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Journal : CogITo Smart Journal

Analisis Tingkat Kepuasan Pelanggan terhadap Layanan Grab dan Gojek di Masa Pandemi Covid-19 Jacquline Morlav S. Waworundeng; Green Sandag; stevanlee ngeloh; arlius lalong
CogITo Smart Journal Vol. 8 No. 1 (2022): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v8i1.395.111-121

Abstract

Dalam situasi wabah pandemi Covid-19, penulis tertarik untuk menganalisis tingkat kepuasan pelanggan terhadap layanan Grab dan Gojek. Tujuan dari analisis ini adalah untuk mengetahui manakah layanan yang lebih efektif dan untuk mengetahui tingkat kepuasan pelanggan terhadap layanan Grab dan Gojek. Penelitian ini dilakukan dengan membagikan kuesioner kepada 100 responden mahasiswa Universitas Klabat yang pernah menggunakan aplikasi Grab dan Gojek dengan layanan Grab Food, Grab Express, GoFood dan GoSend pada periode Desember 2020 sampai Februari 2021. Metode analisis yang digunakan yaitu deskriptif kuantitatif. Hasil analisis layanan Grab dan Gojek terkait variabel reliability, responsiveness, assurance, emphaty dan tangibles terhadap tingkat kepuasan pelanggan, menunjukkan indikator-indikator dalam penelitian ini bersifat valid dan reliabel sesuai dengan kuesioner yang dijalankan. Uji validitas dan reliabilitas menggunakan software IBM SPSS 25. Pada hasil pengukuran untuk semua variabel yaitu reliability, responsiveness, assurance, emphaty dan tangible untuk layanan Grab dengan nilai rata-rata 4.11, dinyatakan bahwa tingkat kepuasan pelanggan “puas”. Sedangkan pada hasil pengukuran varibel yang sama untuk layanan Gojek dengan nilai rata-rata 4.37, dinyatakan tingkat kepuasan pelanggan “sangat puas”. Kata kunci: Kepuasan Pelanggan, Covid 19, Grab, GoJek, Universitas Klabat
Analisis Sentimen Tweet Kuliah Online menggunakan Naïve Bayes Classifier Jacquline Morlav S. Waworundeng; Green Arther Sandag; Reynoldus Andrias Sahulata; Godlife Davidson Rellely
CogITo Smart Journal Vol. 8 No. 2 (2022): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v8i2.414.371-384

Abstract

Online lecture is an alternative learning method during the Covid-19 pandemic. There are opinions with pro and contra of the learning method. The purpose of this study is to evaluate the tweets of opinion or sentiment retrieved from social media Twitter regarding online lectures among the Indonesian community. Twint is used to collect the data tweet and Jupyter notebook is for text preprocessing and classification. The processes started with scraping data from Twitter, text preprocessing, and text classification. Using the Naïve Bayes classifier shows the performance has a precision value of 100%, an accuracy value of 70.8%, an F-measure of 10.2%, and a recall value of 5.4%. Performance rating can be affected by the dataset used for modeling. This analysis covers the positive sentiment and negative sentiments toward online lectures and the result shows 69% negative sentiments and 31% positive sentiments. The negative sentiments had a higher percentage compared to positive sentiments. The results were also supported by the word cloud which expressed a high frequency of negative words such as sleep problems, bored, tired, dizzy, difficult and lazy. So, it is concluded that during the Covid-19 pandemic from August 1, 2020, to May 31, 2021, Twitter users in Indonesia had negative sentiments about online lectures.
Analisis Sentimen Masyarakat Terhadap Exchange Tokocrypto Pada Twitter Menggunakan Metode LSTM Green Arther Sandag; Jacquline Waworundeng
CogITo Smart Journal Vol. 8 No. 2 (2022): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v8i2.418.411-421

Abstract

The internet has played an important role in influencing all human activities in today's technological era. With the internet can be used for various purposes, including sharing knowledge, transacting, socializing, shopping, business, education, and many other things that can be done. While the internet is getting more and more popular, various kinds of digital transactions continue to develop, one of which is the exchange of coins for other coins which are called cryptocurrencies. Cryptocurrencies are digital assets that use strong cryptography to encrypt financial transactions, and verify asset transfers. One of the cryptocurrency exchanges for investment in Indonesia is Tokocrypto. With such enthusiasm for cryptocurrency, many Indonesians use social media such as Twitter to find information, provide opinions, as well as information. To classify public tweets on Twitter into positive and negative categories, a sentiment analysis model is needed. This study uses the Long Short Term Memory (LSTM) method, where LSTM is a neural network development that can be used for modeling time series data on Twitter users' tweets against the Tokocrypto exchange. There were 2022 positive tweets, 1632 negative tweets, and 1012 neutral tweets.
Implementation of Face Recognition in People Monitoring Access In-and-Out of Crystal Dormitory Universitas Klabat Jacquline Waworundeng; Raycle Raynold Inzaghi Suwu
CogITo Smart Journal Vol. 9 No. 1 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i1.500.156-170

Abstract

Crystal Dormitory is a dormitory in Universitas Klabat that accommodates some male students. This study aims for monitoring and minimize the entry of foreigners into the dormitory which affects the comfort and safety of boarding students. Using the prototyping model, the systems can observe the faces of students who live in the dormitory, as well as foreigners who enter the dormitory. The system performed face recognition to recognize a person’s face when the person’s face data has been stored in the dataset. The hardware in this system used a Raspberry Pi 3 which is integrated with a webcam and monitor to detect and recognize human facial images. With machine learning libraries namely TensorFlow, OpenCV, Dlib, and Haar Cascade, combine with Python programming, the system can detect and recognize human facial images. If the system detects an unfamiliar human face, then the image of that person's face will be sent via the Telegram application using the auto-send feature to notify about the unidentified person.
Design Prototype Detector of Temperature, Humidity, and Air Quality using Sensors, Microcontrollers, Solar Cells, and IoT Jacquline Waworundeng
CogITo Smart Journal Vol. 9 No. 2 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i2.542.411-421

Abstract

Environment monitoring refers to the process, tools, and techniques to observe the quality of the environment. This research discussed the prototype detector of temperature, humidity, and air quality in a scope of hardware design. The components consist of sensors, and microcontrollers with electricity and solar cells as power supplies. The sensors used a DHT22 as the temperature and humidity sensor module and the MQ135 air quality sensor module which are connected to two types of microcontrollers, namely Arduino Uno R3 and Wemos ESP32 for data processing. The prototype has a Wi-Fi modem that can provide a connection to the internet. This prototype can be used as a tool to detect and monitor the environmental changes related to temperature, humidity, and air quality whether indoors or outdoors. The prototype is designed to be integrated with IoT platforms so that data can be sent to the smartphones and then viewed by the users. With the support of the IoT platform, the value of temperature, humidity, and air quality can be monitored easily in a real-time. This design of prototype, potentially be implemented indoors or outdoors to observe the changes in the environment.
Manajemen Pembatasan Kehadiran Beribadah di Gedung Gereja Berbasis Regulasi Pemerintah Reynoldus Andrias Sahulata; Oktoverano Lengkong; Jacquline Waworundeng
CogITo Smart Journal Vol. 9 No. 2 (2023): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v9i2.571.328-339

Abstract

Indonesia adalah negara yang telah menyatakan bebas dari pandemi COVID- 19 berdasarkan Keppres Nomor 17 Tahun 2023 tentang Penetapan Berakhirnya Status Pandemi Corona Virus Disease 2019 (COVID-19) di Indonesia, tertanggal 21 Juni 2023, dan menyatakan COVID-19 menjadi penyakit endemi di Indonesia. Hal ini terlihat dalam beberapa hari belakangan ini COVID-19 RI berfluktuasi kenaikannya terlihat di beberapa tempat di Indonesia dan tidak bersifat masif, namun tidak boleh lengah untuk mengatasi pencegahan penularannya dan bentuk pencegahan penularan adalah dengan menerapkan seperti pada masa pandemi, yaitu dengan melakukan pembatasan dalam melakukan kegiatan sosial tatap muka langsung. Berdasarkan status yang dikeluarkan oleh pemerintah dari penyakit pandemi ke penyakit endemi, maka pembatasan pertemuan tatap muka dalam suatu kegiatan masyarakat menjadi cara mengatasi penyebaran varian Covid-19 RI. Penelitian ini mengatur pembatasan pertemuan peribadatan secara tatap muka bersama di dalam gedung ibadah, yang disesuaikan dengan ketentuan yang diberlakukan pemerintah pusat atau daerah dan dapat mengatur semua pertemuan peribadatan tatap muka, sehingga dapat mengendalikan semua pertemuan tatap muka sesuai dengan ketentuan pemerintah dan peribadahan dapat berlangsung dengan baik.
IoT-based Environmental Monitoring with Data Analysis of Temperature, Humidity, and Air Quality Jacquline Waworundeng
CogITo Smart Journal Vol. 10 No. 1 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i1.708.692-705

Abstract

Environment monitoring has been linked to the use of the IoT. To raise awareness for the environment, the IoT system is built as an instrument tool based on a Prototyping model with an experimental approach. The hardware consists of sensors, microcontrollers, a Wi-Fi modem, powered with solar cells, and electricity integrated with IoT platforms Blynk and ThingSpeak. The prototype detectors were installed in two different locations at the Universitas Klabat. The IoT systems can store data, display information, and send push notifications as alerts to the user’s smartphone when critical conditions emerge. In the two locations for a specified time of May 2023, the data analysis shows average temperatures are 28,39˚C and 28,44˚C, where 28˚C is the optimal value. The average humidity shows 90,18%RH and 85,28%RH. These humidity values are critical because the humidity outside 40-60%RH can significantly impact health. The average air quality shows 59,62 AQI as “moderate” and 3.7 AQI as “good”. While “good” air quality is the best, “moderate” is safe because only when a value higher than 100 is unhealthy. The IoT system can help to monitor and provide real-time information about the environmental parameters.
Prototype Design of IoT-Based Real-time Monitoring and Security System for University Server Room Waworundeng, Jacquline; Korompis, Hilkia Heart
CogITo Smart Journal Vol. 10 No. 2 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i2.800.496-509

Abstract

The server rooms consist of computing devices hosting essential data which is critical for the operation of universities. Ensuring server room environmental stability and security is vital to prevent data loss and service disruptions. This study presents the design of an IoT-based real-time monitoring and security system for university server rooms to help the IT staff monitor the conditions of the server room. The system aims to enhance server room management efficiency while mitigating risks associated with server room issues and unauthorized access. The research is conducted based on a prototyping model which integrates hardware and software. The main focus is on the construction of the prototype device as a monitoring tool to monitor the server room environment based on the sensor parameters. The prototype has sensors to detect temperature, humidity, smoke, flame, dust, and motion as well as a real-time camera to provide continuous environmental monitoring and intrusion detection. On the software side, the functional design is presented using Unified Modeling Language. Data collected by the sensors are transmitted to IoT platforms for further analysis and visualization, enabling remote monitoring and instant notifications. The research result is a hardware prototype designed with an IoT system that is potentially used to monitor the server room environment.
Sentiment Analysis and Topic Detection on Post-Pandemic Healthcare Challenges: A Comparative Study of Twitter Data in the US and Indonesia Tangka, George Morris William; Chrisanti, Ibrena Reghuella; Waworundeng, Jacquline; Maringka, Raissa Camilla; Sandag, Green Arther
CogITo Smart Journal Vol. 10 No. 2 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i2.819.561-579

Abstract

This study examines public sentiment and key topics in Twitter discussions regarding the COVID-19 vaccine and the Omicron variant in the US and Indonesia. The importance of this research lies in understanding people's changing views on vaccination, especially in light of new virus variants. Using sentiment analysis with VADER and topic modeling with Latent Dirichlet Allocation (LDA), this research analyzes 637,367 tweets from the US and 91,679 tweets from Indonesia collected over two months from January 21 to February 21, 2022. The results reveal that US discussions on vaccines are predominantly positive, while those on Omicron are mostly negative. In contrast, discussions in Indonesia are largely neutral, followed by positive sentiment. Additionally, five main topics were identified for each country, with the US showing a broader range of vaccine-related discussions. These findings suggest that while the vaccine is seen as a source of hope in both countries, factors such as literacy, socioeconomic status, and education contribute to negative sentiment and vaccine resistance.