Garuda - Garba Rujukan Digital

Django Framework and Python-Gammu as Middleware SMS Broadcast Cahyo, Puji Winar; Wicaksono, Arief Ikhwan
Compiler Vol 8, No 1 (2019): Mei
Publisher : Sekolah Tinggi Teknologi Adisutjipto Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (630.077 KB)

Because the growing of mobile technology in recently days, technology practitioners are required to be able to create a variety of devices and media that support the mobile technology. Application developers compete to create mobile applications that have a variety of features, including video call, voice sending, image sending or text messaging. Developing of mobile applications have an impact on using of Short Message Service, although using of Short Message Service began to shift, but the Short Message Service feature cannot be abandoned, because Short Message Service is a standard feature carried by mobile devices (mobile phones). For this reason, we need to develop Short Message Service Broadcast middleware as an intermediary for Short Message Service communication between web technology and mobile devices. This technology is using for disseminating information between systems that have been built with mobile devices via Short message service. Broadcast system will produce information about new student admissions, That will be received directly by Senior High School Students through their mobile phones. The Middleware can send message broadcast in real time to more than 500 cellular numbers automatically with an average time of 13 seconds for one message. The advantage of using this technology is direct configuration with Python Back-End. Meanwhile, Technology for message inbox still requires further configuration.

Clustering User Characteristics Based on the influence of Hashtags on the Instagram Platform Muhammad Habibi; Puji Winar Cahyo
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 13, No 4 (2019): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.50574

Instagram is a social media that has the potential to be used to increase awareness of a product. Approximately 70% of users spend their time searching for a product on Instagram. Many people promote their products with a lack of attention to the target. So that not infrequently the information distributed is inaccurate information and not following user characteristics. This study aims to cluster the characteristics of Instagram users based on hashtag compatibility. The method used in this study is the K-Means Clustering method. Based on the results of the experiment, this research succeeded in clustering Instagram users based on the hashtag match on the text caption. Besides, TF-IDF can be used as a feature suitable for the K-Means Klastering method. The results of the hashtag "#kopi" analysis resulted in hashtag suggestions that can be used for the promotion of a product related to coffee, including the hashtag #coffeeshop and #coffee with total usage of 14968 captions.

Clustering followers of influencers accounts based on likes and comments on Instagram Platform Puji Winar Cahyo; Muhammad Habibi
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 2 (2020): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.53028

The promotion of goods or services is now facilitated by the dissemination of information through Instagram. Dissemination of information is usually done by influencers or promotional accounts. The account used certainly has a lot of followers. Because of the large amount of follower data in that account, it can be grouped into the same characters. This is done to determine the potential for promotion using social media accounts. This study uses data from 2 popular accounts. The first account is an artist with the username ayutingting92. The second account is Infounjaya, the official promotion account from Jenderal Achmad Yani University, Yogyakarta. The results of grouping can divide follower data into two cluster groups with different interactions. The basic difference between the two groups is the number of likes and comments. The infounjaya account analysis results showed that of 4,906 followers, only 3,211 followers were actively involved in the interaction, 1,695 followers were passive followers who did not like or did not comment on the interaction. Meanwhile, the results of the ayutingting92 follower cluster show that out of 1 million sample data followers, only 13,591 followers were actively involved in the interaction of likes and comments, 986,409 were passive followers.

Entity Profiling to Identify Actor Involvement in Topics of Social Media Content Puji Winar Cahyo; Muhammad Habibi
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 14, No 4 (2020): October
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.59869

The efficiency of using social media affected modern society's nature and communication; they are more interested in talking through social media than meeting in the real world. The number of talks on social media content depends on the topic being discussed. The more topic interesting will impact the amount of data on social media will be. The data can be analyzed to get the influence of actors (account mentions) on the conversation. The power of an actor can be measured from how often the actor is mentioned in the conversation. This paper aims to conduct entity profiling on social media content to analyze an actor's influence on discussion. Furthermore, using sentiment analysis can determine the sentiment about an actor from a conversation topic. The Latent Dirichlet Allocation (LDA) method is used for analyzes topic modeling, while the Support Vector Machine (SVM) is used for sentiment analysis. This research can show that topics with positive sentiment are more likely to be involved in disaster management accounts, while topics with negative sentiment are more towards involvement in politicians, critics, and online news.

Django Framework and Python-Gammu as Middleware SMS Broadcast Puji Winar Cahyo; Arief Ikhwan Wicaksono
Compiler Vol 8, No 1 (2019): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Because the growing of mobile technology in recently days, technology practitioners are required to be able to create a variety of devices and media that support the mobile technology. Application developers compete to create mobile applications that have a variety of features, including video call, voice sending, image sending or text messaging. Developing of mobile applications have an impact on using of Short Message Service, although using of Short Message Service began to shift, but the Short Message Service feature cannot be abandoned, because Short Message Service is a standard feature carried by mobile devices (mobile phones). For this reason, we need to develop Short Message Service Broadcast middleware as an intermediary for Short Message Service communication between web technology and mobile devices. This technology is using for disseminating information between systems that have been built with mobile devices via Short message service. Broadcast system will produce information about new student admissions, That will be received directly by Senior High School Students through their mobile phones. The Middleware can send message broadcast in real time to more than 500 cellular numbers automatically with an average time of 13 seconds for one message. The advantage of using this technology is direct configuration with Python Back-End. Meanwhile, Technology for message inbox still requires further configuration.

A social network analysis: identifying influencers in the COVID-19 vaccination discussion on twitter Muhammad Habibi; Puji Winar Cahyo
Compiler Vol 10, No 2 (2021): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Social media analytics, especially Twitter, has experienced significant growth over the last few years. The data generated by Twitter provides valuable information to many stakeholders regarding user behavior, preferences, tastes, and characteristics. The presence of influencers on social media can invite interaction with other users. An influencer can affect the speed of spreading information on social media. This study looks at the influence of influencers and information dissemination channels on Twitter data related to COVID-19 vaccination in Indonesia as one of the hot Twitter discussion trends. This study applies Social Network Analysis (SNA) as a theoretical and methodological framework to show that interactions between users have differences on the network when the analyzed tweets are divided into mention and retweet networks. This study found that the key accounts in disseminating information related to Covid-19 vaccination were dominated by official accounts of government organizations and online news portals. The official Twitter account of government organizations turns out to have an essential role in disseminating information related to COVID-19 vaccination, namely the @KemenkesRI account belonging to the Ministry of Health of the Republic of Indonesia and the @Puspen_TNI account belonging to the TNI Information Center.

Geographical Information System of Disaster Victims Location Using Web-Based and Mobile Application Puji Winar Cahyo; Naufal Asyhab; Ahmad Subhan Yazid; Muhammad Taufiq Nuruzzaman
IJID (International Journal on Informatics for Development) Vol. 3 No. 2 (2014): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Disasters that have occurred in the city of Yogyakarta, causing no casualties were relatively few. Result of the many victims of the disaster led to the spread of location affected to some areas. Then it takes the system is fast in the submission of data in each affected area. Method of UML (Unified Modeling Language) is used to build this system, the method UML is focused in the development of object-oriented systems, suitable for use in android programming, CodeIgniter PHP framework that accommodates the library Google Map. Mobile apps (android) is used as a client that handles input data disaster victims, Geographic Information Systems (GIS) as a server whose job is to receive and data mapping disaster victims. Coordinator unit rescue can send disaster relief information notice to each member through a GIS that has been communicated to the SMS Gateway (Short Message Service). Geographic Information System of Disaster Victims Location Using Web-Based and Mobile Application built to help control aid disaster victims, especially accuracy in mapping location of the disaster victims, because it uses a GPS (Global Positioning System) to determine the coordinates of disaster victims.

Internet of Things pada Dashboard Informasi Kandang Jangkrik Qurnia Dwi Yoga Putra; Puji Winar Cahyo
IJAI (Indonesian Journal of Applied Informatics) Vol 5, No 1 (2020)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v5i1.44488

Abstrak :Kondisi lingkungan sering berubah-ubah membuat kondisi hewan ternak menjadi kurang produktif, terutama pada hewan ternak jangkrik. Selain dipengaruhi kondisi lingkungan yang berubah-ubah dan tidak menentu, penurunan hasil ternak jangkrik dipengaruhi oleh suhu dan kelembaban. Suhu yang ideal untuk ternak jangkrik ini berada pada kisaran 20°C-32°C. Sedangkan untuk kelembaban kandang berada pada kisaran 65%-80%. Untuk itu perlu alat untuk mengukur suhu dan kelembaban kandang jangkrik yang dapat mengawasi keadaan serta mengetahui kondisi kandang jangkrik itu sendiri sehingga dapat meningkatkan kualitas produksi jangkrik.Berdasarkan permasalahan tersebut dibuat sistem monitoring ternak jangkrik. Dimana sistem ini dapat melakukan penyiraman secara otomatis jika suhu kandang jangkrik terlalu panas dan kandang terlalu lembab.Hasil dari penelitian ini adalah dashboard informasi kondisi kandang jangkrik dengan sensor suhu dan kelembaban. Sistem ini pada menggunakan sensor suhu, kelembaban dan perangkat water pump yang didirakit pada mikrokontroler NodeMCU. Sedangkan Informasi ditampilkan secara dashboard monitoring dengan menggunakan framework Codeigniter._____________________________Abstract :Environmental conditions often change, making conditions for livestock to be less productive, especially for crickets. Apart from being influenced by changing and erratic environmental conditions, the decline in cricket production is influenced by temperature and humidity. The ideal temperature for crickets is in the range of 20 ° C-32 ° C. Meanwhile, the humidity of the cage is in the range of 65% -80%. For that, we need a tool to measure the cricket cage's temperature and humidity that can monitor the situation and know the condition of the cricket cage itself so that it can improve the quality of cricket production.Based on these problems, a monitoring system for crickets was created. This system can do watering automatically if the cricket cage's temperature is too hot and the cage is too humid.This research made a dashboard of information on the crickets cage's condition with temperature and humidity sensors. This system uses temperature, humidity sensors, and water pump devices, which are assembled on the NodeMCU microcontroller. Meanwhile, information is displayed in a monitoring dashboard using a Codeigniter framework.

Analisis Eksploratif Berita Hoax pada Situs Cek Kebenaran Puji Winar Cahyo; Ulfi Saidata Aesyi
Jurnal Informatika Universitas Pamulang Vol 7, No 2 (2022): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v7i2.13952

The spread of fake news (hoax) through social media is currently quite difficult for the public to distinguish hoax or actual news. News can be categorized as actual if it comes from a trusted source and is supported by valid source clarification. Therefore, the news that has been spread needs to be clarified to check the truth. Currently, news checking sites are available, including turnbackhoax.id and kominfo.go.id. They have a detail of clarification data on the news classified as hoax or actual. Based on the number of online spreading hoaxes, this study seeks to create a Directory Fact Checker platform, which is a news analysis platform that can display distribution data in graphic form within a certain period of time. Exploratory data analysis was applied to hoax data in 2020. The results of the analysis show that Facebook is the first ranked social media that is often used to spread hoax news, followed by Whatsapp in second place. Meanwhile, judging from the categorization of hoaxes, Content Fabrication is the most widely spread category. Content Fabrication is a news category, 100% of the discussion is fake news. Then in the second rank, followed by the Misleading Content category, Misleading Content is a discussion of news whose contents are twisted with the aim of discrediting.

Klasterisasi Penjawab Berdasar Kualitas Jawaban pada Platform Brainly Menggunakan K-Means Puji Winar Cahyo; Landung Sudarmana
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 11, No 2 (2022): JULI
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v11i2.1314

Brainly is a Community Question Answering (CQA) educational platform that makes it easy for users to find answers based on questions posed by students. Questions from students are often answered quickly by many answerers interested in the field being asked. The number of available answers is the choice of students to be able to receive answers and give a good rating to the answerer. Based on the number of good ratings, an answerer can be said to be an expert in certain subjects. Therefore, this research focuses on finding expert answering groups who have quality answers. K-means clustering is possible to group the answering data into two different clusters. The first cluster is expert users with ten respondents, and The second cluster is a non-expert cluster with 474 respondents. The expert cluster data is expected to help the questioner to be able to ask questions directly to the experts and obtain quality answers. Meanwhile, the number of clusters is determined based on the test results using a silhouette score that obtains a value of 0.971, with the optimal number of clusters being two clusters.

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