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All Journal Jurnal Ilmiah Informatika Komputer Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan CESS (Journal of Computer Engineering, System and Science) Jurnal CoreIT JURNAL KAJIAN TEKNIK ELEKTRO JTAM (Jurnal Teori dan Aplikasi Matematika) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi INTECOMS: Journal of Information Technology and Computer Science KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) IJID (International Journal on Informatics for Development) JURIKOM (Jurnal Riset Komputer) Jurnal Tekno Kompak TEKNOKOM : Jurnal Teknologi dan Rekayasa Sistem Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Indonesian Journal of Electrical Engineering and Computer Science Bubungan Tinggi: Jurnal Pengabdian Masyarakat Jurnal Manajemen Informatika Jayakarta International Journal Software Engineering and Computer Science (IJSECS) Berdikari : Jurnal Pengabdian kepada Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science Technology and Informatics Insight Journal KAMI MENGABDI Journal of Data Science Theory and Application Journal of Digital Business and Management Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Edusight International Journal of Multidisciplinary Studies (EIJOMS) International Journal of Law Social Sciences and Management Innotech Computer Journal ABDINE :Jurnal Pengabdian Masyarakat
Tundo, Tundo
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Subjectivity Tracking System for Poor Scholarship Recipients at Elementary School Using the MOORA Method Tundo, Tundo
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 3 (2022): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i3.8373

Abstract

This research was conducted because of complaints from several parents at Elementary School regarding recipients of the Poor Student Assistance (PSA) who were still less objective. Elementary School XY regularly conduct screening activities every year to select prospective PSA recipients. This selection is made so that the recipients of this assistance are students entitled to it. Some students should be accepted as a selection committee but do not mistake of choosing some students who have kinship or subjective matters. Therefore, this study aims to explore and create applications that apply the Multi Objective Optimization to the basic  Ratio Analysis (MOORA) method, which is a method for determining students based on predetermined criteria. The criteria used are the value of report cards, student achievement, student activity, parental income, parental dependents, and home conditions. After conducting a search and implementation using the MOORA method in determining PSA recipients, it was found that there were some non-objective results where the student's criteria and final results were lower than some other students. However the Elementary School provided a recommendation to get PSA. If this happens again, then the importance of this system is to help objective selection. The accuracy results explained that 14.39% of PSA recipients were subjective. It was concluded that this research helps an objective decision and facilitates the decision maker in determining the best 3 recipients from each class at Elementary School XY.
Evaluasi Kepuasan Mahasiswa terhadap Fasilitas Kampus Menggunakan Metode Simple Additive Weighting (SAW) Nugroho, Agung Yuliyanto; Tundo, Tundo; Saidah, Andi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 10 No 2 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v10i2.5324

Abstract

Evaluation of student satisfaction with campus facilities is one important aspect in improving the quality of college services and infrastructure. However, this satisfaction evaluation process has a gap between student expectations of the facilities provided by the campus. This research aims to design a Decision Support System (DSS) that can help the campus in assessing student satisfaction levels using the Simple Additive Weighting (SAW) method. This method was chosen because of its ability to conduct an assessment based on criteria that have certain weights so as to produce the best alternative ranking. The criteria used in this study include cleanliness, maintenance, comfort, completeness, condition, service, and level of satisfaction. Data was obtained through questionnaires distributed to students in various study programs, focusing on various aspects of campus facilities such as classrooms, laboratories, libraries, hall areas, and podcast studios. It was then processed using SAW steps, including matrix normalization and final score calculation. The result showed that the final results of the evaluation of student satisfaction with campus facilitiesf from 100 respodents obtained a fairly high score of 44 which was said to be quite good. This SAW method is able to provide a clear ranking of the level of student satisfaction, as well as identify areas that require improvement or enchancement at the college.
PENGARUH E-WOM DALAM MEMEDIASI HUBUNGAN ANTARA DIGITAL MARKETING ACTIVITIES DAN INTENTION TO BUY DI TOKOPEDIA Heri Mahyuzar; Tundo, Tundo
Journal of Digital Business and Management Vol. 1 No. 2 (2022): Journal of Digital Business and Management
Publisher : LP3M Universitas Putra Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32639/jdbm.v1i2.182

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh electronic word of mouth (E-WOM) dalam memediasi hubungan antara digital marketing activities dan intention to buy di Tokopedia. Populasi pada penelitian ini adalah semua pengguna Tokopedia di Indonesia. Adapun sampel penelitian yang digunakan pada penelitian ini sebanyak 100 responden yang dipilih berdasarkan convinience sampling. Teknik pengumpulan data dalam penelitian ini menggunakan metode survey dengan cara mengirimkan kuesioner kepada responden. Alat analisis yang digunakan adalah SEM AMOS. Berdasarkan analisis yang telah dilakukan diperoleh bahwa content marketing berpengaruh positif signifikan terhadap electronic word of mouth (E-WOM). Electronic Promotion berpengaruh positif signifikan terhadap electronic word of mouth (E-WOM). Electronic word of mouth (E-WOM) berpengaruh positif signifikan terhadap intention to buy. Sedangkan electronic word of mouth (E-WOM) dapat memediasi hubungan antara digital marketing dan intention to buy.
Implementasi Clustering Prestasi Siswa Mata Pelajaran IPS Melalui Visual Studio Code Raihanah, Syifa; Tundo, Tundo; Wahyudi, Tri; Sugiyono, Sugiyono
TEKNOKOM Vol. 8 No. 1 (2025): TEKNOKOM
Publisher : Department of Computer Engineering, Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/teknokom.v8i1.221

Abstract

Penelitian ini mengoptimalkan data prestasi siswa dalam mata pelajaran IPS di SMP Ksatrya Jakarta melalui metode K-means clustering. Menggunakan metodologi CRISP-DM, data prestasi seperti nilai harian, sumatif tengah semester, sumatif akhir tahun, dan rapor dikumpulkan dan diolah. Hasil analisis menunjukkan tiga kategori siswa: prestasi sangat baik, baik, dan cukup. Nilai silhouette score menunjukkan cluster 2 memiliki kecocokan tertinggi (0.2745), sedangkan cluster 1 terendah (0.0585), mengindikasikan cluster 2 lebih terdefinisi. Pengelompokan ini diperoleh melalui aplikasi desktop yang dikembangkan dengan Visual studio code dan Tkinter. Implementasi clustering ini mendukung pembelajaran lebih efektif dan personal dengan materi menantang untuk siswa berprestasi sangat baik, sesuai tingkat pemahaman untuk siswa berprestasi baik, dan berbasis pengulangan untuk siswa berprestasi cukup, memberikan wawasan mengenai pola prestasi siswa dan mendukung keputusan pembelajaran yang lebih terarah.
SHARING KNOWLEDGE: DECISION SUPPORT SYSTEM DALAM MEMBUAT BERBAGAI KEPUTUSAN YANG RASIONAL Tundo, Tundo; Saidah, Andi
KAMI MENGABDI Vol 5, No 2 (2025): KAMI MENGABDI
Publisher : Universitas 17 Agustus 1945 Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52447/km.v5i2.8640

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman dan keterampilan siswa-siswi SMA Yappenda Jakarta Utara dalam menggunakan Decision Support System (DSS) sebagai alat bantu dalam pengambilan keputusan yang rasional dan terstruktur. Pengambilan keputusan yang tepat sangat penting dalam kehidupan akademik maupun sehari-hari, terutama di era digital saat ini yang sarat dengan informasi dan pilihan. Melalui kegiatan sharing knowledge ini, para peserta diperkenalkan pada konsep dasar DSS, jenis-jenis sistem pendukung keputusan, serta implementasinya dalam situasi nyata yang relevan dengan kehidupan pelajar. Metode yang digunakan dalam kegiatan ini meliputi ceramah interaktif, studi kasus, serta simulasi pengambilan keputusan berbasis teknologi. Hasil dari kegiatan ini menunjukkan peningkatan pemahaman peserta terhadap pentingnya pendekatan sistematis dalam membuat keputusan serta kemampuan awal dalam mengidentifikasi masalah, menganalisis alternatif, dan memilih solusi terbaik menggunakan prinsip DSS. Kegiatan ini diharapkan dapat menjadi bekal awal bagi siswa dalam menghadapi tantangan pengambilan keputusan di masa depan secara lebih rasional dan terukur.
Automatic Detection of Skin Diseases Using Convolutional Neural Network Algorithms Tundo; Fadillah Abi Prayogo; Sugiyono
International Journal Software Engineering and Computer Science (IJSECS) Vol. 4 No. 3 (2024): DECEMBER 2024
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v4i3.3021

Abstract

Skin diseases are a major health concern in Indone sia and they can seriously impact a patient’s quality of life. The problem is aggravated by humid tropical climate, limited access to healthcare facilities, and a lack of trained dermatology personnel. The cases in Indonesia are many, and the diagnosis and treatment of skin diseases are delayed, which makes the patient's condition worse. Based on data from the Ministry of Health (Kemenkes), the prevalence of skin disease in Indonesia is 0.62 cases per 10,000 population with the highest prevalence in Eastern Indonesia. Developing a Skin Disease Detection System Based on Convolutional Neural Network (CNN) algorithms. However, CNN algorithms are widely used in image recognition and classification, and can act as an automatic diagnostic system. This system has been developed to aid in diagnosis and improve patient access to dermatological care, especially for remote communities. Users can reach out for services at any time and any location, a practical solution for treating skin health problems. This study's results are anticipated to lower the diagnostic delays and improve the treatment outcomes while offering quick access to reliable dermatological service. This is a great effort on global level for any skin disease supporting to improve life of human lives from skin health issues.
Classification of Apple Ripeness Detection System Using Self-Organizing Map (SOM) Method Tundo; Shindy Apriani; Sugeng
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3734

Abstract

Apple (Malus Domestica) is one of the most popular types of fruit and is in high demand by the public because of its varied flavors. Apples have many nutrients and various vitamins including healthy fats, carbohydrates, proteins, vitamins and many more. The Apple is one of the apple varieties developed in Batu City, Malang and planted in several areas with suitable agroclimates for apple growth. This research uses Anna apple images as datasets. Various ways can be employed to distinguish Anna apples' maturity, including through color image analysis. But to the naked eye, Anna apples are often difficult to distinguish. This research classifies the maturity of Anna apples based on color analysis with the Self-Organizing Map method. Using Google Colab and Python programming language and datasets from kaggle.com as many as 139 datasets, 46% training data, 54% validation data. The Self-Organizing Map method was chosen because of its ability to recognize visual patterns accurately. The accuracy of the results based on the SOM Method performance evaluation metrics namely Quantization Error, Silhouette Score and Topographic Error. Quantization Error RGB (0.004737) is lower than HSV (0.073178) which indicates RGB's ability is effective in representing data in SOM. Silhouette Score HSV (0.704204) is higher than RGB (0.599846) indicating the ability of HSV is slightly better in grouping objects.
Chili Type Detection System Using Principal Component Analysis Method Rindy Julianda; Tundo; Sugeng
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3735

Abstract

Classification of types of chili vegetables is an important aspect in the agricultural industry to increase the efficiency of product management, packaging and distribution. This research aims to implement the Principal Component Analysis (PCA) method in the process of classifying vegetables and types of chilies. PCA is used to reduce the dimensionality of the data and extract the main features that are significant in distinguishing vegetable categories. The research dataset consists of digital images of chili vegetables which are extracted into color, texture and shape attributes. The research results show that PCA is able to significantly improve classification accuracy by minimizing computational complexity. Experiments were carried out with various numbers of principal components in PCA to determine the optimal configuration. In the best configuration, this method achieves classification accuracy of 90%, with PCA effectively reducing data dimensionality by up to 95% without losing important information. In conclusion, this approach has great potential to be implemented in vegetable classification automation systems to support efficiency in agricultural supply chains.
Prediksi Produksi Sablon di Perusahaan Tomoinc dengan Perbandingan Metode Single Moving Average dan Single Exponential Smoothing Galih Satria Yacob; Tundo; Dadang Iskandar Mulyana; Sri Lestari
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i1.3018

Abstract

A common problem faced by companies is predicting future production of goods based on previously recorded data. The company produces only according to orders, conducting production processes solely based on consumer demand. Any excess production is stored as stock to meet sudden consumer demands. These predictions significantly influence management decisions regarding the quantity of goods that must be prepared, considering factors like general business and economic conditions, competitors' actions, government policies, market trends, product life cycles, styles and fashions, changes in consumer demand, and technological innovations. This research aims to identify and analyze screen printing production predictions using the Moving Average and Exponential Smoothing methods. The more data used for comparison, the more accurate the prediction results. The research successfully developed a screen printing production prediction system, facilitating easier determination of future production quantities.
Analisis Sentimen Kepuasan Publik Terhadap Masa Kepemimpinan Shin Tae Yong Menggunakan Algoritma Naïve Bayes Pramudya Nugraha; Rasiban; Frencis Matheos Sarimole; Tundo
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 1 (2025): JANUARI-MARET 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i1.3020

Abstract

Shin Tae Yong is the coach of the Indonesian national team who has been a football player in South Korea and has coached the South Korean national team at the 2018 World Cup in Russia. Many people watch or pay attention to Shin Tae Yong's behavior and behavior when coaching the Indonesian national team. Shin Tae Yong has considerable worry with the Indonesian national team because of his strategy. However, there are several media that frame Shin Tae Yong's news differently so that differences in viewpoints and opinions on Shin Tae Yong are controversial, inviting many people to give their opinions. Therefore, people choose social media as a place to channel opinions. In this study, we will take tweets from X with search keywords for Shin Tae Yong and the Indonesian national team to process and classify the text using the sentiment analysis method. The text classification process is divided into two classes, namely positive sentiment classes and negative sentiment classes. The data used amounted to 2495 data that had been cleansed, which amounted to 2.348 Positive sentiment data and 147 data with negative sentiments so that they can be presented 98.94% positive and 60.00% negative, based on the classification of the Naïve Bayes algorithm model, using a split comparative data 0.8 :  0.2 With the value of k=3 for Shin Tae Yong's dataset, an accuracy value of 96.67%.
Co-Authors Abdus Salam, Abdus Agung Yuliyanto Nugroho Ahmad Satria Rizqi Maula Akbar, Rasyan Akbar, Riolandi Akbar, Yuma Alief Prima Gani Amelia, Ika Andhika Pramudya Andi Ode Larios Anisah Nurul Azhar Arinal, Veri Arvianto, Ramdani Aryanti, Putri Gea Atsilah Daini Putri Aula, Raisah Fajri Aulia Nur Septiani Azhar, Anisah Nurul Betty Yel, Mesra Betty Yel, Mesra Bobby Arvian James Dadang Iskandar Mulyana` Dalail Dalail Dalail, Dalail Devia, Elmi Devika Azahra Ramadhani Dewantara, Rizki Dewanti, Elsa Mayorita Dharmawan, Tio Dita Tri Yuliantoro Doni Kurniawan Doni Kurniawan Eflin Tresia Eldina, Ratih Enny Itje Sela Fadillah Abi Prayogo Fakhrurrofi Fakhrurrofi Fakhrurrofi, Fakhrurrofi Faldo Satria Farhan Adriansyah Waloeya Faridatun Nisa Farras Abiyyu Handoko Fauzan Ibnu Sarky Firly Januarsyah Galih Satria Yacob Gatra, Rahmadhan Hadi Gunawan Hadi Gunawan, Hadi Haryati Heri Mahyuzar Heri Mahyuzar Humam Mu'asyir Husain Rahmani James, Bobby James, Bobby Arvian Januarsyah, Firly Joko Sutopo Junaidi Junaidi Kasiono, Roy Kastum Kastum Kastum Kastum, Kastum Kevin Arya Josaphat Sitompul Khafid Nurohman Khana, Rajes Kiki Setiawan Laily Nurmayanti Lutfi Nugrahaini M. A. Burhanuddin Maharani, Delia Maharani, Shinta Aulia Mahardika, Fajar Mahyuzar, Heri Marcia Rizky Hamdala Marliani, Tiara Marthy, Nicola Mohd Khanapi Abd Ghani Muhammad Derry Oktaviandi Muhammad Nurdin Muhammad Nurdin Muhammad Raffiudin Muhammad Rizqi Ramadhan Muhammad Syazidan Nabilah, Laila Nandang Sutisna Nandang Sutisna Nenden Nuraini Nisa, Faridatun Nizar, Amin Nugraha, Pramudya Nugrahaini, Lutfi Nugroho, Agung Yuliyanto Nugroho, Wisnu Dwi Nuradi, Fahmi Nurohman, Khafid Paidi, Imam Pramudya Nugraha Prayogo, Fadillah Abi Priyanto, Imansyah Putri Wibowo, Salsabila Qolbi, Rofika Rachmat Hidayat Insani Rachmat Hidayat Insani Rachmawati, Dea Noer Raden Dewa Saktia Purnama Raffiudin, Muhammad Raihanah, Syifa Raisah Fajri Aula Ramadhan, Abhirama Huga Ramadhani, Devika Azahra Ramdani Arvianto Rasiban Rasiban Ridho Akbar Rindy Julianda Riolandi Akbar Rizki Maulana, Rizki Rohmat Wijaya Romadan, Diva Putra Rona Guines Purnasiwi Saidah, Andi Saifullah, Shoffan Saktia Purnama, Raden Dewa Sarimole, Frencis Matheos Setiawan, Kiki Shindy Apriani Shofwatul ‘Uyun Sodik Sopan Adrianto SOPAN ADRIANTO SRI LESTARI Sugeng Sugiono Sugiono Sugiyono Sugiyono Sugiyono Sugiyono Suropati, Untung Sutisna, Nandang Syani, Muhammad Syifa Raihanah Tampubolon, Parlindungan Tasti, Andi Thalita Tiara Ratu Alifia Tresia, Eflin Tri Wahyudi Tri Wahyudi Tundo Tundo Untung Suropati Untung Suropati Wafiqi, Achmad Ulul Azmi Wagiman, Wagiman Waloeya, Farhan Adriansyah Wijonarko, Panji Wisnu Dwi Nugroho Yacob, Galih Satria Yudisman Ferdian Bili