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All Journal TEKNIK INFORMATIKA Teknika: Jurnal Sains dan Teknologi JOIV : International Journal on Informatics Visualization JRSI (Jurnal Rekayasa Sistem dan Industri) Academica : Journal of Multidisciplinary Studies Jurnal Pendidikan dan Konseling Jurnal Varian eProceedings of Engineering SmartComp The Indonesian Journal of Computer Science IJoICT (International Journal on Information and Communication Technology)
Dita Pramesti
Universitas Telkom
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Public Sentiment and GoTo Stock Price Movement in Indonesia: A Null-Relationship Study Using Naïve Bayes and Non-Parametric Measures Pramesti, Dita; Fakhrurroja, Hanif; Karina M., Rahma
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: 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.v18i2.46447

Abstract

The expiration of the lock-up period for PT GoTo Gojek Tokopedia Tbk's shares led to a sharp stock price decline and public discourse on Twitter. This study aims to examine the statistical relationship between public sentiment and GoTo’s stock price movement in Indonesia. Tweets were classified into positive or negative sentiment using the Naïve Bayes classifier, selected for its computational efficiency on large-scale textual data. The model achieved 70% accuracy, with a precision of 82% and F1-score of 75%. The sentiment polarity was then compared with stock trends across 39 distinct trading periods using four non-parametric statistical tests: Chi-Square (p = 0.6398), Cramer’s V (0.014), Goodman-Kruskal’s Lambda (0.053), and Mann-Whitney U test (p = 0.8994). None of these tests showed a statistically significant association between sentiment polarity and stock price movement. These findings highlight that while public sentiment may reflect short-term public interest, it does not reliably capture the market’s behavioral dynamics—especially in cases of investor decisions driven by broader macroeconomic or institutional factors. Sentiment data, therefore, should be considered as a complementary, rather than primary indicators in stock price analysis.
Back-End Development of an Interactive Dashboard with Real-Time API Integration for Chili Plant Monitoring in Precision Agriculture Azwar Farrel Wirasena; Hanif Fakhrurroja; Dita Pramesti
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 2: 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.v18i2.46450

Abstract

  This research focuses on the development of an interactive web-based dashboard to support a precision agriculture system for chili plants. The primary focus of this research is on the back-end development of the system. The system integrates several internal and external APIs, including the Flask API (internal) for plant disease classification and growth prediction, and the Google Gemini API for the AI-powered chatbot that provides consultation to farmers (external). These features allow farmers to receive automatic disease diagnosis and growth predictions, improving decision-making and crop management. The dashboard also presents weather information, environmental data, and nanobubble data, along with Echarts gauge charts for seven essential metrics: Electrical Conductivity (EC), temperature, humidity, pH, nitrogen, phosphorus, and potassium. Data for the environmental and nanobubble data is retrieved from the ThingSpeak API (external), while weather information is fetched from the OpenWeatherMap API (external). The system was thoroughly tested using Postman to ensure all API endpoints function correctly. The results confirmed that all endpoints responded with status code 200 OK, indicating stable back-end performance. Performance testing showed response times stabilizing at 2000 ms after initial 4500 ms peaks, confirming efficient handling, reliable endpoints, and deployment readiness.
A Mobile Application Development for Monitoring Cash Transfer Program for MSMEs in Indonesia Dita Pramesti; M. Rizal Bimantoro; Fitria Dewi Wulandari; Pradita Cahyani
Jurnal Rekayasa Sistem & Industri Vol 9 No 01 (2022): Jurnal Rekayasa Sistem & Industri
Publisher : School of Industrial and System Engineering, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jrsi.v9i01.544

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play an important role in improving Indonesia’s economicgrowth that has been slowing down during the Covid-19 pandemic, an outbreak that significantly affectedthe national economy. MSMEs contribute 60.51% to Gross Domestic Product (GDP) of Indonesia andabsorb 96.29% of Indonesia’s workforce. In order to boost national economic recovery and growth, thegovernment is stimulating the growth in MSMEs by providing Bantuan Langsung Tunai (BLT) or CashTransfers for MSMEs. In practice, however, there are various problems in relation to the distribution of CashTransfers, such as illegal fees, corruption, misappropriation of funds, and mistargeting. In this paper, wepropose a mobile application design that can be a solution to all those problems. The application is designedto provide easy access for users to submit proposals and track the progress, with the result that the cash isdelivered efficiently and quickly to intended beneficiaries. This is an effort to promote openness andtransparency in public administration and also to prevent corruption that can occur in delivery of cash. Thisapplication, namely “Sumbangsih”, applies a prototype method as the System Development Life Cycle(SDLC), which consists of six phases: planning, analysis, design, implementation, testing, and maintenance.In the final phase, after the application is created, testing is carried out using User Acceptance Test (UAT)to verify that every function of the application is working exactly as required.
Rancang Bangun Website Perpustakaan Digital Untuk Alternatif Perpustakaan Konvensional Menggunakan Metode Extreme Programming Kusuma, Kemal Indra; Andreswari, Rachmadita; Pramesti, Dita
eProceedings of Engineering Vol. 10 No. 2 (2023): April 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak—Perpustakaan merupakan tempat umum untuk mencari buku atau sekedar mencari referensi. Namun semenjak virus covid menyebar di seluruh dunia pada tahun 2019, pemerintah menutup semua tempat umum untuk mencegah penyebaran virus salah satunya perpustakaan. Dikarenakan oleh hal ini banyak masyarakat umum bingung bagaimana cara untuk membaca buku secara gratis dalam keadaan virus COVID-19 masih berkeliaran. Oleh karena itu diperlukan suatu solusi agar masyarakat masih dapat membaca buku secara gratis seperti pada perpustakaan umum. Solusi tersebut ialah membuat suatu website yang berisikan buku digital sehingga masyarakat umum dapat membaca buku kapan saja dan dimana saja tanpa harus keluar rumah. Metode pengembangan website akan menggunakan salah satu metode agile, yaitu extreme programming (XP). Metode extreme programming (XP) cocok diterapkan pada projek berskala kecil dan hanya membutuhkan satu sampai tiga orang saja. Selain metode pengembangan diperlukan juga metode evaluasi untuk menguji kelayakan website. Metode evaluasi yang akan digunakan ada dua yaitu blackbox testing untuk menguji antar muka dan fungsi website dan load testing untuk menguji kapasitas website pada beberapa pengguna. Hasil dari pengujian tersebut akan dijadikan saran untuk pengembangan lebih lanjut agar website menjadi lebih efektif.Kata kunci— web, extreme programming, blackbox testing, load testing
Penerapan Metode Iterative Incremental Dalam Pengembangan Website Tripinaja Untuk Meningkatkan Pelayanan Dan Proses Bisnis Maulana Purbaya, Andre; Fauzi, Rahmat; Pramesti, Dita
eProceedings of Engineering Vol. 10 No. 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak — Perkembangan teknologi di masa sekarang sangat pesat sehingga mempermudah berbagai kegiatan atau pekerjaan yang harus dilakukan terutama pada sektor wisata. Perkembangan aplikasi berbasis website khususnya pada bagian wisata menjadi suatu kemudahan tersendiri untuk masyarakat, karena membantu untuk melakukan pemesanan tiket berlibur tanpa harus datang ke stasiun atau bandara. Perkembangan tersebut juga berdampak kepada aplikasi Tripinaja karena aplikasinya masih menggunakan platform pemendek link seperti linktree. Hal ini berdampak kepada proses bisnis dan pelayanan yang diberikan kepada customer. Oleh karena itu peneliti mengembangkan sebuah aplikasi berbasis website untuk membantu meningkatkan pelayanan dan proses bisnis pada startup Tripinaja. Pengembangan aplikasi ini menggunakan salah satu metode pengembangan agile yaitu iterative incremental. Penggunaan metode ini bertujuan untuk membuat aplikasi dengan cepat namun tetap menyesuaikan dengan umpan balik yang diberikan oleh pengguna. Sehingga aplikasi yang dibuat dapat menyesuaikan perubahan yang terjadi dan dapat diterima oleh masyrakat. Hal ini telah dibuktikan dengan tes atau evaluasi menggunakan metode UAT kepada 15 calon pengguna dengan masing masing bobot penilaiannya adalah 4 point. Aplikasi yang dikembangan mendapatkan skor sebesar 81% yang artinya aplikasi ini dapat diterima dan digunakan oleh masyarakat.Kata kunci— travel,iterative incremental,websit
Students Demography Clustering Based on The ICFL Program Using K-Means Algorithm Andreswari, Rachmadita; Fauzi, Rokhman; Izzati, Berlian Maulidya; Widartha, Vandha Pradwiyasma; Pramesti, Dita
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1916

Abstract

Independent Campus, Freedom to Learn (ICFL) Program is one of the manifestations of student-centered learning. This program can help students reach their full potential by allowing them to pursue their passions and talents. This study aims to see how the segmentation of students participating in the ICFL program is based on demographic data. This research is based on survey responses from students participating in the ICFL program. The method used in this study is input data preparation, pre-processing, data cleansing, and data analysis. The information will be pre-processed before being utilized and evaluated. To help produce better outcomes in data clustering, the K-Means clustering approach is used, which is processed using the Python computer language. The data is clustered using the K-Means clustering approach based on gender characteristics, Grade Point Average (GPA), university entrance selection, ICFL category, and year or semester when participating in ICFL. This study resulted in three clusters with each of its criteria. The dominant gender is found in clusters 2 (100% female) and 3 (100% male). Software Development was the most popular ICFL category among students in cluster 1, accounting for 67%, while Design and Analysis Information Systems was the most popular in clusters 2 and 3. The most dominant ICFL program is found in three clusters. ICFL - Internship program in which at least 40% of participants come from each cluster. The research results are expected to assist stakeholders in evaluating the implementation of the ICFL program.  
Identification of Mirai Botnet in IoT Environment through Denial-of-Service Attacks for Early Warning System Rahmatulloh, Alam; Muhammad Ramadhan, Galih; Darmawan, Irfan; Widiyasono, Nur; Pramesti, Dita
JOIV : International Journal on Informatics Visualization Vol 6, No 3 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.3.1262

Abstract

The development of computing technology in increasing the accessibility and agility of daily activities currently uses the Internet of Things (IoT). Over time, the increasing number of IoT device users impacts access and delivery of valuable data. This is the primary goal of cybercriminals to operate malicious software. In addition to the positive impact of using technology, it is also a negative impact that creates new problems in security attacks and cybercrimes. One of the most dangerous cyberattacks in the IoT environment is the Mirai botnet malware. The malware turns the user's device into a botnet to carry out Distributed Denial of Service (DDoS) attacks on other devices, which is undoubtedly very dangerous. Therefore, this study proposes a k-nearest neighbor algorithm to classify Mirai malware-type DDOS attacks on IoT device environments. The malware classification process was carried out using rapid miner machine learning by conducting four experiments using SYN, ACK, UDP, and UDPlain attack types. The classification results from selecting five parameters with the highest activity when the device is attacked. In order for these five parameters to be a reference in the event of a malware attack starting in the IoT environment, the results of the classification have implications for further research. In the future, it can be used as a reference in making an early warning innovative system as an early warning in the event of a Mirai botnet attack.
Desain User Experience dan User Interface Website “Nufish” Menggunakan Metode Design Thinking dan Extreme Programming Putri, Natasya Kusuma; Fauzi, Rahmat; Pramesti, Dita
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 1 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i1.4637

Abstract

Di masa pandemi Covid-19, distribusi di sektor perikanan mengalami kesulitan. Berdasarkan survei pendahuluan, pemasaran hasil perikanan di Kabupaten Klaten belum optimal dan stabil. Oleh karena itu menurut Kementerian Kelautan dan Perikanan, hal ini menyebabkan penumpukan ikan 70% pada tahun 2020. Berdasarkan permasalahan tersebut, penelitian ini akan menganalisis kebutuhan untuk membuat user experience dan desain user interface untuk website NuFish. Selain itu, evaluasi desain yang telah dibuat menggunakan metode cognitive walkthrough dan skala usability sistem. Pemikiran desain dan pemrograman ekstrem digunakan dalam mengembangkan situs web NuFish. Penelitian ini menghasilkan desain prototype high fidelity yang nantinya akan diujicobakan pada pengguna. Kemudian untuk hasil kelayakannya, digunakan skala usability sistem berdasarkan skala likert. Website NuFish di bagian penjual mendapat skor rata-rata 77, skor B, peringkat baik dan dapat diterima, sedangkan di bagian pembeli kisaran penerimaan rata-rata adalah 78,5, skor B, peringkat baik dan dapat diterima. Dari hasil yang telah dijelaskan, dapat disimpulkan bahwa website NuFish cocok untuk masyarakat sebagai platform untuk membantu para pembudidaya ikan dan UMKM memasarkan hasil perikanannya.
Pengembangan Marketplace “Nufish” Berbasis Web Untuk Meningkatkan Pemasaran Hasil Perikanan Menggunakan Metode Extreme Programming Rusmana, Intan Akbar; Fauzi, Rahmat; Pramesti, Dita
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 1 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i1.4635

Abstract

Pandemi COVID-9 menyebabkan stok ikan menumpuk sehingga berdampak pada rendahnya daya beli masyarakat sehingga menyebabkan harga ikan turun. Berdasarkan wawancara yang dilakukan dengan para pembudidaya ikan di Desa Nganjat, banyak pembudidaya ikan yang kesulitan mendistribusikan produknya secara luas. Hal ini dikarenakan pendistribusian masih dilakukan secara tradisional, dan pemanfaatan teknologi yang masih belum optimal. Berdasarkan permasalahan tersebut, penelitian ini akan merancang dan mengembangkan marketplace berbasis website untuk membantu para pembudidaya ikan dalam kegiatan jual beli dan mendistribusikan produknya kepada konsumen. juga merancang fitur-fitur yang dibutuhkan di sisi penjual dan pembeli. Proses pengembangan aplikasi menggunakan pendekatan Agile dengan metode Extreme Programming. Pengembangan aplikasi menghasilkan aplikasi marketplace NuFish berbasis website. Fitur yang dibangun digunakan untuk kegiatan jual beli, terbagi menjadi dua sisi yaitu pihak penjual dan pihak pembeli. Hasil evaluasi dengan pengujian black box menyatakan bahwa sistem telah berjalan sesuai dengan yang diharapkan. Pada uji penerimaan pengguna, persentasenya adalah 71,57%. Pengujian beban pada kondisi 50, 100, dan 150 pengguna dan periode ramp-up 600 detik memiliki waktu respons rata-rata kurang dari 1 detik dan menghasilkan lebih dari 10 permintaan/detik.
Association Analysis Between Public Sentiment and Grab Stock Performance Using SVM and Lambda Test Dita Pramesti; Hanif Fakhrurroja; Rahma Karina M.
IJoICT (International Journal on Information and Communication Technology) Vol. 11 No. 1 (2025): Vol. 11 No. 1 Jun 2025
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v11i1.9152

Abstract

During a period of strong economic performance in Indonesia—marked by a 5.4% growth in the second quarter of 2022—concerns about a potential downturn in the fourth quarter began to surface, as indicated by increased stock market volatility, including fluctuations in Grab’s share prices. This study aims to classify public sentiment toward Grab based on comments from the social media platform Twitter, and to analyze its relationship with the direction of the company’s stock price movement. Sentiment classification was conducted using the Support Vector Machine (SVM) algorithm through a series of steps including data preprocessing, TF-IDF weighting, imbalance data handling, and model performance evaluation. The dataset was split into 70% training data and 30% testing data. The SVM model achieved an accuracy of 87%, with a precision of 90%, recall of 91%, and F1-score of 91%. Public sentiment for each period was then aggregated using the Net Sentiment Score (NSS), which was subsequently categorized into positive or negative sentiment. These sentiment categories were analyzed in relation to stock price movements using the Goodman-Kruskal Lambda test. The result of ????(stock∣sentiment)=0.053 indicates that knowing public sentiment reduces prediction error by only 5.3%, while ????(sentimen|saham)=0.000 shows no predictive value in the opposite direction. This study contributes a novel approach by integrating machine learning-based sentiment classification with a categorical association test, specifically applied to a regional technology company in Southeast Asia, which remains underexplored in existing literature.
Co-Authors Aditya Zhafir Dhiaulhaq Alam Rahmatulloh Alfis Salam Azwar Farrel Wirasena Berlian Maulidya Izzati Fa'rifah, Riska Yanu Fakhrurroja, Hanif Fauzan , Daffa Surya Fauzi, Rokhman Fitria Dewi Wulandari Ilham Perdana Indah Nur Fitri Astuti Intan Akbar Rusmana Irfan Darmawan Karina M., Rahma Kusuma, Kemal Indra M. Rizal Bimantoro Maharani, Anggi Kusuma Maulana Purbaya, Andre Mufti, Afrizal Muhammad Ramadhan, Galih Muhammad Rizal Bimantoro Natasya Kusuma Putri Nur Widiyasono, Nur Pariswara, Endar Poedjimartojo, Naufal Avilandi Pradita Cahyani Pratama, M Fajri Bryan Putri, Natasya Kusuma Rachmadita Andreswari Rahma Karina M. Rahmat Fauzi Rahmat Fauzi Rusmana, Intan Akbar Taufik Nur Adi Vandha Pradwiyasma Widartha