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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 Reaktor 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 Plantropica: Journal of Agricultural Science 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 Proceeding of the Electrical Engineering Computer Science and Informatics MNJ (Malang Neurology Journal) Mimbar Agribisnis: Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis 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 JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya INJURITY: Journal of Interdisciplinary Studies Jurnal Polimesin 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) Buletin Veteriner Udayana
Adi Setiawan
Universitas Kristen Satya Wacana
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Penentuan Dua Lokasi Lumbung Padi dengan Menggunakan Metode Grid di Provinsi Kalimantan Tengah Wijayanti, Yunita Puput; Setiawan, Adi; Parhusip, Hanna Arini
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 6: Desember 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3401.41 KB) | DOI: 10.25126/jtiik.2019661750

Abstract

Perancangan lokasi pendistribusian pangan merupakan salah satu kegiatan yang dilakukan pemerintah untuk memenuhi kebutuhan pokok pangan masyarakat yang bisa berubah secara dinamis dari waktu ke waktu. Metode Grid diaplikasikan dalam penelitian ini untuk menentukan lokasi yang tepat untuk lumbung padi dalam upaya pendistribusian bahan pangan di Provinsi Kalimantan Tengah dengan memperhatikan jarak dan biaya transportasi. Tidak hanya itu, dengan bantuan metode grid untuk penentuan kandidat lokasi lumbung padi juga membantu dalam proses penelitian. Berdasarkan data yang berupa koordinat lokasi kantor kabupaten, jumlah penduduk, dan banyaknya produksi padi di Provinsi Kalimantan Tengah dapat diperoleh dua lokasi lumbung padi terdapat pada koordinat geografis (-1.8,113.0) tepatnya di Desa Koeling, Kecamatan Pundu, Kabupaten Kotawaringin Timur, Kalimantan Tengah dan (-3.0,114.2) tepatnya di Desa Pangkuh, Kecamatan Pangkoh Hilir, Kabupaten Pulang Pisau, Kalimantan Tengah dengan total cost sebesar Rp. 55,287,393.08. AbstractThe design of food distribution location is one of the goverment activity to fulfill the main need of society that can change dynamically over time. The Grid  method was applied in this study to determine the exact location the granary for the distribution of food in Central Borneo Province by pay attention distance and transportation cost. Not only that, with the help of the grid method for determining candidates for granary locations it also help in the research process. Based on the data in the form of the coordinates of the location of the district office, population, and the amount of rice production in Central Borneo Province, two granary locations are located at the geographical coordinates (-1.8,113.0) precisely in Koeling Village, Pundu Sub-district, East Kotawaringin District, Central Borneo, and (-3.0,114.2) precisely in Pangkuh Village, Pangkoh Hilir Sub-district, Pulang Pisau District, Central Borneo with a total cost Rp. 55,287,393.08.
GLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning Kurniati, Florentina Tatrin; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan; Huizen, Roy Rudolf
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27842

Abstract

In the era of modern technology, object detection using the Gray Level Co-occurrence Matrix (GLCM) extraction method plays a crucial role in object recognition processes. It finds applications in real-time scenarios such as security surveillance and autonomous vehicle navigation, among others. Computational efficiency becomes a critical factor in achieving real-time object detection. Hence, there is a need for a detection model with low complexity and satisfactory accuracy. This research aims to enhance computational efficiency by selecting appropriate features within the GLCM framework. Two classification models, namely K-Nearest Neighbours (K-NN) and Support Vector Machine (SVM), were employed, with the results indicating that K-Nearest Neighbours (K-NN) outperforms SVM in terms of computational complexity. Specifically, K-NN, when utilizing a combination of Correlation, Energy, and Homogeneity features, achieves a 100% accuracy rate with low complexity. Moreover, when using a combination of Energy and Homogeneity features, K-NN attains an almost perfect accuracy level of 99.9889%, while maintaining low complexity. On the other hand, despite SVM achieving 100% accuracy in certain feature combinations, its high or very high complexity can pose challenges, particularly in real-time applications. Therefore, based on the trade-off between accuracy and complexity, the K-NN model with a combination of Correlation, Energy, and Homogeneity features emerges as a more suitable choice for real-time applications that demand high accuracy and low complexity. This research provides valuable insights for optimizing object detection in various applications requiring both high accuracy and rapid responsiveness.
PENGABDIAN MASYARAKAT UNTUK PEMBELAJARAN CODING ARTIFICIAL INTELLIGENCE KEPADA SISWA SMP KRISTEN WONOSOBO Trihandaru, Suryasatriya; Parhusip, Hanna Arini; Kurniawan, Johanes Dian; Susanto, Bambang; Setiawan, Adi; Nugroho, Didit Budi
Jurnal Abdi Insani Vol 11 No 2 (2024): Jurnal Abdi Insani
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdiinsani.v11i2.1536

Abstract

Artificial intelligence and the Internet of Things (AIOT) have been widely used by various activities, especially in the millennial generation. However, scientific technology has not been widely introduced in education. Additionally, schools experience a decline in student enrollment every year, so it is necessary to carry out innovative learning actions that can be introduced to the community through students. Innovation learning is demonstrated by providing coding lessons that students have never done before so that AIOT becomes part of the learning. Therefore, coding as a learning method is  introduced to junior students so they can get to know AIOT early. The method used is making a device called AIOT-kit with training to be able to directly monitor environmental parameters such as temperature and humidity. The Internet of Things was introduced, which uses ThinkSpeak as a dashboard for making observations. This device was made by students so that they could follow the process from making the AIOT-kit hardware and related coding to utilization. It is shown that AIOT-kit is not yet known to students, including how to code in it. AIOT is an urgent need to access developing related technology. This activity is part of the service team's efforts to make a positive contribution to the community and school environment. After carrying out this activity, there was a change in how students could make their own AIOT-kit devices while also coding. The school even received an award from the local government for the innovation activities carried out during that period.
Analysis of Attack Detection on Log Access Servers Using Machine Learning Classification: Integrating Expert Labeling and Optimal Model Selection Ridwan, Mohammad; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49424

Abstract

Purpose: As the complexity and diversity of cyberattacks continue to grow, traditional security measures fall short in effectively countering these threats within web-based environments. Therefore, there is an urgent need to develop and implement innovative, advanced techniques tailored specifically to detect and address these evolving security risks within web applications.Methods: This research focuses on analyzing attack detection in log access servers using machine learning classification with two primary approaches: expert labeling integration and best model selection. Expert labeling determines whether log entries are safe or indicate an attack.Result: Validation in labeling was applied using different datasets to minimize errors and increase confidence in the resulting dataset. Experimental results show that the Decision Tree and Random Forest models have nearly identical accuracy rates, around 89.3%-89.4%, while the ANN model has an accuracy of 81%.Novelty: This study proposes a fusion of expert knowledge in labeling log entries with a rigorous process of selecting the best classification model. This integration has not been extensively explored in previous research, offering a novel approach to enhancing attack detection within web applications. The research contribution lies in the integration of expert security assessment and the selection of the best model for detecting attacks on server access logs, along with validating labels using various datasets from different log devices to enhance confidence in the analysis results.
MINDFULNESS DAN PENERIMAAN DIRI PADA REMAJA DI ERA DIGITAL Waney, Natalia Christy; Kristinawati, Wahyuni; Setiawan, Adi
Insight: Jurnal Ilmiah Psikologi Vol. 22 No. 2: Agustus 2020
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/psikologi.v22i2.969

Abstract

Di era digital ini, remaja melakukan eksplorasi dan mengekspresikan diri di media sosial. Media sosial menyebabkan remaja rentan terlibat dalam cyberbullying . Hal ini membuat remaja malu dengan diri sendiri dan berusaha menampilkan citra ideal di media sosial sehingga kurang mampu menerima diri apa adanya. Studi ini merupakan studi literatur yang mencoba menelusuri bagaimana mindfulness dan penerimaan diri pada remaja di era digital. Mesin pencari (search engine) digunakan sebagai alat mencari data. Ditemukan 13 literatur dan penelitian dan digunakan sebagai sumber data. Penelitian ini menyimpulkan bahwa latihan mindfulness bisa dijadikan alternatif dalam meningkatkan penerimaan diri pada remaja, dan mindfulness dapat dipraktikkan dengan memanfaatkan aplikasi smartphone. Namun, belum ditemukan penelitian yang secara khusus membuktikan efektivitas penggunaan aplikasi mindfulness dalam meningkatkan penerimaan diri pada remaja di Indonesia.
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 : 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 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 : 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.
Ketahanan Pangan Rumah Tangga di Kabupaten Jember Setiawan, Adi; Suciati, Luh Putu; Aji, Joni Murti Mulyo
Mimbar Agribisnis : Jurnal Pemikiran Masyarakat Ilmiah Berwawasan Agribisnis Vol 12, No 1 (2026): Januari 2026
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ma.v12i1.20035

Abstract

National or regional food security does not necessarily guarantee food security at the household or individual level. Although Jember Regency was classified as a highly food-secure region in 2024 based on Food Security and Vulnerability Atlas (FSVA) data, the reality of household-level food security urgently needs to be addressed. The objective of this research was to analyze household food security conditions based on Engel's Law and Jonsson & Toole's theory. Data from Susenas 2024, analyzed using the Jonsson and Toole method, revealed that the majority of households in Jember still face food vulnerability. Specifically, only about 35.49% (427 households) fell into the food-secure category. Conversely, nearly half, 49.34% (597 households), were in the food- vulnerable category. Additionally, approximately 7.60% (92 households) experienced food scarcity, and 7.77% (94 households) were in a state of food insecurity.
MACROSCOPIC LESION HEALING IN DOGS WITH ATOPIC DERMATITIS FOLLOWING COCONUT OIL ADMINISTRATION Setiawan, Adi; Jayanti, Putu Devi; Susari, Ni Nyoman Werdi; Sudimartini, Luh Made; Suartha, I Nyoman
Buletin Veteriner Udayana Bul. Vet. Udayana. February 2026 Vol. 18 No. 1
Publisher : Fakultas Kedokteran Hewan Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/bulvet.2026.v18.i01.p31

Abstract

Atopic dermatitis is a multifactorial disease associated with inflammatory and pruritic allergic conditions, with a genetic predisposition and immunoglobulin E (IgE) production against environmental allergens. To address this disease, the use of coconut oil as a herbal medicine may serve as an alternative therapy. This study aimed to evaluate changes in macroscopic skin lesions in dogs with atopic dermatitis following coconut oil administration. The study used five Balinese local breed dogs with atopic dermatitis aged three months. The dogs received coconut oil massage treatment once every three days for 33 days. The research procedure involved observing the progression of primary and secondary lesion healing, hair growth around the lesion area, and microscopic examination of the hair growth phase. The data were analyzed using nonparametric tests, followed by the Friedman test, Wilcoxon test, and regression analysis. The results of the Friedman, Wilcoxon, and regression tests showed significant healing after coconut oil application, with statistically significant differences (P < 0.05) in macroscopic observations. Overall, improvements in macroscopic lesions were observed in all sample dogs, characterized by reduced pruritus, erythema, macules, papules, pustules, crusts, scabs, scaling, hyperpigmentation, and lichenification, as well as hair regrowth in areas affected by alopecia. In conclusion, coconut oil application is effective in improving the healing of macroscopic lesions in dogs with atopic dermatitis.
Effect of torrefaction temperature and HDPE binder addition on the physicochemical and combustion properties of elephant grass bio pellets Khan, Nani Siska Putri; Setiawan, Adi; Hakim, Lukman; Hasibuan, Zulfikar; Riskina, Shafira
Jurnal Polimesin Vol 24, No 1 (2026): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v24i1.8360

Abstract

This study investigates the effect of torrefaction temperature and the addition of HDPE binder on the physical, chemical, and combustion properties of elephant grass (Pennisetum purpureum) biopellets. The samples were torrefied at 225°C and 275°C, with an HDPE plastic added at concentrations of 0, 5, 10, 15, and 20%. The results showed that higher torrefaction temperatures substantially reduced the solid yield due to the thermal decomposition of hemicellulose and cellulose, while simultaneously increasing fixed carbon and ash content. Apparent density and drop resistance showed a positive correlation with the addition of HDPE, indicating improved durability and structural integrity of the pellets. The hydrophobicity test revealed longer water penetration times with increasing HDPE content, demonstrating enhanced moisture resistance, although a slight decline was observed at 275°C due to polymer degradation. During combustion, pellets torrefied at 275°C exhibited a faster temperature rise and more stable mass reduction compared to those processed at 225°C, reflecting better combustion efficiency and heat transfer performance. The relationship between proximate analysis and combustion showed that lower Volatile Matter (VM) and higher fixed carbon contents contributed to improved thermal stability and controlled combustion behavior. These findings confirm that torrefaction at 275°C combined with a 15% HDPE binder produces high-quality biopellets with superior mechanical strength, hydrophobicity, and combustion performance, making them a promising candidate for sustainable and efficient bioenergy systems.
Co-Authors Adella Septiana Mugirahayu Aldian Umbu Tamu Ama Alfida Tegar Nurani Alicia Anggelia Lumbantoruan ALOYSIUS JOAKIM FERNANDEZ Ariani, Dwi Setya Atina Rahmatalia Bambang Susanto Baskoro Arie Nugroho Bayu Wijayanto Beni Utomo Christiana Hari Soetjiningsih Christina Maya Indah Susilowati D. B. Nugroho, D. B. Daivi Wardani, Daivi Delsylia Tresnawaty Ufi Denny Indrajaya Denny Indrajaya Deswita, Yenny Dewi Anisa Istiqomah Dewi Lukitasari Didit Budi Nugroho Djoko Hartanto E. D. Saputri, E. D. Eko Sediyono Elsa Septyana Endang Sulistyaningsih Faldy Tita Fika Widya Pratama Florentina Tatrin Kurniati Haay, Happy Alyzhya Hanna Arini Parhusip Hari Slamet Trianto Hari Slamet Trianto Hariyanto Hariyanto Hartiningsih, Tri Hasibuan, Zulfikar Henderi . Henry Junus Wattimanela I Nyoman Suartha Ignatius Agus Supriyono Ilham Hizbuloh Irwan Sembiring Iwan Setiawan Iwan Setyawan Joko Siswanto Joni Murti Mulyo Aji JT Lobby Loekmono Keo, Jitro Jemryes Khan, Nani Siska Putri Kholifah, Izzah Nurul Kurniawan, Johanes Dian Kurniawan, Titus Antonius David Leipary, Harfely Leonardo Refialy Leonardo Refialy, Leonardo Leopoldus Ricky Sasongko Lilik Linawati Lindin Anderson Luh Made Sudimartini Luh Putu Suciati Lukman Hakim Lydia Soepriyani Fallo masipupu, Frangky Aristiadi Meydelina, Gloria Migunani Migunani Mitha Febby R. Donggori Mitha Febby R. Donggori Modjo, Marchella Ellena Mohammad Ridwan Muhammad Muhammad Nafisah Riskya Hasna Ni Nyoman Werdi Susari Ninda Lutfiani Olivia Rumahpasal Pariama, Aprillia Mauren Pradani, Wynona Adita Priatna , Wowon Purbaratri, Winny Purwoko, Agus Putu Devi Jayanti Qurotul Aini Rachayu, Laras Andriani Rachel Wulan Nirmalasari Wijaya Ramadhana, Varotama Putra Riana Dewi Riskina, Shafira Romauli Basaria Roy Rudolf Huizen Rudhito, Andy Salomina Patty Saputri, Cut Rahmah SARI, EMMA NOVITA Setivani, Febi Sri Suwartiningsih Sulistio Sulistio Suryasatriya Trihandaru Sutarto Wijono Tamaela, Jemaictry Theo Sarita, Fetriks Theopillus J. H. Wellem Tri Wahyuningsih Tundjung Mahatma Umbu Tamu Ama, Aldian Untung Rahardja Untung Rahardja Vikky Aprelia Windarni Vikky Aprelia Windarni Vincentia Pawestri Wahyuni Kristinawati Waney, Natalia Christy Wattimanela, Henry Junus Wibowo, Mars Caroline Wijayanti, Yunita Puput Windarni, Vikky Aprelia Wisnu Anendya Sekti Yenusi, Yuni naomi Yulius Yusak Ranimpi