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All Journal TEKNIK INFORMATIKA Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) JAIS (Journal of Applied Intelligent System) Creative Information Technology Journal SISFOTENIKA JITK (Jurnal Ilmu Pengetahuan dan Komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURTEKSI CCIT (Creative Communication and Innovative Technology) Journal Jurnal Sistem Informasi Kaputama (JSIK) E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi TRIDARMA: Pengabdian Kepada Masyarakat (PkM) IT (INFORMATIC TECHNIQUE) JOURNAL Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Journal of Applied Data Sciences Jurnal Dharma Bhakti Ekuitas Journal of Social Responsibility Projects by Higher Education Forum INFOSYS (INFORMATION SYSTEM) JOURNAL Jurnal Minfo Polgan (JMP) Jurnal ABDIMAS Budi Darma Journal of Artificial Intelligence and Engineering Applications (JAIEA) INTERNATIONAL JOURNAL OF MECHANICAL COMPUTATIONAL AND MANUFACTURING RESEARCH Information System and Data Science Information Technology and Cyber Crime Informatics Engineering and Electronic Data Jurnal Penelitian Sistem Informasi Jurnal ICT : Information and Communication Technologies Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka Jurnal Bima PUBLIDIMAS ORAHUA : Jurnal Pengabdian Kepada Masyarakat
Lili Tanti
Universitas Potensi Utama
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A Hybrid GRG-Neighborhood Search Model for Dynamic Multi-Depot Vehicle Routing in Disaster Logistics Hartama, Dedy; Poningsih, Poningsih; Tanti, Lili
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.973

Abstract

In disaster relief logistics, timely and adaptive routing is critical to meet fluctuating demands and disrupted infrastructure. This paper proposes a Hybrid GRG–Neighbourhood Search (NS) model for solving the Multi-Depot Vehicle Routing Problem with Capacity and Time Dependency (MDVRP-CTD). The model integrates the Generalized Reduced Gradient (GRG) method for handling nonlinear capacity constraints and NS for local route refinement. The objective is to minimize total travel distance, delay penalties, and maximize vehicle utilization under dynamic disaster scenarios. Tested using the SVRPBench dataset, the hybrid model achieved up to 96.5% demand fulfillment, an 11% improvement in vehicle utilization, and a reduction in total distance by 7%, outperforming Tabu Search and ALNS in three simulation scenarios. The model demonstrates enhanced adaptability and responsiveness to time-sensitive, capacity-constrained environments. Its novelty lies in the integration of nonlinear optimization with adaptive local improvement tailored for disaster contexts, providing a robust decision-support tool for real-time humanitarian logistics.
Design and Development of an Android-Based Inpatient Room Availability Application for Sinar Husni Hospital Salwani D, Zuki Salwani D; Tanti, Lili
Jurnal ICT : Information and Communication Technologies Vol. 16 No. 2 (2025): October, Jurnal ICT : Information and Communication Technologies
Publisher : Marqcha Institute

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

Abstract

For every patient requiring inpatient care, Sinar Husni Hospital provides inpatient rooms in various classes. Sinar Husni Hospital also accepts medical and inpatient services through the Social Security Agency (BPJS). A problem is that inpatient rooms at Sinar Husni Hospital are often unavailable due to the large number of people requiring inpatient care and limited space. This is discovered after people arrive for treatment and the hospital informs them of available inpatient rooms, ultimately resulting in patients being referred to other nearby hospitals. Therefore, a method is needed for Sinar Husni Hospital to provide information to the public regarding inpatient room availability and for the public to receive information about the availability of inpatient rooms at Sinar Husni Hospital. The researcher's solution involves using computers and Android devices using the K-NN method to recommend inpatient rooms for patients. This research also aims to create an application that can manage inpatient room data and disseminate information about inpatient room availability to the public, allowing them to determine the availability of inpatient rooms. KNN can determine rooms that meet patient needs and desired facilities. The application consists of two users: the first, an administrator via a web server, who manages inpatient room data, and the second, a member of the public, who receives inpatient room availability information via an Android device.
DESIGN AND CONSTRUCTION OF SOIL MOISTURE DETECTION TOOL USING ANDROID BASED DECISION TREE ALGORITHM Aziz Ritonga, Mirwan; Tanti, Lili
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 4 (2025): September 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i4.4194

Abstract

Abstract: Soil moisture is an important factor in determining the watering needs of plants for optimal growth. Therefore, accurate monitoring of soil moisture is necessary. This research aims to design and build a soil moisture detection tool based on the Decision Tree algorithm with the support of the YL-69 sensor for humidity measurement and the DHT11 sensor for temperature measurement to increase data accuracy. This system uses NodeMCU ESP8266 as a microcontroller and is integrated with an Android application as a user interface. Sensor interpretation data is analyzed using the Decision Tree algorithm to determine soil conditions (dry, damp or wet). The test results show an accuracy level of 95% from 300 data samples. Thus, this system is able to detect soil moisture effectively and can help increase the efficiency of crop management on a household and commercial agricultural scale. Keywords: agriculture, android, decision tree algorithm, sensors, soil moisture detection
Anomaly Detection in Computer Networks Using Isolation Forest in Data Mining Lubis, Hartati Tammamah; Roslina, Roslina; Tanti, Lili
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i1.44285

Abstract

The rapid growth of network data has increased the complexity of detecting anomalies, which are crucial for ensuring the security and integrity of information systems. This study investigates the use of the Isolation Forest algorithm for anomaly detection in network traffic, utilizing the Luflow Network Intrusion Detection dataset, which contains 590,086 records with 16 features related to network activities. The methodology encompasses data preprocessing (cleaning, normalization, and feature scaling), feature selection (bytes in, bytes out, entropy, and duration), model training, and performance evaluation. The results demonstrate that Isolation Forest can effectively identify anomalies based on feature patterns, isolating suspicious data points without the need for labeled datasets. However, performance metrics, such as accuracy (42.92%), precision (14.37%), recall (2.87%), and F1-score (4.79%), reveal challenges such as high false-positive rates and low sensitivity to true anomalies. These findings highlight the potential of the algorithm for dynamic, high-dimensional datasets but also indicate the need for further improvements through hyperparameter tuning, feature engineering, and alternative approaches. This study contributes to the development of adaptive anomaly detection frameworks for network security and suggests future integration into real-time systems for proactive threat mitigation. The study's findings are particularly relevant for enhancing network security in environments such as corporate and governmental networks, where real-time anomaly detection is crucial.
Online Shop Product Sales Prediction Using Multilayer Perceptron Algorithm Safitri, Erica Rian; Tanti, Lili; Wanayumini, Wanayumini
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i1.44286

Abstract

This study aims to develop a predictive model for forecasting product sales using the Multilayer Perceptron (MLP) algorithm. The model's performance was evaluated using key metrics, including the Mean Absolute Error (MAE), Mean Squared Error (MSE), and R² score. The model achieved an MAE of 0.861, an MSE of 9.521, and an impressive R² score of 0.999, demonstrating its ability to accurately predict product sales with minimal error. Feature correlation analysis identified key variables related to the target prediction, which is the number of products ready for shipment, underscoring the importance of feature selection in enhancing model performance. Prediction results revealed variability among product sales, with products like Foodpak Matte 245 (Code 49) predicted to sell approximately 244.31 units, while others like Stiker Kertas (Code 90) showed lower sales forecasts. The findings suggest that strategic interventions may be necessary to boost sales for underperforming items and capitalize on the demand for popular products. Future improvements, such as optimizing the network architecture, experimenting with activation functions and optimization algorithms, and incorporating external factors such as market trends, could further enhance the model’s accuracy and predictive power. Overall, the MLP model demonstrates strong potential for product sales forecasting, providing valuable insights for business decision-making.
PELATIHAN PRESENSI ONLINE MENGGUNAKAN GOOGLE FORM DI YAYASAN PENDIDIKAN ISLAM AR-RIDHA Adhar, Deni; Safrizal, Safrizal; Tanti, Lili; Fahrozi, Wirhan
Jurnal Pengabdian Masyarakat Sabangka Vol 3 No 03 (2024): Jurnal Pengabdian Masyarakat Sabangka
Publisher : Pusat Studi Ekonomi, Publikasi Ilmiah dan Pengembangan SDM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62668/sabangka.v3i03.1082

Abstract

The use of online attendance at several schools in the North Sumatra region can help efficiency in reducing physical materials (paper) and can be directly monitored/evaluated online. Currently, the school at the Ar-Ridha Foundation, one of the attendance methods implemented online, still uses WhatsApp to monitor online attendance. Due to many obstacles, sending attendance via WhatsApp is considered less effective. One of the barriers reported was the requirement for teachers to review each student's data submission individually. Using Google Forms to create virtual courses is one way teachers can apply online learning. Google Forms is a Google product. Google Forms is a free online program available to schools, non-profit organizations, and anyone with a Google Account. Using Google Forms will facilitate interaction between teachers and students. Google Forms makes it easy for students and teachers to stay in touch. Google Forms is a blended learning platform that Google developed for schools seeking to create, distribute, and assign paperless assignments
Sistem Pendukung Keputusan Perpanjang Kontrak Karyawan dengan Algoritma Decision tree Handoko, Muhammad Yan Handoko Putra F; Lili, Lili Tanti
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

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Abstract

Proses perpanjangan kontrak kerja di perusahaan sering kali menimbulkan kompleksitas karena melibatkan kesejahteraan karyawan serta kelangsungan produktivitas organisasi. PT. Duta Agung Jaya, sebagai perusahaan outsourcing di Kota Medan, masih mengalami hambatan dalam menentukan karyawan yang memenuhi syarat untuk perpanjangan kontrak. Hingga saat ini, proses penentuan dilakukan secara manual atau semi-komputerisasi menggunakan Microsoft Excel, yang berpotensi menimbulkan kesalahan perhitungan, kecenderungan subjektivitas, serta kurangnya pertimbangan komprehensif terhadap aspek-aspek kinerja. Variabel independen yang diterapkan mencakup absensi, pendidikan, kuantitas kerja, disiplin, masa kerja, prestasi, komunikasi, dan tanggung jawab, sedangkan variabel dependen adalah kelayakan perpanjangan kontrak karyawan (layak/tidak layak). Data penelitian terdiri dari 1000 dataset karyawan kontrak, yang kemudian diproses dan diuji untuk menghasilkan model keputusan yang lebih objektif. Dengan pendekatan ini, penelitian diharapkan dapat menyediakan sistem yang akurat dalam memberikan rekomendasi keputusan, mengurangi kesalahan akibat subjektivitas, serta memfasilitasi manajemen dalam mengevaluasi kinerja karyawan secara transparan dan terukur. Secara keseluruhan, hasil penelitian ini diharapkan memberikan kontribusi signifikan dalam meningkatkan kualitas pengambilan keputusan di PT. Duta Agung Jaya, serta menjadi referensi bagi penelitian serupa di bidang penerapan Sistem Pendukung Keputusan dengan algoritma ID3 pada kasus manajemen sumber daya manusia. Algoritma ID3 atau Iterative Dichotomiser 3 merupakan salah satu algoritma yang dapat digunakan untuk membangun decision tree dengan mencari semua kemungkinan dalam pohon keputusan melalui struktur hierarki untuk pembelajaran terawasi.
Klasifikasi Kelayakan Penerima Program Indonesia Pintar (PIP) Menggunakan Teknik Data Mining Naive Bayes Ahmad, Ahmad Syah Lubis; Lili, Lili Tanti; Ratih, Ratih Puspasari
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9160

Abstract

Program Indonesia Pintar (PIP) merupakan inisiatif bantuan pendidikan dari pemerintah yang ditujukan bagi siswa dari keluarga kurang mampu. Namun, dalam pelaksanaannya, proses seleksi penerima PIP sering kali dilakukan secara manual dan subjektif, sehingga rentan terhadap kesalahan dan ketidaktepatan sasaran. Penelitian ini bertujuan untuk mengembangkan sistem klasifikasi kelayakan penerima PIP dengan menggunakan teknik data mining melalui algoritma Naive Bayes. Pengujian dilakukan dengan data historis siswa di SMA Laksamana Martadinata. Hasil evaluasi menunjukkan bahwa metode Naive Bayes menghasilkan performa yang memuaskan, dengan akurasi sebesar 95% pada data pengujian dan 90% pada data baru. Sistem ini diharapkan dapat mendukung pihak sekolah dalam proses seleksi penerima PIP secara lebih objektif, efisien, dan akurat.
Penerapan Metode Combined Compromise Solution (CoCoSo) Dalam Penentuan Kelayakan Pemberian Insentif Karyawan Anggi, Anggi Canita Simanjuntak; Lili, Lili Tanti
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9161

Abstract

Penilaian kelayakan pemberian insentif kepada karyawan merupakan salah satu aspek penting dalam manajemen sumber daya manusia, guna mendorong motivasi dan produktivitas kerja. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan berbasis website dengan menerapkan metode CoCoSo dalam menentukan kelayakan insentif karyawan di PT. Bolon Jaya Karya. Metode CoCoSo digunakan karena kemampuannya dalam menggabungkan beberapa kriteria penilaian menjadi satu skor akhir yang objektif dan adil. Proses evaluasi dilakukan terhadap 200 data karyawan, dan hasil pengujian menggunakan confusion matrix menunjukkan nilai akurasi sebesar 85%, presisi 89%, recall 82%, specificity 88%, dan F1-score sebesar 85%. Hasil ini menunjukkan bahwa sistem yang dibangun mampu memberikan hasil klasifikasi yang akurat dan andal. Implementasi sistem ini memberikan manfaat signifikan bagi perusahaan, antara lain mempercepat proses evaluasi, mengurangi bias subjektif, serta meningkatkan transparansi dan kepercayaan karyawan terhadap sistem insentif yang berlaku.
Pengoptimalan Penjadwalan Rute Pengiriman Barang dengan Algoritma Genetika pada Logistik Terpadu Jasri, Jasri Ramadhan; Lili, Lili Tanti
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i2.9169

Abstract

Pengiriman barang yang efisien merupakan faktor penting dalam sistem logistik terpadu, terutama dalam penentuan rute pengiriman yang optimal untuk meminimalkan jarak tempuh dan biaya operasional. Penelitian ini mengembangkan sistem penjadwalan rute pengiriman barang menggunakan Algoritma Genetika (AG). Proses optimasi dilakukan melalui tahapan seleksi, crossover, dan mutasi terhadap populasi awal berisi 5 kandidat rute. Hasil pengujian menunjukkan bahwa algoritma genetika berhasil menurunkan total jarak tempuh rute pengiriman dari rute awal 90 km menjadi 70 km, atau terjadi efisiensi jarak sebesar 22,2%. Selain itu, algoritma mampu menghasilkan beberapa konfigurasi rute optimal yang konsisten dengan nilai fitness tertinggi pada tiap generasi. Dengan pengurangan jarak tersebut, estimasi biaya operasional dapat ditekan hingga 20–25%, bergantung pada konsumsi bahan bakar kendaraan. Sistem penjadwalan rute yang dihasilkan juga mampu menyesuaikan secara dinamis terhadap perubahan jumlah titik tujuan dan kondisi operasional. Dengan demikian, penerapan Algoritma Genetika terbukti meningkatkan efisiensi distribusi dan mendukung proses pengambilan keputusan pada perusahaan logistik terpadu.
Co-Authors adhar, Deni Adhar, Deni Adhar Ahmad, Ahmad Syah Lubis Ahsanul Huda Alim Murtani Alvian Julianto Hutajulu alya, Alya Rahmadani Andra Alfira Andra Alfitra Andrian Syahputra Anggi, Anggi Canita Simanjuntak Ayu Nadya Ayuni Syahputri Aziz Ritonga, Mirwan Bob Subahan Riza Bob Subhan Riza Bob Subhan Riza Bob Subhan Riza Bob Subhan Riza, Bob Subhan Budi Triandi Budi Triandi, Budi Daifiria Daifiria Deni Adhar Deni Adhar Deni Adhar Adhar Deni Anggara Devi Pratiwi Putri Dewi Kartika Dhooni, Dhoni Briliant Efendi, Syahril Erica Rian Safitri Evri Ekadiansyah fachrie, Fachrie Ditya Faisal Tanjung Fauzan Arif Feberianus Zai Fretty S Siahaan Handoko, Muhammad Yan Handoko Putra F Hartama, Dedy Hartati Tammamah Lubis Herman Mawengkang Indah Widiastuti Iwan Fitrianto Rahmad Jasri, Jasri Ramadhan Juli Iriani Juli Iriani Juli Iriani Juli Iriani, Juli Juni Ismail Khairul Fajri Khairul Ummi Lahmudin Sipahutar Lubis, Hartati Tammamah M Rizky M Zendi Lubis M. Aidil Fitra Wahyudi M. Haidil Umam Mangunsong, Puja Mawardah Azzahra Maya Silvi Lydia Mubarak Mubarak Muhammad Daud Muhammad Faris Nanda Setiawan Nety Juwita Lubis Nurainun Nurhayati Nurhayati Pairin, Yusfrizal Bin Patuan Putra Wijaya Sitorus Poningsih Poningsih, Poningsih Rabiana Saragih Ratih Puspasari Ratih Puspasari Ratih, Ratih Puspasari Ridho, Irdian Rika Rosnelly, Rika Riza, Bob Subahan Rofiqoh Dewi Roslina Roslina Roslina Roslina, Roslina Safitri, Erica Rian Safrizal Safrizal Safrizal Safrizal Safrizal Safrizal Salwani D, Zuki Salwani D Simalango, Clarensia Mende Surbakti, Dio Febrian Susianto Susianto Syefira Arrafah Tasya Ardilah Thanri, Yan Yang Wanayumini Windy, Micky Alviansyah Wirhan Fahrozi, Wirhan Yanyang Thanri Yudhi Andrian Yulika Ababil _, Safrizal