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All Journal Jurnal Informasi dan Komputer Jurnal Teknologi Informasi dan Pendidikan Infotekmesin Zonasi: Jurnal Sistem Informasi JATI (Jurnal Mahasiswa Teknik Informatika) G-Tech : Jurnal Teknologi Terapan Jurnal Teknik Informatika (JUTIF) Jurnal Puan Indonesia Jurnal Akuntansi Keuangan dan Bisnis Tedc Journal of Informatics and Electronics Engineering Journal of Economics, Accounting, Tax and Management Media Elektrik JPPkM: Jurnal Pengabdian dan Pemberdayaan kepada Masyarakat Journal of Applied Information Technology and Innovation
Novita Lestari Anggreini
Politeknik TEDC
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Pelatihan Mengenalkan Struktur Data pada SMK Negeri 2 Cimahi Tresnawati, Shandy; Ekawati, Nia; Anggreini, Novita Lestari; Rohmayani, Dini
PUAN INDONESIA Vol. 6 No. 1 (2024): Jurnal Puan Indonesia vol 6 no 1 Juli 2024
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v6i1.278

Abstract

Data structures and algorithms are important, integrated, and mutually supportive parts of building good and efficient application programs. Paying more attention to this can provide very important results, especially in increasing access speed and providing insight and guidance on how to improve problem solving and find better solutions. The service team conducts community service in Software Engineering expertise, this certainly supports the material that will be delivered to the Software Engineering department about learning Data Structures. In addition, the service team received an explanation from the teacher of SMK Negeri 2 Cimahi, there is data structure learning material so that it is sustainable in the training held by the service team. The material presented by 3 (three) speakers included linked lists, stacks and queues. The following are the results done by the service participants. The conclusion on community service at SMK Negeri 2 Cimahi, the service participants, namely school students, were enthusiastic in learning data structure material. Service participants understand better and can implement the results that have been done in the training process.
ANALISIS POLA PEMBELIAN KONSUMEN PADA DATA PENJUALAN MENGUNAKAN ALGORITMA APRIORI: STUDI KASUS COFFEE SHOP GELORA FANTASI Alya Shafira, Salma; Lestari Anggreini, Novita
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 5 (2024): JATI Vol. 8 No. 5
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i5.10953

Abstract

Pada Coffee Shop Gelora Fantasi, data – data terkait penjualan dan stok bahan masih belum terorganisir secara baik dan masih dilakukan secara manual seperti pada data penjualan, stok bahan lama dan stok untuk produk yang tidak terjual. Hal tersebut mengakibatkan sulitnya melihat stok yang habis sehingga membuat banyaknya stok tersebut terabaikan dan menyebabkan penumpukan data. Tujuan dibuatnya analisis pola pembelian konsumen ini yaitu untuk memudahkan proses baik pembelian dan pengukur untuk stok bahan juga mengurangi terbuangnya stok saat proses general cleaning. Metode yang di implementasikan yaitu Data Mining dengan Algoritma Apriori. Data yang digunakan merupakan data penjualan Coffee Shop Gelora Fantasi selama 6 bulan sekitar 15.409 data. Analisis pola pembelian produk dengan menngunakan Algoritma Apriori ini diharapkan dapat mengetahui akurasi data penjualan lalu dijadikan bahan evaluasi dan juga perbaikan sehingga dapat memudahkan Coffee Shop Gelora Fantasi terhadap stok bahan yang keluar masuk dan dijadikan acuan juga untuk pemasaran produk yang dapat ditingkatkan kembali. Proses analisis menggunakan Rapid Miner, hasil pengujian menghasilkan menu Cappucino dan Kopi Susu Aren menunjukkan hubungan erat dengan nilai Support tertinggi 14,5% dari total transaksi namun untuk nilai Confidence tertinggi 85,3% dengan nilai Support sebesar 10,5% untuk menu Cafe Latte dan Kopi Susu Aren.
Prototype Sistem Kendali Pintu Gerbang Otomatis Berbasis Internet of Things (IoT): Indonesia Novita Lestari Anggreini; Nia Ekawati; Hasbi Nur Ichsan
Infotekmesin Vol 14 No 2 (2023): Infotekmesin: Juli, 2023
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v14i2.1893

Abstract

An automatic gate is a door whose operation process runs automatically using a remote drive tool, but when combined with IoT elements, it means that users can control the automatic gate using a cell phone or mobile phone. The purpose of this research is to create a prototype of an automatic gate control system based on the Internet of Things (IoT). The method used in the current research is the prototype method. The results in this study were tested to determine the range. Testing is done using an adapter connected to a power supply. The testing process is carried out by observing the movement and response of the servo motor when controlled via a smartphone and the stepper motor when the Ultrasonic sensor detects an object less than 5 cm. The conclusion of this research is that at a distance of 1 to 19 meters, the gate lock can still be controlled properly. While at a distance of 20 meters when the gate lock is open, the gate opens and closes. This is because the WiFi signal cannot be captured properly by the central controller of the circuit at a distance of more than 19 meters.
IMPLEMENTASI ALGORITMA NAIVE BAYES DENGAN METODE KLASIFIKASI DALAM MENENTUKAN SISWA PENERIMA BANTUAN PROGRAM INDONESIA PINTAR: STUDI KASUS : SMPN 3 CIHAMPELAS Purnama Oktavia, Irma; Lestari Anggreini, Novita
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 6 (2024): JATI Vol. 8 No. 6
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i6.11241

Abstract

Pendidikan memiliki peran penting dalam meningkatkan kualitas sumber daya manusia (SDM) di Indonesia. Namun, faktor ekonomi sering kali menjadi hambatan dalam mendapatkan pendidikan yang layak. Pemerintah telah mengatasi hal ini dengan Program Indonesia Pintar (PIP), sebuah beasiswa untuk siswa kurang mampu. SMPN 3 Cihampelas merupakan salah satu penerima program ini, namun penentuan siswa penerima PIP masih menemui kendala, terutama dalam memastikan bantuan tepat sasaran. Penelitian ini bertujuan untuk mengimplementasikan algoritma Naive Bayes dalam mengklasifikasikan kelayakan siswa penerima bantuan PIP berdasarkan beberapa atribut seperti Jenis Tinggal, Alat Transportasi, Pekerjaan dan Penghasilan Orang Tua, serta penerima KPS dan KIP. Pengujian dilakukan menggunakan perangkat lunak RapidMiner dan teknik Cross Validation. Hasil penelitian menunjukkan tingkat akurasi sebesar 97.24%, precision 72.73%, recall 88.89%, dan nilai AUC 0.886, yang dikategorikan sebagai Good Classification. Sehingga dapat disimpulkan, bahwa algoritma ini dapat diimplementasikan dengan sangat baik untuk mendukung pengambilan keputusan terkait penerima bantuan PIP di SMPN 3 Cihampelas.
SYSTEM DESIGN FOR CALCUALTING THE NUMBER AND DENSITY OF MOTORCYCLES IN PARKING AREA BASED ON BACKGROUND SUBTRACTION METHOD Muhammad Yusuf Fadhlan; Auliya Rahmawati; Novita Lestari Anggreini
Jurnal Media Elektrik Vol. 21 No. 2 (2024): MEDIA ELEKTRIK
Publisher : Jurusan Pendidikan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/metrik.v21i2.1536

Abstract

There are still issues with a number of students parking their vehicles improperly in the parking spaces provided. This causes suboptimal parking capacity due to a lack of information about parking capacity. In recent years, at a certain library, vehicle detection has been implemented using a Gaussian mixture model algorithm using a Raspberry Pi. However, this library does not provide information about the density status of the parking area. Therefore, an information system was created to determine the level of density of the parking area based on the ratio of vehicles entering and exiting compared to the maximum capacity of the parking area. The system uses the Gaussian mixture model algorithm with the machine learning method of background subtraction MOG2, which can calculate the number of vehicles based on the difference between objects and the background of objects, using test data in the form of videos recorded using a camera positioned horizontally to the entrance and exit lanes of the parking area. This research resulted in an accuracy of 89.7% for Video1TA, precision of 93.2%, a crowded parking area density level, and a value of 129.12. Video2TA had a value of 101.08, precision of 100%, and accuracy of 90%, while Video3TA had an accuracy of 35%, precision of 56.7%, and a value of 49.48. The density levels of videos 2 and 3 are the same, indicating that the parking area is still empty. The test results show that the value can affect the system in detecting an object.
Improving Diabetes Prediction Performance Using Random Forest Classifier with Hyperparameter Tuning Anggreini, Novita Lestari; Yuliana, Ade; Ramdan, Dadan Saepul; Al-Dayyeni, Wissam
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4755

Abstract

Diabetes mellitus is a chronic metabolic disorder that poses a serious challenge to global healthcare systems due to its increasing prevalence and the high costs associated with treatment. Although machine learning has been widely adopted to support early diagnosis, many predictive models still underperform due to limited preprocessing strategies and inefficient hyperparameter settings. This study proposes a comprehensive machine learning pipeline to enhance diabetes prediction accuracy by utilizing a Random Forest classifier optimized through systematic hyperparameter tuning. The novelty of this method lies in its integrated approach, which includes thorough preprocessing such as removing duplicate records, handling inconsistent unique values, addressing missing data, and applying the SMOTE technique to overcome class imbalance. Additionally, hyperparameter tuning is conducted using GridSearchCV combined with 5-fold cross-validation, and only the most influential features are selected to improve model interpretability and efficiency. The proposed model achieved an accuracy of 95 percent, with a recall of 0.88 and an F1-score of 0.85, indicating its robustness in identifying diabetic cases more effectively than previous studies using standard machine learning algorithms. This model contributes to the development of a reliable and scalable early detection system for diabetes, applicable in clinical decision support environments. Further refinement can be achieved by testing on larger and more diverse datasets or by implementing more efficient tuning techniques such as Bayesian optimization.
A Hybrid LSTM–Smith Waterman Model for Personalized Semantic Search in Academic Information Systems Yuliana, Ade; Anggreini, Novita Lestari; Iskandar, Rachmat; Prasanth, G. Rafi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4763

Abstract

The growing complexity of digital learning environments presents a critical challenge in computer science, particularly in designing intelligent academic systems capable of delivering context-aware and personalized content. Traditional academic information systems often rely on literal keyword matching, failing to interpret the semantic intent behind user queries and ignoring historical learning behavior. This study addresses these limitations by proposing a hybrid semantic search and recommendation model that integrates Long Short-Term Memory (LSTM) networks with the Smith Waterman algorithm. The LSTM component models temporal sequences of user interactions, while Smith Waterman enables local semantic alignment between user queries and learning content. Historical query logs and user-clicked topics are transformed into semantic vectors, which are further enhanced through a contextual graph and semantic relation matrix. Experimental results demonstrate the model’s effectiveness, achieving 89% accuracy, an F1-score of 0.89, and an AUROC of 0.88 by epoch 50. The hybrid architecture successfully captures the evolution of user interest and semantic relevance, outperforming baseline approaches. This research contributes to the field of computer science by bridging natural language understanding and sequential modeling to improve adaptive learning technologies. The proposed model offers a scalable foundation for developing intelligent recommendation systems in academic platforms, fostering improved learner engagement and efficiency.
ANALISIS SENTIMEN OPINI WARGANET TERHADAP PENDIDIKAN MILITER BAGI PELAJAR MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE Fitrah, Nuzul Karimah; Anggreini, Novita Lestari
ZONAsi: Jurnal Sistem Informasi Vol. 7 No. 3 (2025): Publikasi artikel ZONAsi: Jurnal Sistem Informasi Periode September 2025
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/4ggj4c78

Abstract

Perkembangan media sosial, khususnya TikTok, telah menjadi ruang diskusi publik yang sarat opini terkait berbagai isu sosial dan kebijakan pemerintah. Salah satunya adalah program pendidikan militer bagi pelajar di Jawa Barat yang menimbulkan pro dan kontra di kalangan masyarakat. Penelitian ini bertujuan untuk menganalisis sentimen warganet terhadap program tersebut dengan mengklasifikasikan opini ke dalam kategori positif, negatif, dan netral. Data komentar diperoleh melalui crawling menggunakan APIfy TikTok Scraper dengan total 1.147 komentar. Tahapan penelitian meliputi preprocessing teks (case folding, cleansing, tokenisasi, stopword removal, stemming, dan normalisasi), ekstraksi fitur menggunakan TF-IDF, serta klasifikasi menggunakan algoritma Support Vector Machine (SVM) [1]. Hasil penelitian menunjukkan bahwa sentimen netral mendominasi sebesar 70,1%, disusul sentimen positif sebesar 28,6%, dan negatif hanya 1,3%. Evaluasi model menghasilkan tingkat akurasi yang baik, sehingga SVM terbukti efektif dalam menganalisis opini warganet berbasis teks di media sosial. Temuan ini diharapkan dapat menjadi masukan bagi pemerintah, khususnya dalam mengevaluasi kebijakan pendidikan militer, sekaligus memperkaya kajian penerapan analisis sentimen di bidang kebijakan publik.
PERANCANGAN DAN IMPLEMENTASI SISTEM INFORMASI PENJUALAN, PEMBELIAN DAN PERSEDIAAN BERBASIS WEB (STUDI KASUS ARI JAYA MOTOR CIPARAY) Anggreini, Novita Lestari; Andiva, Anindita Nur
Journal of Economics, Accounting, Tax, and Management (JECATAMA) Vol 2 No 1 (2023): JECATAMA
Publisher : Unit Penelitian dan Pengabdian kepada Masyarakat Politeknik TEDC Bandung Jl. Pesantren Km 2 Cibabat Cimahi Utara, Cimahi 40513 Jawa Barat, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70428/jecatama.v2i1.673

Abstract

Tugas Akhir ini berjudul “Perancangan dan Implementasi Sistem Informasi Penjualan, Pembelian dan Persediaan Berbasis Web (Studi Kasus Ari Jaya Motor Ciparay)” yang bertujuan untuk menganalisis, merancang, mengimplementasikan dan menguji sistem informasi penjualan, pembelian dan persediaan pada Ari Jaya Motor Ciparay. Metode penelitian yang digunakan adalah metode deskriptif, metode ini menjelaskan kenyataan yang terjadi berdasarkan fakta yang bersumber dari data primer dan data sekunder serta menggunakan jenis data kualitatif dan kuantitatif. Adapun metode pengumpulan data yang digunakan adalah observasi, wawancara, dan studi kepustakaan. Perancangan sistem informasi ini menggunakan bahasa pemrograman web dengan database PHPMyAdmin dan Mysql. Dengan metode pengembangan sistem yang digunakan yaitu metode waterfall (air terjun) menggunakan cara pendekatan yang sistematis, dimulai dari analisis, perancangan, pengujian dan implementasi, serta pengujian sistem ini menggunakan metode black box. Sistem informasi yang telah dibuat untuk Ari Jaya Motor Ciparay dapat menjadi solusi atas permasalahan yang terjadi, juga sebagai alat bantu dalam proses kegiatan transaksi penjualan dan pembelian juga input data barang, sehingga menghasilkan laporan penjualan, pembelian dan persediaan yang dapat mengatasi masalah pencatatan, stok barang yang tidak terkontrol, kesulitan dalam mencari barang yang dapat diatasi dengan sistem informasi ini. Selain itu, sistem informasi ini memiliki pengendalian hak akses pada menu login yang berfungsi untuk melindungi keamanan data, karena menu utama yang ditampilkan untuk setiap pengguna akan berbeda-beda. Maka dapat disimpulkan, sistem informasi penjualan, pembelian dan persediaan berbasis web telah berjalan dengan baik.
PERANCANGAN DAN IMPLEMENTASI SISTEM INFORMASI PENERIMAAN DAN PENGELUARAN KAS BERBASIS WEB PADA DAYKLIN LAUNDRY Anggreini, Novita Lestari; Ramdan, Dadan Saepul; Miliani, Fera
Journal of Economics, Accounting, Tax, and Management (JECATAMA) Vol 3 No 2 (2024): JECATAMA
Publisher : Unit Penelitian dan Pengabdian kepada Masyarakat Politeknik TEDC Bandung Jl. Pesantren Km 2 Cibabat Cimahi Utara, Cimahi 40513 Jawa Barat, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70428/jecatama.v3i2.1008

Abstract

The purpose of this study is to analyse, design and also implement a Cash Receipt and Expenditure Information System at Dayklin Laundry Service Company. The research methodology uses descriptive methods and the data collection techniques used are field studies and library research data, the type of data uses quantitative and qualitative as well as secondary and primary data sources. The programming language used in this information system is web-based and MYSQL as the database. The system development method used is waterfall and system testing using black box. The information system that has been implemented functions as a system development from the use of simple bookkeeping to the desktop-based processing of cash receipts and disbursements. The function of this system is to overcome the problems that exist in Dayklin Laundry, among others, managing the calculation of cash receipts and disbursements and can maintain data security so that it is not known by all parties who have limited user access rights from this system, which are adjusted to the company policies. Based on the results of black box testing, the system, which is 98% up and running, is considered to be good.
Co-Authors Ade Yuliana Al-Dayyeni, Wissam Albaar, Sy Nur Qamaria Alya Shafira, Salma Andiva, Anindita Nur Aqmal Mulqy Bagja Laksana Ari Sudrajat Aris Haris Rismayana Auliya Rahmawati Ayu Hendrati Rahayu Castaka Agus Sugianto Diky Fermana Dini Rohmayani Fitrah, Nuzul Karimah Hasbi Nur Ichsan Heldi Akbar Kosasih Heri Abijono Ichsan Perdana Putra Ichsan, Hasbi Nur Indra Budi Iskandar, Rachmat Miliani, Fera Muhammad Ridwan Muhammad Yusuf Fadhlan Nia Ekawati Nia Ekawati Nia Ekawati, Nia Nuhgraha, Yoddy Agung Prasanth, G. Rafi Pujilestari, Intan Puput Santoso Purnama Oktavia, Irma Ramdan, Dadan Saepul Ratna Rizky Wulandari Risman, Riski Shandy Tresnawati Shandy Tresnawati Shandy Tresnawati Tresnawati, Shandy Tri Pratiwi Olivia Riska Bokings