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All Journal Prosiding Semnastek Indonesian Journal on Software Engineering (IJSE) Jurnal Teknik Komputer AMIK BSI Paradigma Bina Insani ICT Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Jurnal Mantik JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Infortech JPM: JURNAL PENGABDIAN MASYARAKAT Journal of Informatics Management and Information Technology KLIK: Kajian Ilmiah Informatika dan Komputer Reputasi: Jurnal Rekayasa Perangkat Lunak IMTechno: Journal of Industrial Management and Technology JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Administrasi Kantor Info Abdi Cendekia Journal of Accounting Information System Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Komtika (Komputasi dan Informatika)
Titik Misriati
Universitas Bina Sarana Informatika
Religion Aerospace Engineering Humanities Astronomy Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Public Health Social Sciences Transportation Other

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Sistem Informasi Rekomendasi Izin Parkir dengan Metode Agile pada Dinas Perhubungan Kota Bekasi Titik Misriati; Riska Aryanti; Oktaviyani Oktaviyani
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 10, No 4 (2022)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v10i4.49804

Abstract

Parkir merupakan salah satu hal yang penting pada lalu lintas terutama bagi pengemudi yang memiliki kendaraan. Terutama pada saat pengemudi sudah sampai di titik pemberhentian yang dituju, pengemudi membutuhkan lokasi parkir untuk dapat meninggalkan kendaraan yang dimiliki dengan aman dan nyaman. Namun kadang kala, pengemudi tidak dapat menemukan lokasi parkir yang tepat sehingga pengemudi melakukan parkir di lokasi yang tidak semestinya. Lokasi parkir ini dimanfaatkan oleh pengelola parkir tanpa izin resmi dan tidak mengikuti aturan dari pemerintah daerah. Pengelolaan izin parkir di Kota Bekasi dilakukan oleh Dinas Perhubungan Kota Bekasi. Proses pengelolaan izin parkir masih dilakukan secara konvensional dimana pemohon datang langsung ke Dinas Perhubungan Kota Bekasi untuk mengajukan permohonan rekomendasi izin parkir dengan membawa berkas sesuai dengan ketentuan yang ditetapkan. Akibatnya data yang diinformasikan antara Dinas Perhubungan dan Pemohon tidak sinkron sehingga menyebabkan pemohon harus kembali lagi untuk menyerahkan kekurangan data. Penelitian ini meggunakan metode Agile untuk merancang sistem informasi rekomendasi izin parkir. Hasil dari analisis ini menyatakan bahwa Sistem Informasi Rekomendasi Izin Parkir dapat mengoptimalkan proses pengelolaan izin parkir menjadi lebih cepat dan data yang dihasilkan menjadi lebih akurat.
Analisis Sentimen Aplikasi Primaku Menggunakan Algoritma Random Forest dan SMOTE untuk Mengatasi Ketidakseimbangan Data Riska Aryanti; Titik Misriati; Asriyani Sagiyanto
Journal of Computer System and Informatics (JoSYC) Vol 5 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i1.4562

Abstract

The Primaku application is an application that can be used as a tool to monitor the growth of children under five, this application can be used to collect data on the growth of children under five, apart from that this application can also provide clear information and visualization about the growth of children under five, including nutritional status and growth development In accordance with the standards that have been set, the Primaku application can help parents or health workers in routinely monitoring the growth of children under five and early detecting the potential risk of stunting. Stunting is a growth disorder that occurs in children under five due to malnutrition which is characterized by the child's height. which is shorter than the age standard. Stunting can have a long-term impact on a child's quality of life, such as disrupting physical, cognitive and social development, as well as increasing the risk of chronic disease in adulthood. The primaku application has been widely used, more than 500,000 users have downloaded this application and 44,700 reviews have been given by users to this application, however, reading all the reviews may take time, but if there are few reviews read, then the review results will be biased. Therefore, sentiment analysis aims to overcome this problem by automatically grouping user reviews into positive and negative reviews. Therefore, research on toddler growth detection to determine the public's response to the Primaku application can be of great benefit in efforts to prevent stunting in children under five in Indonesia. In this research, the random forest algorithm with the SMOTE technique was used to carry out sentiment analysis of Primaku application reviews. The random forest algorithm is a machine learning algorithm based on decision trees. The SMOTE technique is used to overcome data imbalance problems and is able to reduce overfitting while increasing the performance of the Random Forest algorithm. The data used in this research is Primaku application review data obtained from scrapping results from the Google Play Store. This data contains comments from application users, namely positive and negative. The results of this sentiment analysis show a deep understanding of user perceptions of the Primaku application. This sentiment analysis can be a basis for further improvement and development of the Primaku application, with a focus on aspects that influence user satisfaction and the research results show that the random forest algorithm with the SMOTE technique can produce quite good accuracy in sentiment analysis of the Primaku application. obtained in this study was 88%.
PENERAPAN METODE WATERFALL PADA PEMBELIAN BAHAN BAKU PRODUKSI PT. CAM JAYA ABADI Ningsih, Rahayu; Istiqomah, Amelia; Yusnaeni, Wina; Misriati, Titik
Jurnal Infortech Vol 2, No 1 (2020): Juni 2020
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (609.667 KB) | DOI: 10.31294/infortech.v2i1.8104

Abstract

Dalam era globalisasi sekarang ini ilmu pengetahuan dan teknologi informasi berkembang dengan sangat cepat. Membuat perusahaan harus mencari cara agar tetap mampu bersaing didalam dunia bisnis, PT. Cam Jaya Abadi adalah perusahaan yang bergerak dibidang pembuatan palet kayu,furniture, exterior dan interior yang telah berpengalaman dibidang perkayuan. Pembelian bahan baku yang berjalan di PT. Cam Jaya Abadi masih sangat sederhana dari mulai proses permintaan barang sampai dengan pembuatan laporan. Dengan sistem yang ada tersebut sering terjadi kesalahan pada persediaan barang, kehilangan dokumen dikarenakan penyimpanan dokumen transaksi yang tidak baik, dan sering terjadi kesalahan informasi pada proses pembayaran. Dari beberapa permasalahan yang ada, maka peneliti memberikan solusi yaitu dengan merancang sebuah sistem informasi pembelian bahan baku dengan metode Waterfall , design menggunakan UML (Unifield Modeling Language) dan pembuatan aplikasi dengan Java Neatbeans 7.1. Metode tersebut dipergunakan untuk mempermudah proses pembelian bahan baku tersebut, dapat mempersingkat waktu kerja karyawan, dapat menghasilkan data yang akurat, dan dapat dibuat laporan pembelian perbulannya.
Pemanfaatan Teknologi Informasi Bagi Ibu-Ibu PKK RW 09 Prima Harapan Regency Bekasi Misriati, Titik; Nurajizah, Siti; Sugiarto, Hari; Maria, Vivi
Info Abdi Cendekia Vol. 6 No. 2: Desember 2023
Publisher : Lembaga Penelitian Universitas YARSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33476/iac.v6i2.104

Abstract

PKK RW 09 Prima Harapan Regency menghadapi kurangnya pengetahuan dan keterampilan TI. Untuk mengatasi permasalahan tersebut, sebuah pendekatan holistik dan terstruktur diusulkan. PKK RW 09 Prima Harapan Regency memerlukan pelatihan dan pengembangan pengetahuan dan keterampilan TI sehingga anggota PKK RW 09 dapat memahami dan menggunakan teknologi dengan lebih efektif. Melalui implementasi pendekatan tersebut, diharapkan PKK RW 09 Prima Harapan Regency dapat mencapai berbagai capaian yang positif sehingga dapat meningkatkan efisiensi dalam menjalankan tugas-tugas PKK, Pelatihan pemanfaatan teknologi dan informasi pada PKK RW 09 Prima Harapan Regency dapat memberikan peningkatan dan pengetahuan 86% sehingga mampu mengoptimalkan manfaat TI dan meningkatkan kualitas pemberdayaan kesejahteraan keluarga di lingkungan PKK RW 09 Prima Harapan Regency.
Optimisasi Model Deep Learning untuk Deteksi Penyakit Daun Tebu dengan Fine-Tuning MobileNetV2 Aryanti, Riska; Agustiani, Sarifah; Wildah, Siti Khotimatul; Arifin, Yosep Tajul; Marlina, Siti; Misriati, Titik
Journal of Informatics Management and Information Technology Vol. 4 No. 4 (2024): October 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v4i4.411

Abstract

Sugarcane leaf diseases are a serious threat in sugarcane farming because they can significantly reduce productivity and can cause major losses in yields if not detected early. Therefore, fast and accurate disease management is needed to prevent further losses. This study aims to develop a deep learning model based on MobileNetV2 with fine-tuning techniques to effectively detect sugarcane leaf diseases. Fine-tuning is a method used to adjust the parameters of a pre-trained model on a more specific target dataset. The dataset contains images of sugarcane leaves that have been classified per class based on the type of disease. In this study, fine-tuning was performed on the MobileNetV2 architecture that had been previously trained using the sugarcane leaf dataset. The fine-tuning process was carried out by rearranging the top few layers of MobileNetV2 and adding a special classification layer to predict the class of sugarcane leaf diseases. The model was trained through two stages: initial training to obtain a baseline performance and fine-tuning by opening several layers of MobileNetV2. In the initial evaluation, the model achieved a validation accuracy of 93.12%. After fine-tuning, the accuracy increased to 95.01%, indicating that this technique was able to significantly improve disease detection capabilities. The results of this study provide important contributions in the field of agriculture, especially in supporting the sustainability of sugarcane production through artificial intelligence-based technology. The implementation of the proposed model is expected to help farmers detect diseases more quickly and take timely preventive measures, thereby reducing losses.
Klasifikasi Multi Label untuk Deteksi Keseimbangan Emosi Pengguna Media Sosial Menggunakan K-Fold Cross Validation Misriati, Titik; Aryanti, Riska; Sagiyanto, Asriyani; Fachri, Muhamad; Ramadhani, Arya
Journal of Information System Research (JOSH) Vol 6 No 1 (2024): Oktober 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i1.6033

Abstract

Social media has grown in popularity, with millions of people using it to engage with and share information worldwide. Social media, in addition to serving as a communication tool, are crucial for expressing the emotions and feelings of users. The widespread use of social media has had a significant impact on people's emotions. In particular, negative emotions are frequently experienced and can have a significant impact on mental health. This study aimed to analyze multiple classification models to discover the optimal model for detecting emotional balance among social media users. The classification models utilized in this study include the K-Nearest Neighbor, Random Forest, Support Vector Machine, Decision Tree, and AdaBoost to identify the best classification model capable of detecting the emotional balance of social media users. Several classification models are applied and compared with the aim of evaluating model performance. This research project employed K-fold cross-validation to evaluate the categorization model by comparing various k values. The Random Forest algorithm achieved the greatest accuracy of 99.90% at a K-Fold cross validation value of 10 and an Area Under the Curve (AUC) value of 100%. Thus, this study successfully found a reliable model for accurately detecting emotions of social media users, which is expected to contribute to the development of mental well-being monitoring systems on social media platforms.
Optimalisasi Random Forest dan Support Vector Machine dengan Hyperparameter GridSearchCV untuk Analisis Sentimen Ulasan PrimaKu Misriati, Titik; Aryanti, Riska
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5347

Abstract

PrimaKu App has been a pioneer in the field of digital health since 2017. Through this application, parents can regularly and continuously monitor their children’s health and development. PrimaKu also has a formal alliance with the Indonesian Pediatric Association (IDAI) to promote child health in Indonesia. This application can be downloaded through the Google Play Store. Google Play Store has a feature that allows users to review the app before downloading. Sentiment analysis is used to distinguish between positive and negative reviews by users who have provided reviews so that an evaluation of the services provided can be made. This research aims to conduct sentiment analysis of user reviews of the PrimaKu application using Random Forest (RF) and Support Vector Machine (SVM) algorithms with TF-IDF weighting. Optimization was performed using hyperparameters to improve the performance of the Random Forest and SVM algorithms. The data used consisted of the 2,293 most relevant reviews collected from the Google Play Store. The most effective models for the Random Forest and Support Vector Machine were selected by adjusting the hyperparameters using GridSearch CV. The results of this study show that Random Forest has a higher success rate in classifying PrimaKu user review data, with an accuracy of 89%, precision of 88%, recall of 81%, and F1-Score of 85%.
Soft Voting Based Optimized Ensemble for Migraine Type Classification Misriati, Titik; Aryanti, Riska; Leidiyana, Henny
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 6 No. 3 (2025): Volume 6 Number 3 September 2025
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v6i3.861

Abstract

The accurate classification of migraine subtypes is a complex challenge in neurology, hindered by symptomatic similarities between types. This complexity necessitates advanced computational tools to support diagnostic precision. This study aims to develop and evaluate an optimized soft voting ensemble classifier to automate this multi-class classification task effectively. The methodology involved training eight base models—including Neural Network, Random Forest, and Gradient Boosting—on a publicly available migraine dataset, with an 80-20 train-test split. The top three performers were integrated into a soft voting ensemble, which aggregates their predicted probabilities to enhance decision robustness. Model performance was rigorously assessed using accuracy, precision, recall, F1-score, and AUC-ROC metrics. The results demonstrated that the proposed ensemble achieved superior performance, with an accuracy of 91.67% and an F1-score of 91.50%, outperforming all constituent models. Furthermore, the ensemble attained near-perfect AUC-ROC values across multiple classes, confirming its strong discriminatory capability. The study concludes that the soft voting ensemble is a highly effective and reliable approach for migraine subtype classification, offering significant potential as a decision-support tool in clinical environments. Future work will focus on hyperparameter optimization, explainability, and validation with larger multi-centric datasets to facilitate clinical adoption.
Optimalisasi Pengelolaan Keuangan melalui Digitalisasi Pencatatan pada Usaha Mikro dan Kecil Misriati, Titik; Setyaningsih, Eka Dyah; Aryanti, Riska
JPM: Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v6i2.2744

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in driving the local economy, including in the city of Bekasi. However, the main challenge faced by MSME players is their low capacity to manage and record finances effectively. Most business owners still use manual recording methods, which risk errors, data loss, and difficulties in analyzing financial conditions. In addition, the lack of separation between business and family finances causes uncertainty in profit and loss calculations and capital planning. The lack of knowledge about the use of digital financial applications is also a significant obstacle. This community service activity aims to empower MSMEs in Bekasi City to move up the ladder through digital innovation in financial recording. The partners in this activity are MSMEs in the Bekasi City area that have not yet implemented a digital recording system. The implementation method includes stages of needs analysis, financial literacy training, assistance in using digital recording applications, and evaluation of the level of understanding through pre-tests and post-tests. The results of the activity show an average increase in understanding and application of digital financial management of 80%. Business owners have become more disciplined in recording transactions, able to separate business and personal finances, and understand profit and loss calculations more accurately. In addition to its economic impact, this activity has also fostered social change in the form of the Bekasi Digital MSME community, which serves as a platform for continuous learning. Digital innovation has proven effective in increasing the professionalism and competitiveness of MSME players towards a technology-based economic transformation.
Perancangan Sistem Informasi Arus Kas Pada PKBM Ratu Kencana Misriati, Titik; Alfarizi, Salman; Aryanti, Riska; Martenia, Rina
JAIS - Journal of Accounting Information System Vol. 3 No. 1 (2023): Juni
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jais.v1i03.1634

Abstract

Sistem pengelolaan arus kas pada PKBM Ratu Kencana masih dilakukan secara manual. Kondisi tersebut dapat mempengaruhi kinerja serta tata kelola laporan keuangan pada PKBM Ratu Kencana. Pembuatan laporan arus kas masih belum terkontrol dengan maksimal, misalnya dalam menangani proses penerimaan kas penulisan data masih menggunakan buku besar yang harus ditulis tangan kemudian di input ulang di Microsoft Excel. Sedangkan untuk mencatat pengeluaran kas yang ada pada PKBM Ratu Kencana harus ditulis tangan di buku pengeluaran kas, kemudian di input ulang di aplikasi SIMDAK (Sistem Informasi Dana Alokasi Khusus Kemendikbud) sesuai RKAS (Surat Rencana Kegiatan Dan Anggaran Sistem Pendidikan). Metode pengembangan software yang digunakan dalam pembuatan website penerimaan dan pengeluaran arus kas pada PKBM Ratu Kencana Karawang menggunakan waterfall mulai dari analisis kebutuhan perangkat lunak, desain, pembuatan kode program, dan pengujian. Untuk mengatasi permasalahan tersebut, peneliti merancang sistem pemasukan kas dan pengeluaran kas serta pembuatan laporan menggunakan aplikasi berbasis website. Penggunaan aplikasi berbasis website dapat mempermudah dalam kegiatan administrasi berupa pencatatan penerimaan maupun pengeluaran kas, untuk melakukan pencatatan bisa langsung diinputkan melalui aplikasi berbasis web serta memudahkan bendahara dalam pembuatan laporan untuk meminimalisir terjadinya kesalahan, dan memudahkan dalam pencarian data.
Co-Authors Agustiani, Sarifah Aldian Mauluda Amanda Subhi Pertiwi Arie Kurniawan Arifin, Yosep Tajul Asriyani Sagiyanto ASRIYANI SAGIYANTO, ASRIYANI Eka Dyah Setyaningsih Fachri, Muhamad Fachry Abda El Rahman Handayani Meilisa Hari Sugiarto - UBSI Haryani Henny Leidiyana Ida Zuniarti Ida Zuniarti, Ida Instianti Elyana Instianti Elyana Istiqomah, Amelia Maria, Vivi Martenia, Rina Mohammad Afdhol Rizal Muhammad Arif Sulistiyo Nadhifah, Rifda Nadhifah, Rifda Norma Yunita Nurvi Oktiani Oktaviyani Oktaviyani Rahayu Ningsih Rahayu Ningsih Rahmat Hidayat Rahmat Hidayat Rahmat Hidayat Rahmawati Rahmawati Ramadhani, Arya Rina Martenia Riska Aryanti SALMAN ALFARIZI Sari Hartini, Sari Siti Khotimatul Wildah Siti Marlina Siti Marlina, Siti Siti Nurajizah Sri Ariyati Widiarina . Widiarina, Widiarina Wina Yusnaeni Yoseph Tajul Arifin