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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu dan Teknologi Kelautan Tropis IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Informatika JURNAL SISTEM INFORMASI BISNIS Proceedings of KNASTIK Jurnal Simetris Elkom: Jurnal Elektronika dan Komputer Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta INOVTEK Polbeng - Seri Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Aptisi Transactions on Management Aptisi Transactions on Technopreneurship (ATT) Magisma: Jurnal Ilmiah Ekonomi dan Bisnis JUKANTI (Jurnal Pendidikan Teknologi Informasi) JATI (Jurnal Mahasiswa Teknik Informatika) Journal Sensi: Strategic of Education in Information System Abdimasku : Jurnal Pengabdian Masyarakat INFOKUM Aiti: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Jurnal Dimensi DKV Seni Rupa dan Desain Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Eduvest - Journal of Universal Studies CENDEKIA PENDIDIKAN Jurnal Rekayasa elektrika Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pendidikan Teknologi Informasi (JUKANTI) INTERNAL (Information System Journal) Pendekar: Jurnal Pendidikan Berkarakter Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics BACA: Jurnal Dokumentasi dan Informasi International Journal of Information Technology and Business JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Danny Manongga
Universitas Kristen Satya Wacana
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Neuroscience Social Sciences Transportation Other

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ALGORITHM COMPARISON AND FEATURE SELECTION FOR CLASSIFICATION OF BROILER CHICKEN HARVEST Christian Cahyaningtyas; Danny Manongga; Irwan Sembiring
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 6 (2022): JUTIF Volume 3, Number 6, December 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.6.493

Abstract

Broiler chickens are the result of superior breeds that produce a lot of meat. In practice, however, many breeders experience crop failure, which has a serious impact on the economy and can also affect farmer quality, resulting in sanctions. The value of the performance index produced at harvest indicates the success rate of harvesting broiler chickens. Broiler crop yield data can be used to help classify broiler crop yield data using an approach method. The CRISP-DM (Cross Industry Standard Process for Data Mining) method was used in this study's data mining technique. This study compares 3 classification algorithms to determine the best algorithm and 3 feature selection methods to determine the best method for improving algorithm performance. According to the findings of this study, the Random Forest algorithm is the best algorithm for classifying harvest data, with an accuracy rate of 89.14 percent. The best way to improve the algorithm's performance is to use the Backward Elimination method, which can increase the accuracy by 7.53 percent. As a result, the Random Forest + Backward Elimination algorithm yields an accuracy value of 96.67 percent. According to this study, the factors that influence crop yield increase are FCR, number of harvests, and body weight.
Analisis Terhadap Tagar #LGBT di Twitter Menggunakan Analisis Jaringan Sosial (SNA) Erwianta Gustial Radjah; Ade Iriani; Daniel H.F. Manongga
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5476

Abstract

Twitter is utilized to express opinions and respond to social phenomena in real life. Responses to events through Twitter conversations are relatively fast and create popular topics. Popular topics using hashtags are often used to attract, invite and influence other users to respond as well. In May 2022, the hashtag "#LGBT" was widely discussed, which was due to the invitation of a gay couple to attend a podcast by Youtuber Deddy Corbuzier. This resulted in a decrease in Deddy Corbuzier's subscribers and the blocking of one of the TikTok accounts of a gay couple. This study aims to analyze opinions on social media that influence the decisions of other social media users. Negative impacts on content creators and affects the real-life community of religious Indonesians. An analysis of network structure, group, and actors involved was conducted using Social Network Analysis to detect and study the opinions that occurred. Network structure mapping of Density, Diameter, and Reciprocity. Group detection using Modularity and Centrality to identify influential actors. Crawling Dataset of 10,000 tweets with 7,761 nodes (actors) and 8,371 edges. The results of the network structure research showed the farthest distance to reach other accounts is 18 (Diameter), the low-Density value is 0.000164 and the low Reciprocity value between accounts is 0.049480. The results of the research show that the value of the group formed is relatively high, 0.868000. Centrality identification shows @brn as the account with the most connections of 287 and @sop as the account with the highest intermediary among other accounts at 0.000303, and @aiy as the account with the closest distance to other nodes at 1.0. Based on the quality of the node to other nodes, @brn is the highest at 1.0
Covid-19 Sentiment Analysis Using Convolutional Neural Network / Reccurent Neural Network Method Ravensca Matatula; Danny Manongga; Hendry Hendry
Eduvest - Journal of Universal Studies Vol. 2 No. 8 (2022): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1819.418 KB) | DOI: 10.59188/eduvest.v2i8.514

Abstract

Social media is a very important tool in this modern era , one of which is namely twitter. Twitter allows user for give opinion / opinion to various issues and topics hot / viral trending . Trending on twitter is so so fast in the process of spreading so that Twitter becomes a medium of information that often become a media issue conspiracy . Covid-19 is a moderate epidemic / disease _ experienced the whole world when this . Issues circulating in the population , they believe that Covid-19 is a real pandemic and a conspiracy , issue this make population confused differentiate Among second issue that . Because of that required a fast and accurate analysis _ for produce valid results , that Covid-19 a real thing _ or conspiracy seen from opinion population and corner views written on Twitter. CNN/RNN or combined from RNN(LSTM) and CNN methods are method used _ for classify opinion population about Covid-19 issues . Study this also done with compare is correct RNN/CNN accuracy same like deep RNN even more fast for in the process . Research results state that accuracy from combined RNN/CNN no different remote , even RNN/CNN in the process more fast than deep RNNs. Research results about opinion / opinion residents on twitter who believe about Covid-19 is conspiracy more low than residents who have confidence about Covid-19 is something the real thing . Percentage classification opinion / opinion from sentiment positive by 63.15% and opinion / opinion sentiment negative by 28.60%, this is results calculation use RNN/CNN method , with accuracy reached 58%. Accuracy from method used _ make Covid-19 issues that exist in the population no Becomes hoax news so population more alert against the ongoing Covid-19 pandemic happen.
Analysis Sentiment On Airline Customer Saisfaction Using Reccurent Neural Network Astriyer J. Nahumury; Danny Manongga; Ade Iriani
Eduvest - Journal of Universal Studies Vol. 2 No. 10 (2022): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (299.157 KB) | DOI: 10.59188/eduvest.v2i10.594

Abstract

When talking about customer satisfaction, Twitter as a large and great media could be used to get sentiment or opinion on a product and service of a business. The sentiment will be in a form of tweet that was posted on Twitter that referred to hot debated issues subjectively. The tweet data then will be processed using machine learning to analyze the sentiment of a certain topic. This study aimed to analyze the sentiment of Indonesian public on one of the Indonesian airlines using Deep Learning, Recurrent Neural Network (RNN) method based on the training for Long Short-Term Memory (LSTM), validation and prediction. The tweet will be selected in the span of three years (2017-2020) through the triangulation sentence sentiment process. The LSTM model gives a result of 98.5% accuracy and 92.2% validation accuracy in the data training. Whereas, the LSTM model’s data testing gives a result of 56.5% negative sentiment higher than the positive and neutral sentiment. It could be assumed that the factors which affect the negative sentiment could be used as an input to improve any business process
Analisis Sentimen Ulasan Aplikasi Tripadvisor Dengan Metode Support Vector Machine, K-Nearest Neighbor, Dan Naive Bayes Antonius Mbay Ndapamuri; Danny Manongga; Ade Iriani
Jurnal Inovtek Polbeng Seri Informatika Vol 8, No 1 (2023)
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/isi.v8i1.3260

Abstract

Penelitian ini bertujuan untuk mengklasifikasikan review pada aplikasi Tripadvisor yang terdapat pada Google Playstore berbasis Word Cloud dan Visual Network Explorer dengan algoritma Support Vector Machine (SVM), K-Nearest Neighbor (K-NN), dan Naïve Bayes. Tahapan penelitian dimulai dengan pengumpulan data sebanyak 1.000 data yang diperoleh dengan menggunakan teknik Web Scraping, kemudian tahap Preprocessing data dan dilanjutkan dengan model klasifikasi menggunakan SVM, K-NN, dan Naïve Bayes. Berikutnya evaluasi model dengan hasil SVM memperoleh akurasi tebaik 89,8%. Tahap terakhir analisis visual menggunakan Visual Word Cloud dan Visual Network Explorer untuk mendapatkan informasi keputusan pengguna dalam memberikan Review positif dan negatif. Keluhan yang sering muncul seperti aplikasi jelek, aplikasi lumayan, hapus aplikasi, aplikasi error, aplikasinya tolong diperbaiki, aplikasi membuat hp jadi lemot karna sering update. Untuk mengatasi masalah tersebut diharapkan pihak aplikasi Tripadvisor agar lebih meningkatkan kinerja aplikasi dengan melakukan update dari segi penggunaan aplikasi agar mengatasi masalah yang dialami para pengguna.
Analisis Strategis e-Business untuk Strategi Pemasaran dan Penjualan Rimes Jopmorestho Malioy; Danny Manongga
AITI Vol 20 No 1 (2023)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v20i1.111-124

Abstract

Electronic business (e-business) merupakan sebuah aktivitas bisnis yang dilakukan dengan memanfaatkan pendekatan teknologi informasi. Dengan e-business maka perusahaan dapat mengetahui seluruh proses dan perkembangan di perusahaan. Selain itu pemilik perusahaan juga dapat membuat sebuah keputusan berdasarkan analisis e-business dari perusahaan. Pada penelitian ini dibuat sebuah analisis strategi e-business pada home industry yaitu Toko XYZ. Penelitian ini menggunakan metode dan tools untuk analisis, yaitu analisis SWOT, politik, ekonomi, sosial, teknologi (PEST), Porter’s five forces model, Value chain, dan critical success factor (CSF). Hasil penelitian ini adalah diidentifikasinya beberapa sistem informasi yang berpotensi pada Toko XYZ, guna meningkatkan strategi e-business untuk proses pemasaran maupun penjualan. Sistem informasi tersebut antara lain Sistem Informasi Penjualan berbasis CRM, Sistem Informasi Managemen Keuangan, Sistem Informasi Karyawan, Sistem Informasi Pergudangan, dan Sistem Informasi Geografis.
PENGGUNAAN TEKNOLOGI INFORMASI DALAM PENGELOLAAN KEUANGAN BADAN USAHA MILIK DESA (BUMDES) BERGAS KIDUL SEJAHTERA Suharyadi Suharyadi; Ade Iriani; Danny Manongga; Hendry Hendry; Sutarto Wijono
Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Vol. 3 No. 3 (2023)
Publisher : Universitas Kristen Satya Wacana Salatiga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/jms.v3i32023p417-427

Abstract

Badan Usaha Milik Desa Bergas Kidul Sejahtera adalah Badan Usaha yang terletak di desa Bergas Kidul, Kecamatan Bergas kabupaten Semarang. Dalam proses pengelolaan keuangannya menghadapi kendala yaitu keterbatasan kemampuan Sumder Daya Manusia yang mengelola keuangan. Program pengabdian masyarakat yang diakukan ini bertujuan untuk memberikan pelatihan penggunaan Teknolgi Informasi dalam hal ini memaksimalkan kemampuan Microsoft Excel untuk pengelolaan laporan keuangan. Metode pelaksanaan program antara lain adalah perencanaan, analisa kebutuhan, persiapan program, pelaksanaan program. Hasil yang dicapai adalah kemampuan sumber daya BUMDes dapat bertambah dalam hal penggunaan fungsi-fungsi akuntansi yang dimiliki oleh Microsoft Excel. .
Analisis Klasterisasi Kerawanan Gempa Bumi di Provinsi Papua Menggunakan Algoritma Invasive Weed Optimization (IWO) Lorna Yertas Baisa; Danny Manongga; Yessica Nataliani
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 2 (2023): Volume 9 No 2
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i2.65312

Abstract

Gempa bumi adalah fenomena alam yang sering terjadi di Indonesia, termasuk di Provinsi Papua. Untuk mengurangi risiko dampak gempa bumi, diperlukan analisis untuk mengidentifikasi daerah-daerah yang rawan terha  dap gempa bumi. Penelitian ini bertujuan untuk menganalisis klasterisasi kerawanan gempa di Provinsi Papua menggunakan algoritma Invasive Weed Optimization (IWO). Metode ini dipilih karena dapat menghasilkan klaster yang lebih baik dibandingkan dengan algoritma klasterisasi lainnya. Data yang digunakan adalah data kejadian gempa di Provinsi Papua yang terdiri dari atribut latitude, longitude, magnitude, dan depth mulai tahun 2018 sampai Februari 2023 yang diperoleh dari website Badan Geologi Amerika Serikat yaitu United States Geological Survey (USGS). Tahapan penelitian meliputi normalisasi data, klasterisasi menggunakan algoritma IWO, dan evaluasi hasil klasterisasi menggunakan SSE dan F-Measure. Jumlah klaster terbaik yang dihasilkan oleh metode Elbow yaitu sebanyak enam klaster kerawanan gempa di Provinsi Papua, yang diberi label Sangat Tidak Rawan, Tidak Rawan, Kurang Rawan, Cukup Rawan, Rawan dan Sangat Rawan. Dengan nilai parameter sinitial sebesar 8, algoritma IWO menghasilkan nilai SSE dan F-Measure terkecil dibanding nilai parameter sinitial lainnya, yaitu masing-masing sebesar 19.1002 dan 0.5137. Evaluasi hasil klasterisasi menggunakan SSE menunjukkan nilai yang baik dari 30 kali percobaan, dengan rata-rata SSE sebesar 19.218, lebih kecil dibanding dengan rata-rata SSE hasil metode k­-Means dan DBSCAN yaitu masing-masing sebesar 19.307 dan 59.910.
Knowledge Capture Menggunakan Teknik Explore, Elaborate dan Execute Untuk Bagian Kesiswaan Sekolah Victor Peter Lodewyk Duan; Danny Manongga; Ade Iriani
Jurnal Informatika: Jurnal Pengembangan IT Vol 3, No 3 (2018): JPIT, September 2018
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v3i3.1002

Abstract

Students are late to school showed a lack of awareness about discipline. The teachers who handle the student late are created the tacit knowledge. This paper applied explore, elaborate and execute technique to capture the knowledge. The purpose is to documenting and stored it as a wealth of school knowledge by create a model in knowledge capture. The model of knowledge capture can be an indicator in capturing and documenting knowledge process so it will be good impact when handling the students late. The result showed the model of knowledge capture was created based on three step explore, elaborate and execute with the factors who cause students late. The use of technology have not technofull applicable in process to capturing knowledge except in documenting and storage process, allow to presence a utilization technology design in capturing knowledge on future research.
EVALUASI KETERGUNAAN WEBSITE PERPUSTAKAAN UNIVERSITAS KRISTEN SATYA WACANA DENGAN MENGGUNAKAN METODE SYSTEM USABILITY SCALE Herdin Yohnes Madawara; Danny Manongga; Hendry Hendry
Jurnal Pendidikan Teknologi Informasi (JUKANTI) Vol 6 No 2 (2023): JURNAL PENDIDIKAN TEKNOLOGI INFORMASI (JUKANTI) EDISI NOPEMBER 2023
Publisher : Program Studi Pendidikan Informatika, Universitas Citra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37792/jukanti.v6i2.933

Abstract

This research was conducted with the aim of evaluating the usability of the Satya Wacana Christian University (UKSW) Library website using the System Usability Scale (SUS) method. This research also aims to identify areas that need to be improved in the UKSW Library website. Respondents in this study were UKSW students who had used the library website. This study used the SUS questionnaire consisting of 10 questions with a 5-point Likert scale. The results of the SUS calculation show that the average value of the usability of the UKSW Library website is 59.514, which is in the medium or "OK" category. Further analysis shows that areas that need to be improved are clarity of information, ease of navigation, and visual appearance. This research is expected to provide input for the UKSW Library in developing the website in order to increase usability and meet the needs of its users. The conclusion of this research is that the UKSW Library website still has some areas that need to be improved to increase usability.
Co-Authors Abas Sunarya, Po Abdi Samuel Mango Ade Iriani Agni Isador Harsapranata Agung Wibowo Albert Kriestian Novi Adhi Nugraha Antonius Mbay Ndapamuri Anumi, Maria Grassella April Lia Hananto Apriliasari, Dwi Astriyer J. Nahumury Ayu Sanjaya, Yulia Putri Baihaqi, Kiki Ahmad Bani, Benediktus Budhi Kristianto Budi Santoso Cahyaningtyas, Christian Daniawan, Benny Dendy Kurniawan Destiyani, Gati Devianto, Yudo Dwi Hosanna Bangkalang Efendy, Rifan Eko Nur Hermansyah Eko Sediyono Elfira Umar Elmanda, Vonda Erwianta Gustial Radjah Evangs Mailoa Evi Maria Faturahman, Adam Fauzi Ahmad Muda Filimdity, Elsa K. Frederik Samuel Papilaya Girinzio, Iqbal Desam Gunawan Gunawan Henderi Hendry Hendry, - Henry Adhi Sulistyo Herdin Yohnes Madawara Hindriyanto Dwi Purnomo Huda, Baenil I Ketut Suada Irwan Sembiring Iwan Setiawan Iwan Setyawan Johan Jimmy Carter Tambotoh Joko Siswanto Julianingsih, Dwi Julians, Adhe Ronny Krismiyati Kristoko Dwi Hartomo Lorna Yertas Baisa Lukman Santoso Madawara, Herdin Yohnes Mango, Abdi Samuel Mangoki, Willson Martza Merry Swastikasari Muhamad Yusup Muhammad Ryza Awwali , Sulartopo, Muhammad Ryza Awwali , Nina Setiyawati Panja, Eben Penidas Fiodinggo Tanaem Penidas Fodinggo Tanaem Perdana, Eric Megah Po Abas Sunarya Priatna , Wowon Pudjajana, Andre Maureen Pukada, Michael Alan Hirdi Purbaratri, Winny Purnomo, Hendryanto Dwi Qurotul Aini Radius Tanone Rahardja.,M.T.I.,MM, Dr. Ir. Untung Ravensca Matatula Ravensca Matatula Reni Veliyanti Rimes Jopmorestho Malioy Rivort Pormes Rivort Pormes Rivort Pormes, Rivort Ronny Julians, Adhe Saian, Septovan Dwi Suputra Santoso, Joseph Teguh Santoso, Nuke Puji Lestari Selfiana Pandie Sri Yulianto Joko Prasetyo Stefanus Christian Relmasira Suharyadi Sulistyo, Henry Adhi Sutarto Sutarto Sutarto Wijono Swastikasari, Martza Merry Theopillus J. H. Wellem Tri Wahyuningsih Tukino Tukino, Tukino Untung Rahardja Victor Peter Lodewyk Duan Winny purbaratri Wiwien Hadikurniawati Yari Dwikurnaningsih Yerik Afrianto Singgalen Yessica Nataliani