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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Psikologika : Jurnal Pemikiran dan Penelitian Psikologi dCartesian: Jurnal Matematika dan Aplikasi JURNAL SISTEM INFORMASI BISNIS Prosiding KOMMIT Jurnal Sains dan Teknologi Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Indonesian Journal of Mathematics and Natural Sciences Jurnal Ilmiah Kursor Noetic Psychology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika Scientific Journal of Informatics Psikodimensia: Kajian Ilmiah Psikologi Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Sains Matematika dan Statistika BANGUN REKAPRIMA Proceeding of the Electrical Engineering Computer Science and Informatics MNJ (Malang Neurology Journal) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Mercumatika : Jurnal Penelitian Matematika dan Pendidikan Matematika Inquiry: Jurnal Ilmiah Psikologi BAREKENG: Jurnal Ilmu Matematika dan Terapan IJEBD (International Journal Of Entrepreneurship And Business Development) JOURNAL SPORT AREA Philanthropy: Journal of Psychology MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Evangelikal: Jurnal Teologi Injili dan Pembinaan Warga Jemaat Aptisi Transactions on Technopreneurship (ATT) Insight: Jurnal Ilmiah Psikologi Jurnal Abdi Insani Computer Science and Information Technologies Jurnal Sains dan Edukasi Sains SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Indonesian Journal of Applied Research (IJAR) Journal of Science and Science Education Yumary: Jurnal Pengabdian kepada Masyarakat JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya INJURITY: Journal of Interdisciplinary Studies Jurnal Akademik Pengabdian Masyarakat ENDLESS : International Journal of Future Studies d'Cartesian: Jurnal Matematika dan Aplikasi Tesseract: International Journal of Geometry and Applied Mathematics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) El-Qisth Jurnal hukum keluarga Islam Community Impact and Society Empowerment Journal
Adi Setiawan
Universitas Kristen Satya Wacana
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Public Health Social Sciences Transportation Other

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Pengaruh Quality Of Life Dan Religiusitas Secara Simultan Terhadap Subjective Well Being Mahasiswa Teologi Lindin Anderson; J.T. Lobby Loekmono; Adi Setiawan
Evangelikal: Jurnal Teologi Injili dan Pembinaan Warga Jemaat Vol 4, No 1 (2020): Januari
Publisher : Sekolah Tinggi Teologi Simpson

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46445/ejti.v4i1.194

Abstract

Penelitian yang dilakukan memiliki tujuan untuk mengetahui pengaruh quality of life dan religiusitas secara silmultan terhadap subjective well-being mahasiswa teologi yang bernaung dibawah Yayasan Pekabaran Injil Nusantara. Sampel penelitian adalah mahasiswa teologi Sekolah Tinggi Teologi Nusantara Salatiga dan Sekolah Tinggi Alkitab Nusatara di Malang di bawah naungan Yayasan Pekabaran Injil Nusantara (PINTA) yang berjumlah 112 mahasiswa. Teknik pengumpulan data menggunakan teknik sampel jenuh. Alat pengumpulan data menggunakan tiga skala yaitu skala kepuasan hidup, skala quality of life dan religiusitas. Analisis data menggunakan analisis regresi berganda dengan hasil nilai F = 39,716 pada p = 0,000 (p<0,05), dan R2= 0,422. Melaui uji two ways anova didapatkan hasil quality of life dan religiusitas secara simultan berpengaruh signifikan terhadap subjective well-being mahasiswa teologi yang berada dibawah naungan Yayasan Pekabaran Injil Nusantara (PINTA). The research carried out aims to determine the influence of quality of life and religiously against subjective well-being simultaneously of theological students under the foundation of the Gospel of Nusantara. The research samples are the theological students of the NusantaraTheological College Salatiga and Nusantara Bible Seminary in Malang under the foundation of the Gospel of Nusantara (PINTA), amounting to 112 students. Data collection techniques using saturated sample techniques. Data collection tools use three scales of life satisfaction scale, quality of life scale, and religiosity. Data analyzed by multiple regression analysis with the result of the value F = 39.716 at p = 0.000 (P < 0.05), and  R2= 0.422. Through the test, two ways ANOVA showed that quality of life and religiosity significantly influences the subjective well-being by simultaneously of theological students who are under the foundation of the Gospel of  Nusantara (PINTA).
Analisis Perbandingan Karakteristik Laju Inflasi mtm Kota-Kota di Jawa Tengah dan DIY pada Waktu Sebelum dan Waktu Pandemi Covid-19 Adi Setiawan
Jurnal Sains dan Edukasi Sains Vol. 5 No. 2 (2022): Jurnal Sains dan Edukasi Sains
Publisher : Faculty of Science and Mathematics, Universitas Kristen Satya Wacana, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/juses.v5i2p52-62

Abstract

Dalam penelitian ini dipresentasikan identifikasi karakteristik laju inflasi mtm maupun yoy kota-kota di Jawa Tengah dan DIY pada waktu sebelum pandemi dan pada waktu pandemi Covid-19. Data yang digunakan adalah laju inflasi mtm dan yoy dari bulan Januari 2018 sampai dengan bulan April 2022 dengan menggunakan metode statistik non parametrik. Karakteristik inflasi yang diperoleh adalah bahwa pada bulan Februari, Agustus, September dan Oktober, inflasi mtm cenderung rendah pada kota-kota di Jawa Tengah dan DIY serta kota Ambon namun pada bulan Mei laju inflasi mtm cenderung tinggi. Pada sisi lain laju inflasi cenderung tinggi pada bulan November, Desember dan Januari. Di samping itu, sebelum waktu pandemi dan pada waktu pandemi Covid-19, laju inflasi mtm kota-kota di Jawa Tengah dan DIY cenderung mempunyai keterkaitan satu sama lain. Pada waktu sebelum pandemi, laju inflasi yoy kota Surakarta dan kota Semarang cenderung tidak terkait dengan kota-kota lain di Jawa Tengah dan DIY pada waktu pandemi Covid-19 hanya kota-kota Cilacap, Kudus dan Surakarta yang cenderung terkait, namun pada waktu pandemi, data laju inflasi yoy pada kota-kota di Jawa tengah dan DIY cenderung terkait satu sama lain. Hasil yang juga diperoleh adalah bahwa tidak terdapat perbedaan signifikan distribusi laju inflasi mtm pada waktu sebelum pandemi dan pada waktu pandemi Covid-19 untuk kota-kota di Jawa Tengah dan DIY, namun terdapat perbedaan signifikan distribusi laju inflasi mtm pada waktu sebelum pandemi dan pada waktu pandemi Covid-19 untuk kota-kota di Jawa Tengah dan DIY.
Object Detection to Identify Shapes of Swallow Nests Using a Deep Learning Algorithm Denny Indrajaya; Adi Setiawan; Djoko Hartanto; Hariyanto Hariyanto
Khazanah Informatika Vol. 8 No. 2 October 2022
Publisher : Department of Informatics, Universitas Muhammadiyah Surakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/khif.v8i2.16489

Abstract

Object detection is basic research in the field of computer vision to detect objects in an image or video. the TensorFlow framework is a widely adopted framework to create object detection programs and models. In this study, an object detection program and model are designed to detect the shape of a swallow's nest which consists of three classes, namely oval, angular, and bowl. The purpose model creation is to find out the likeliness of the swallow's nest to the three classes for the swallow's nest sorting machine. The adopted architecture in the modeling is the MobileNet V2 FPNLite SSD since the model obtained from this architecture results in a good speed in detecting objects. Based on the evaluation results that has been carried out, the model can detect the shape of the swallow's nest which is divided into 3 classes, but in some cases swallow's nest are detected into two classes. This issues can still be handled by adjustmenting several parameterss to the object detection program. Results shows that the obtained mAP value of 61.91%, indicating the model can detect the shape of a swallow's nest moderately.
Comparison of k-Nearest Neighbor and Naive Bayes Methods for SNP Data Classification Denny Indrajaya; Adi Setiawan; Bambang Susanto
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 1 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.1758

Abstract

In an accident, sometimes the identity of a person who has an accident is hard to know, so it is necessary to use biological data such as Single Nucleotide Polymorphism (SNP) data to identify the person's origin. This research aims to compare the accuracy and the F1 score of the k-Nearest Neighbor method and the Naive Bayes method in classifying SNP data from 120 people who divide into groups, namely European (CEU) and Yoruba (YRI). Determination of the best method based on the average value of accuracy and the average value of F1 score from 1000 iterations with various percentage distributions of training datasets and testing datasets. In this research, the selection of SNP locations for the classification process was carried out by correlation analysis. The average accuracy obtained for the k-Nearest Neighbor method with the value of k=31 is 98.38% where the average F1 score is 98.39% while the Naive Bayes method obtained the average accuracy of 96.74% and the average F1 score of 96.63%. In this case, the k-Nearest Neighbor method is better than the Naive Bayes method in classifying SNP data to determine the origin of a person's ancestor tends to be from CEU or YRI.
Comparison between Multiple Linear Regression Method and K-Nearest Neighbor Method for Regression on Iris Data Adi Setiawan
Journal of Science and Science Education Vol 5 No 2 (2021): JoSSE Vol. 5 No. 2 (November 2021)
Publisher : Faculty of Science and Mathematics, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/josse.v5i2p26-35

Abstract

This study aims to determine the statistics used in regression models such as RMSE, MAPE, MAE and R2 using the KNN method for regression. The measure of the goodness of the method used is MAPE. The data used is iris data which has been used by many people as an example of data. Variations in the proportion of test data were carried out by 10%, 20%, 30% and 40%. In the proportion of test data of 20%, successively obtained the results that MAPE for case 1, case 2 and case 3 is 5.885 %, 7.778%, 6.979% while in case 4 is 19.341%. As a result, it is obtained that predictions using the KNN method successfully predict/forecast with highly accurate forecasting in case 1, case 2 and case 3 while in case 4 the KNN method predicts with good forecasting.
Perbandingan Kinerja Regresi Decision Tree dan Regresi Linear Berganda untuk Prediksi BMI pada Dataset Asthma Alfida Tegar Nurani; Adi Setiawan; Bambang Susanto
Jurnal Sains dan Edukasi Sains Vol. 6 No. 1 (2023): Jurnal Sains dan Edukasi Sains
Publisher : Faculty of Science and Mathematics, Universitas Kristen Satya Wacana, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/juses.v6i1p34-43

Abstract

Penelitian ini menerapkan dua metode regresi yaitu Decision Tree dan linear berganda untuk memprediksi Body Mass Index (BMI) berdasarkan variabel-variabel lainnya pada dataset Asthma. Metode Decision Tree merupakan salah satu cara data processing dalam memprediksi masa depan dengan cara membangun klasifikasi dan regresi model dalam bentuk struktur pohon. Analisis regresi linear berganda merupakan model regresi yang melibatkan lebih dari satu variabel independen. Analisis regresi linear berganda dilakukan untuk mengetahui arah dan seberapa besar pengaruh variabel independen terhadap variabel dependen. Untuk mengukur tingkat keakuratan model peramalan, digunakan suatu ukuran keakuratan MAPE (Mean Absolute Percentage Error). Hasil MAPE menunjukkan nilai rata-rata prosentase kesalahan mutlak dari nilai sebenarnya dengan nilai peramalan. Pada penelitian ini, metode regresi linear berganda menunjukkan hasil yang lebih baik dengan nilai MAPE berturut-turut sebesar 12,737%; 12,76%; 12,89%; dan 12,99% untuk proporsi data uji berturut-turut 10%, 20%, 30%, dan 40% sedangkan nilai MAPE dari metode regresi Decision Tree sebesar 12,758%; 12,79%; 12,92%; dan 13,13%. Apabila digunakan ukuran kebaikan yang lain seperti MAE dan RMSE akan memberikan hasil yang analog, sedangkan ukuran kebaikan R2 berkebalikan. Penelitian ini dapat dilanjutkan dengan membandingkan hasil yang diperoleh dengan menggunakan metode lain dalam machine learning seperti Support Vector Machine (SVM), random forest, Artificial Neural Network (ANN), dan lain-lain.
Implementation of Wireless User Authentication using WLC-Forti Framework Ignatius Agus Supriyono; Irwan Sembiring; Adi Setiawan; Iwan Setyawan; Theophilus Wellem; Henderi; Ilham Hizbuloh
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 2sp (2023): Special Issue: Support Technopreneurship in the Medical
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i2sp.346

Abstract

Internet access at this time is a daily necessity that cannot be denied. It is certain that most institutions and business entities require internet access in carrying out their activities, including educational institutions. With the development of mobile computer technology in which more users use mobile devices to access the internet, wireless-based network infrastructure is a demand that cannot be postponed any longer. By using a wireless connection to connect to the network, authentication becomes something that must be considered, the use of access to the network by unwanted parties can harm other parties. Changing passwords regularly is important to avoid misuse of access to the network by other parties. This paper presents a problem where when an educational institution implements the Bring Your Own Device (BYOD) program, students and teachers cannot change passwords using the personal device used, this is because the personal device is not registered with the domain controller at the institution. The solution proposed in this article is to move the NPS RADIUS server function on the local site to LDAP in the cloud using a combination of WLC which handles Wi-Fi clients and Fortinet which handles authentication to the cloud. The implementation results show that the WLC-Forti framework functions well.
Exploring network security threats through text mining techniques: a comprehensive analysis Tri Wahyuningsih; Irwan Sembiring; Adi Setiawan; Iwan Setyawan
Computer Science and Information Technologies Vol 4, No 3: November 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v4i3.p258-267

Abstract

In response to the escalating cybersecurity threats, this research focuses on leveraging text mining techniques to analyze network security data effectively. The study utilizes user-generated reports detailing attacks on server networks. Employing clustering algorithms, these reports are grouped based on threat levels. Additionally, a classification algorithm discerns whether network activities pose security risks. The research achieves a noteworthy 93% accuracy in text classification, showcasing the efficacy of these techniques. The novelty lies in classifying security threat report logs according to their threat levels. Prioritizing high-risk threats, this approach aids network management in strategic focus. By enabling swift identification and categorization of network security threats, this research equips organizations to take prompt, targeted actions, enhancing overall network security.
Comparison of the Karney Polygon Method and the Shoelace Method for Calculating Area Vikky Aprelia Windarni; Adi Setiawan; Atina Rahmatalia
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 1 (2023)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.2929

Abstract

In calculating the area of an area, latitude and longitude coordinates are based on data from Global Administrative Region Database and Google Earth can be used. The aim of this research is to calculate the area. This research uses the Karney and Shoelace method to determine its accuracy based on Median Absolute Percentage Error in calculating the area of an area. Median Absolute Percentage Error results use data based on Global Administration The Regional Database by applying the polygon method proposed by Karney is 18.73%, and the percentage is 18.19% by applying the Shoelace method. Based on Google Earth data, implementation the method proposed by Karney obtained a percentage of 19.14%, and the application of shoelaces method obtained a percentage of 19.72%. In this case, Karney polygons and the Shoelace method has good accuracy because the value is below 20%. The proposed Shoelace method is easier to perform understand compared to the Karney method for calculating land area because it uses the Universal Transverse Mercator coordinate system, which projects points on the Earth's surface onto a flat plane.
Perceived Accuracy and User Behavior: Exploring the Impact of AI-Based Air Quality Detection Application (AIKU) Qurotul Aini; Irwan Sembiring; Adi Setiawan; Iwan Setiawan; Untung Rahardja
Indonesian Journal of Applied Research (IJAR) Vol. 4 No. 3 (2023): Indonesian Journal of Applied Research (IJAR)
Publisher : Universitas Djuanda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30997/ijar.v4i3.356

Abstract

The accuracy of air quality detection is a crucial aspect influencing user trust and satisfaction with artificial intelligence (AI) based air quality detection applications. However, only a few studies have tested the effect of the accuracy of AI-based quality detection on users' acceptance and use of these applications. This study aims to fill this gap by addressing the impact of perceived accuracy on behavioral intention and behavior using the AIKU application. This research uses a quantitative approach with the online survey method, distributed in January 2023 - February 2023 to AIKU users. Valid data were 287 respondents from 317 who were received and analyzed using partial least squares structural equation modeling (PLS-SEM). This study uses a modified technology acceptance (TAM) model by adding perceived intelligence as a mediating variable between perceived accuracy and usefulness. The results showed that nine hypotheses were accepted from the 13 hypotheses proposed. The results section of hypothesis testing shows that the effect of perceived AIKU application accuracy on perceived usability and ease of use is insignificant. However, these influences indirectly affect the behavioral intentions and attitudes of users. Even if users do not perceive purity as an essential factor, the user's attitude towards the application is still positive. This study makes a theoretical contribution by developing the TAM model by incorporating variables of perceived accuracy and perceived intelligence relevant to the AI-based context.
Co-Authors Abesha, Muhammad Bagas ADELIA, PUTRI Adella Septiana Mugirahayu Agatha, Titania Puela Aldian Umbu Tamu Ama Aldian Umbu Tamu Ama Alfida Tegar Nurani Alicia Anggelia Lumbantoruan Alkhinaya, Imelzsa ALOYSIUS JOAKIM FERNANDEZ Arbi, Mokhram Ari Ariani, Dwi Setya Arum, Naiya Giska Fauzhia Sekar Atina Rahmatalia Ayu Pratiwi, Ayu Bambang Susanto Baskoro Arie Nugroho Bayu Wijayanto Beni Utomo Christiana Hari Soetjiningsih Christina Maya Indah Susilowati Cintika, Sara Famelia D. B. Nugroho, D. B. Daivi Wardani, Daivi Delsylia Tresnawaty Ufi Denny Indrajaya Denny Indrajaya Deswita, Yenny Dewi Anisa Istiqomah Dewi Lukitasari Diah Wulansari Hudaya, Diah Wulansari Didit Budi Nugroho Djoko Hartanto E. D. Saputri, E. D. Eko Sediyono Elsa Septyana Endang Sulistyaningsih Faldy Tita Fika Widya Pratama Florentina Tatrin Kurniati Gustina, Devi Haay, Happy Alyzhya Hamsani Hamsani, Hamsani Hanna Arini Parhusip Hari Slamet Trianto Hari Slamet Trianto Hariyanto Hariyanto Hartiningsih, Tri Haryadi, Andri Henderi . Henrizal, Henrizal Henry Junus Wattimanela Hidayat, Mario Ignatius Agus Supriyono Ilham Hizbuloh Imansyah, Salmaa R. N Irwan Sembiring Iwan Setiawan Iwan Setyawan Joko Siswanto JT Lobby Loekmono Kasmadi Kasmadi Keo, Jitro Jemryes Kurniawan, Johanes Dian Kurniawan, Titus Antonius David Larassati, Dian Sukma Leipary, Harfely Leonardo Refialy Leonardo Refialy, Leonardo Leopoldus Ricky Sasongko Lilik Linawati Lindin Anderson Litra Diantara Lydia Soepriyani Fallo masipupu, Frangky Aristiadi Meydelina, Gloria Migunani Migunani Mitha Febby R. Donggori Mitha Febby R. Donggori Modjo, Marchella Ellena Mohammad Ridwan Mukti, Audy Desaela Junia Munika, Rani Mustafa Kamal Nafisah Riskya Hasna Nasoetion, Panisean Nasrudienullah, Muhammad Ikhsan Ninda Lutfiani Nizwan Zukhri Olivia Rumahpasal Pariama, Aprillia Mauren Pirmansyah Pirmansyah Pradani, Wynona Adita Priatna , Wowon Pronika, Yeni Purbaratri, Winny Purwanto Purwoko, Agus Qurotul Aini Rachayu, Laras Andriani Rachel Wulan Nirmalasari Wijaya Reniati Reniati Riana Dewi Romauli Basaria Roy Rudolf Huizen Rudhito, Andy Salomina Patty Saputra, Muhammad Dio SARI, EMMA NOVITA Sari, Fariezta Setivani, Febi Sri Suwartiningsih Sulistio Sulistio Suryasatriya Trihandaru Sutarto Wijono Tamaela, Jemaictry Theo Sarita, Fetriks Theopillus J. H. Wellem Tri Wahyuningsih Tundjung Mahatma Uli, Desti Monika Untung Rahardja Untung Rahardja Vikky Aprelia Windarni Vikky Aprelia Windarni Vincentia Pawestri Wahyuni Kristinawati Waney, Natalia Christy Wattimanela, Henry Junus Wibowo, Mars Caroline Wiguna, Edo Wijaya, Maruf Ajisaka Wijayanti, Yunita Puput Windarni, Vikky Aprelia Wisnu Anendya Sekti Yenusi, Yuni naomi Yulius Yusak Ranimpi Yuono, Sukma Setyo Zuliani, Nopita zurman, zurman