentio Pardede; Rikky Martua Hasudungan Simaremare; Evta Indra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1346

Abstract

Royal Prima Hospital faces challenges in managing its drug inventory. Each month, the available quantity of drugs remains the same without considering the actual needs, based only on the amount of drugs sold. As a result, there is often an excess of drug stock, leading to reduced shelf life, lower drug prices, and unsatisfactory patient service. This situation is certainly detrimental to the hospital. To help hospital management reduce errors in forecasting drug sales, the Double Exponential Smoothing forecasting method with an alpha of 0.6 was applied, as the sales data show a trend. This method provides a solution that can be used to predict the number of drugs that will be sold in both the short and long term with a high level of accuracy. The forecasting results produced a Mean Absolute Error (MAE) of 791.64, a Mean Square Error (MSE) of 17,887,289,511.31, and a Mean Absolute Percentage Error (MAPE) of 0.78%. Thus, hospital management can manage drug inventory more efficiently and reduce wastage. This study offers significant benefits by providing a more accurate approach to forecasting drug sales.
Tanggap Darurat Banjir: Inovasi Distribusi Logistik dan Pemulihan Psikososial bagi Masyarakat Sumatera Utara Mas Intan Purba; Esther Praja Anggriany Panggabean; Evta Indra; Beby Astri Tarigan
Jurnal Pengabdian Kepada Masyarakat Teknologi Informasi dan Komunikasi Vol 3 No 1 (2026): Januari
Publisher : CV. ADMITECH SOLUTIONS

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

Abstract

Program Pengabdian kepada Masyarakat Tanggap Darurat Bencana Tahun 2025 ini dilaksanakan sebagai respons terhadap banjir yang melanda Sumatera Utara pada akhir November 2025. Awalnya direncanakan di Kelurahan Sei Mati, Medan Labuhan, program dialihkan ke tiga kecamatan yang masih terdampak parah: Hamparan Perak, Pantai Labu, dan Pangkalan Susu, setelah koordinasi dengan LPPM Universitas Prima Indonesia dan Direktorat Jenderal Pendidikan Tinggi. Kegiatan mencakup distribusi logistik kebutuhan dasar kepada 598 keluarga, pemulihan psikososial melalui trauma healing untuk 400 anak, layanan kesehatan gratis bagi 44 warga, serta bakti sosial pembersihan fasilitas umum. Adaptasi dari proposal awal dilakukan karena kondisi banjir telah surut dan mayoritas masyarakat adalah petani serta nelayan. Program ini berhasil meringankan beban korban, meningkatkan resiliensi komunitas, dan mendukung pemulihan berkelanjutan. Hasil menunjukkan peningkatan akses kebutuhan dasar, pemulihan emosional anak-anak, serta penguatan gotong royong masyarakat. Luaran mencakup artikel di media massa, video impact, dan peningkatan level keberdayaan mitra dari ketergantungan tinggi menjadi mandiri parsial. Kegiatan ini selaras dengan Tri Dharma Perguruan Tinggi dan prioritas nasional penanganan bencana, dengan kontribusi pada pencegahan outbreak penyakit dan edukasi sanitasi..
Analisis Sentimen Pengguna Media Sosial Terhadap Konten Virtual Idol Berbasis AI: Studi Kasus MAVE Hashfi Shani; Yohanna Ria Laura Ambarita; Cici Sundari; Evta Indra
Journal of Computers and Digital Business Vol. 5 No. 2 (2026)
Publisher : PT. Delitekno Media Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56427/jcbd.v5i2.1008

Abstract

Virtual idol berbasis kecerdasan buatan (Artificial Intelligence/AI) menjadi fenomena yang semakin berkembang dalam industri hiburan digital melalui berbagai platform media sosial. Meskipun interaksi pengguna terhadap virtual idol terus meningkat, penelitian yang mengintegrasikan analisis sentimen dan evaluasi kualitas layanan digital dalam konteks virtual idol berbasis AI masih relatif terbatas. Penelitian ini bertujuan menganalisis sentimen pengguna media sosial terhadap konten virtual idol AI MAVE menggunakan model IndoBERT Fine-Tuning serta mengevaluasi kualitas layanan menggunakan pendekatan SERVQUAL. Penelitian menerapkan metode mixed method dengan dua sumber data, yaitu 2,493 komentar YouTube yang dianalisis menggunakan IndoBERT Fine-Tuning dan data survei SERVQUAL dari 216 responden penggemar MAVE di Indonesia. Hasil analisis sentimen menunjukkan bahwa sentimen positif mendominasi sebesar 63.46%, diikuti sentimen netral sebesar 27.32%, dan sentimen negatif sebesar 9.23%. Hasil analisis SERVQUAL menunjukkan bahwa seluruh dimensi kualitas layanan memiliki kesenjangan negatif yang signifikan antara ekspektasi dan persepsi pengguna. Kebaruan penelitian ini terletak pada integrasi analisis sentimen berbasis IndoBERT Fine-Tuning dan evaluasi kualitas layanan SERVQUAL untuk memahami persepsi pengguna terhadap virtual idol berbasis AI. Temuan penelitian memberikan wawasan bagi pengembang virtual idol dalam meningkatkan kualitas layanan dan pengalaman pengguna pada ekosistem hiburan digital berbasis AI.
Studi Eksperimental: Efektivitas AI Dalam Meningkatkan Aksesibilitas Informasi PCOS Via Mobile App Ruth Megarini Panjaitan; Miranda Mas Tasya Sitorus; Evta Indra
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.472

Abstract

Polycystic Ovary Syndrome (PCOS) is a hormonal disorder commonly experienced by women of reproductive age; however, the level of literacy regarding PCOS remains relatively low. Limited access to clear and easily understandable information has contributed to a lack of awareness of this condition. This study aims to develop an Artificial Intelligence (AI)-based mobile application called OVAI as an educational medium to improve the accessibility of PCOS information. The research was conducted by distributing questionnaires to female respondents aged 18–45 years using a Likert scale. The collected data were analyzed to determine the level of user acceptance and the consistency of the research instrument. The results showed that the OVAI application was successfully developed with interactive chatbot features and user-friendly educational content. The application was considered helpful in enabling users to better understand information related to PCOS and to access information more practically. Therefore, the OVAI application can be utilized as a digital educational medium for women of reproductive age.
Cross-Validated Hybrid Machine Learning Model For Real-Time Phishing URL Detection On Google Chrome Extension Evta Indra; Wahyu Soekanta Ginting; Katrin Wijaya; Nuragustyani br Bangun
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 4 (2026): Juni 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i4.9777

Abstract

Phishing attacks continue to pose a major cybersecurity challenge, with traditional server-side and deep learning detection methods often struggling with network latency, privacy risks, and high computational overhead. This research focuses on creating a lightweight phishing URL detection system that operates in real time on the client side, implemented as a Google Chrome extension. The system employs a hybrid machine learning architecture combining Logistic Regression (LR) and Random Forest (RF) to evaluate 22 purely lexical URL features extracted locally. Evaluated using 5-fold cross-validation, the base models demonstrated high stability with mean performance scores of μ = 0.9960 for LR and μ = 0.9968 for RF. Crucially, confusion matrix analysis revealed that the hybrid approach perfectly resolved the trade-off between user accessibility and security. It successfully captured 20,037 phishing links (True Positives) and permitted 26,957 legitimate URLs (True Negatives). It minimized false alarms to just 13 False Positives, matching LR’s efficiency, while also reducing missed detections to 152 False Negatives. Furthermore, a live implementation test on 100 URL samples achieved 92% accuracy rate in providing real-time visual risk alerts. By performing all feature extraction and analysis locally without transmitting data externally, this system overcomes algorithmic trade-offs and network latency, delivering a dependable and user-friendly defense without compromising browsing performance.
Pengenalan Microsoft Office Bagi Guru TKA-TPA Islam Umaira Medan Anita Anita; Muhardi Saputra; Sri Wahyuni Tarigan; Marlince N K Nababan; Evta Indra
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol. 2 No. 1 (2022): April 2022
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v2i1.956

Abstract

Abstrak: Aplikasi office sudah sangat sering digunakan sesuai dengan kebutuhan sehari-hari dalam mendokumentasikan secara digital, baik berupa teks, angka dan presentasi. Berkembangnya aplikasi microsoft office setiap tahunnya membuat para guru kesulitan dalam mengikuti perkembangannya sehingga banyak guru yang belum mengenal dan paham akan penggunaan aplikasi tersebut. Maka itu kegiatan pengenalan microsoft office ini bertujuan untuk meningkatkan pengetahuan dan wawasan serta keterampilan kepada guru tentang penggunaan microsoft office yaitu microsoft word dan microsoft excel untuk proses adminitrasi ataupun pembelajaraan. Melalui pengabdian masyarakat ini guru juga dapat meningkatkan kompetensi profesional terutama dalam pemanfaatan teknologi pada proses pembelajaran. Sehingga guru TK bisa mengenal dan paham akan penggunaan microsoft office secara tepat. Kata kunci: Pengenalan Aplikasi; Microsoft Office; Guru-Guru  Abstract: Office applications are very often used in accordance with daily needs in digitally documenting, both in the form of text, numbers and presentations. The development of Microsoft Office applications every year makes it difficult for teachers to follow its development so that many teachers do not know and understand the use of these applications. Therefore, the introduction of Microsoft Office activities aims to increase knowledge and insight and skills to teachers about the use of Microsoft Office, namely Microsoft Word and Microsoft Excel for the administration or learning process. Through this community service, teachers can also improve professional competence, especially in the use of technology in the learning process. So that kindergarten teachers can recognize and understand the proper use of Microsoft Office. Keywords: office application; microsoft office; teachers
Co-Authors Aguan Aritonang Aldowad Alles Sandro Hamonangan Simanjuntak Andreas Situmorang Anita Anita Beby Astri Tarigan Cici Sundari Cloudia Stevani Saragih Sumbayak Daniel Ryan Hamonangan Sitompul Davit Toramli Husni Delima Sitanggang, Delima Denis Jusuf Ziegel Dennis Jusuf Ziegel Dinda Tamara Silaen Efendi Efendi Esther Mayorita Nababan Esther Praja Anggriany Panggabean Faijriah Nazla Sahira Fanny Dameka br Sitanggang Fredilio Fredilio Hashfi Shani Jefri Syah Putra Laoli Julfikar Rahmad Juli Yanti Kartika Harahap Katrin Wijaya Kurniawan Tarigan M Diarmansyah Batubara M. Diarmansyah Batubara Mardi Turnip, Mardi Mario Gota Manalu Marlince NK Nababan Matthew Oullanley Lee Meri Natasia Napitupulu Michael Owen Miranda Mas Tasya Sitorus Mohammad Irfan Fahmi Muhammad Yasir Muhardi Saputra Nadila Azriansyah Nanchy Adeliana Br S. Muham Nathanael Chrisman Laurentio Pardede Novanius Lahagu Nuragustyani br Bangun Oktoberto Perangin-angin Owen Owen Palma Juanta Paskariawan br Sihotang Pungki Laurensius Ritonga Purba, Mas Intan Putri Rahma Dewi Riama Br Ambarita Rikky Martua Hasudungan Simaremare Rivaldo Sitanggang Ruben Ruben Ruben, Andreas Situmorang Ruth Megarini Panjaitan Sadarman Zebua Saljuna Hayu Rangkuti Sion Putri Zalukhu Sonia Novel Lase Sri Wahyuni Tarigan Stiven Hamonangan Sinurat Sugandi Chau Vincent Vincent Wahyu Soekanta Ginting Winda Yoceva Pane Windania Purba Yakub Anuyuta Zebua Yenny Yenny Yohanna Ria Laura Ambarita