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All Journal Sistemasi: Jurnal Sistem Informasi Prosiding Seminar Nasional Teknoka JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL PENDIDIKAN TAMBUSAI KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Infotech: Journal of Technology Information ABDIMASY: Jurnal Pengabdian dan Pemberdayaan Masyarakat IICS Bidik : Jurnal Pengabdian kepada Masyarakat Jurnal Nasional Teknologi Komputer The Center For Sustainable Development Studies Journal SmartComp Jurnal Pengabdian kepada Masyarakat Dewantara Infact: Jurnal Sains dan Komputer JURNAL ILMIAH PENELITIAN MAHASISWA JURNAL TEKNIK INFORMATIKA DAN KOMPUTER Industrial & System Engineering Journals (ISEJOU)
Ryan Putranda Kristianto
Univeritas Katolik Darma Cendika
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Medicine & Pharmacology Social Sciences Transportation Other

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Forward Chaining Algorithm on Informatics Graduate Job Recommendation System Based on MBTI Test Jhonatan Laurensius Tjahjadi; Yulia Wahyuningsi; Padmavati Darma Putri Tanuwijaya; Ryan Putranda Kristianto
IAIC International Conference Series Vol. 4 No. 1 (2023): SEMNASTIK 2023
Publisher : IAIC Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/conferenceseries.v4i1.641

Abstract

The Myers-Briggs Type Indicator (MBTI) is a method for identifying an individual's personality type based on the psychological theory of Carl Gustav Jung. In the context of computer science students, they often face challenges in planning their academic journey and determining the direction of their career development during their studies, causing confusion when it comes to choosing a career path in the field of computer science in the future. To address these challenges, the researcher has developed a web-based expert system using the PHP programming language. This expert system is designed to make decisions based on a collection of user responses, which are processed using the forward chaining method, ultimately providing the user's personality type along with suitable career choices. The primary objective of the expert system is to assist students in making decisions regarding their studies and future careers. Through this research, the researcher has produced a functioning website capable of efficiently processing user responses and generating decisions regarding personality types and career options. Thus, this study provides a solution to aid computer science students in planning their academic and career paths.
PENGUJIAN APLIKASI GAME PUZZLE INDONESIA BERBASIS ANDROID DENGAN TEKNIK BLACK-BOX TESTING Hendra, Hendra; Kristianto, Ryan Putranda
Infotech: Journal of Technology Information Vol 10, No 1 (2024): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v10i1.224

Abstract

The fast-growing development of technology has brought changes to how individuals carry out their daily lives, one of which is the presence of gadgets. The existence of this technology makes it easy in almost all aspects, both in searching for information, doing activities, and in using applications as a means for learning and entertainment. This paper discusses the process of designing, implementing and testing an Android mobile application with a puzzle game theme. The process of designing and building the application utilizes tools from Figma and Android Studio. The Puzzle Indonesia application adopts the concept of Indonesian culture and aims to serve as a platform for children to gain insight and practice cognitively. The Puzzle Indonesia application can now be downloaded through the Play Store. The application testing was carried out using the Black-Box Testing technique and distributing questionnaires using Likert Scale guidelines. Through this test, it was found that the Black-Box testing technique could be applied well and through the questionnaire an average score of 90.24% was obtained from the 12 respondents involved and there were evaluations from several respondents. ABSTRAKPerkembangan teknologi yang kian berkembang pesat membawa perubahan pada bagaimana suatu individu menjalankan kesehariannya, salah satunya yakni dengan hadirnya gawai. Adanya teknologi tersebut memberikan kemudahan pada hampir semua aspek, baik dalam mencari informasi, beraktivitas, hingga dalam menggunakan aplikasi sebagai sarana untuk belajar dan hiburan. Makalah ini membahas tentang proses perancangan, implementasi, dan pengujian aplikasi mobile android bertemakan permainan puzzle. Proses dalam rancang bangun aplikasi tersebut memanfaatkan tools dari Figma dan Android Studio. Aplikasi Puzzle Indonesia menganut konsep Kebudayaan Indonesia serta bertujuan untuk menjadi wadah bagi anak-anak dalam menambah wawasan serta berlatih secara kognitif. Aplikasi Puzzle Indonesia kini sudah dapat diunduh melalui Play Store. Adapun pengujian aplikasi dilakukan dengan teknik Black-Box Testing dan pembagian kuisoner menggunakan pedoman Skala Likert. Melalui pengujian tersebut, diperoleh bahwa teknik pengujian Black-Box dapat diterapkan dengan baik serta melalui kuisoner didapatkan nilai rata-rata sebesar 90,24% dari 12 responden yang terlibat dan adapun evaluasi dari beberapa responden.
Desain Aplikasi Penjadwalan Menu Makan Siang Karyawan Menggunakan Pendekatan Design Thinking dan SUS Testing Fianindra Riezca Augusty; Ryan Putranda Kristianto
Prosiding Seminar Nasional Teknoka Vol 8 (2023): Proceeding of TEKNOKA National Seminar - 8
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Scheduling is allocating an activity by taking to the sequence of implementation times and availability of limited resources. In the case of employee lunch menus in a company, lunch menu schedule can change every day within a week to adjust the availability of resources limited by company management. Scheduling repeated lunch menus manually will certainly waste a lot of time, an application is needed to do the scheduling automatically. Designing a scheduling application for lunch menus using the Design Thinking approach method applies 5 stages, namely Empathize, Define, Ideate, Prototype, and Testing. Result of this design is an application design which is then evaluated using the System Usability Scale (SUS) to measure user satisfaction. Where user satisfaction data was obtained using the form collecting method using JotForm media which was sent to 30 respondents. The SUS score result is 80.2, which means that the usability design is acceptable or feasible.
PREDIKSI PENJUALAN HT MOTOROLA XIR C2660 MENGGUNAKAN ALGORITMA SUPPORT VECTOR REGRESSION (STUDI KASUS: CV. ALFACOMS) Wildwina; Ryan Putranda Kristianto
Jurnal Teknik Informatika dan Komputer Vol. 3 No. 1 (2024): Jurnal Teknik Informatika dan Komputer
Publisher : Universitas Muhammadiyah Prof. DR. HAMKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/jutikom.v3i1.13836

Abstract

In carrying out a business that operates in the field of selling goods, predictions are very necessary. Predictions are very necessary because making predictions can help predict what will happen in the future so that the risks that will occur can be minimized as small as possible. This research focuses on sales predictions in 2023 for the HT Motorola XiR C2660 brand using the SVR (support vector regression) algorithm and using linear type kernel parameter testing and c(cost) with a test value of 0.1. To obtain parameter types and parameter test values, use the GridSearchCV technique. Apart from that, this research uses error value testing with mean absolute percentage error (MAPE). So the results of the HT Motorola XiR C2660 sales prediction for 2023 with the SVR algorithm were obtained. In 2023, 209 units were sold with an error value of 11.23%, which means the forecasting ability with the SVR algorithm is good.
Pendampingan dan Pemenuhan Lampu Panel Surya Sebagai Penerangan Area Taman dalam Konsep Lingkungan Berkelanjutan Bagi Warga Putra, Heristama Anugerah; Kristianto, Ryan Putranda; Andrian, David; Oktaviani, Yohana Christela; Subhagia, Andreas Andika Putra
BIDIK: Jurnal Pengabdian kepada Masyarakat Vol. 4 No. 2 (2024): BIDIK: Jurnal Pengabdian kepada Masyarakat
Publisher : Fakultas Ilmu Budaya Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/bidik.v4i2.17107

Abstract

Large and excessive use of electricity, especially for lighting, is also a problem in itself, namely the large expenditure on electricity bills. For this reason, the public is encouraged to use energy-saving lighting such as LED lights or the use of solar panels. Residents want sufficient lighting in public facility areas. Community service activities are carried out at the Babatan Pilang RT Housing Complex. 002 RW. 005, where residents expect assistance from the team to provide education on effective ways to overcome large electricity costs in order to save energy. Apart from that, it will also be realized in the physical form of installing garden lights based on the use of solar panels to remain energy efficient. So that from the results of counseling and fulfillment of garden lights, residents can understand and understand how to save money by getting to know the types of energy-saving lights such as solar panel lights. In terms of park functions, solar panel lights can be shared by residents even if they are used at night.
Studi Komparatif: Performansi Akurasi Algoritma Klasifikasi untuk Analisis Sentimen Pada Kandidat Presiden RI di Pemilu 2024 kristianto, ryan putranda
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 13, No 4 (2024): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v13i4.6286

Abstract

Penelitian ini mengulas analisis sentiment terkait pemilihan presiden dan wakil presiden Republik Indonesia tahun 2024 yang menjadi sorotan utama di platform sosial media dan berita nasional. Fokus pada Anies Baswedan, Prabowo Subianto, dan Ganjar Pranowo, ulasan masyarakat menunjukkan variasi sentimen positif dan negatif. Dalam menggunakan algoritma klasifikasi seperti K-Nearest Neighbors (KNN), Multinomial Naive Bayes, Decision Tree  dan  Stochastic Gradient Descent dalam supervised learning, tujuannya adalah memberikan wawasan mendalam tentang pandangan masyarakat terhadap calon pemimpin. Dari hasil analisis, skenario terbaik adalah skenario 1 dengan akurasi rata-rata 75%, sedangkan Multinomial Naïve Bayes menjadi algoritma terbaik dengan akurasi rata-rata 79%. Penelitian ini tidak hanya memberikan kontribusi ilmiah, tetapi juga menyoroti peran opini publik dalam proses demokratisasi dan pemilihan pemimpin negara, memberikan pemahaman lebih mendalam tentang preferensi masyarakat terhadap calon pemimpin
Pengembangan Face Recognition Menggunakan OpenCV dan Kombinasi Algoritma Haarcascade dan Local Binary Pattern Histogram (LBPH) untuk Aplikasi Presensi Mahasiswa kristianto, ryan putranda
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 13, No 4 (2024): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v13i4.7083

Abstract

Penelitian ini bertujuan untuk mengembangkan aplikasi Face Recognition yang sudah ada sebelumnya, dengan fokus pada peningkatan tampilan UI dan nilai confidence dalam pengenalan wajah. Aplikasi sebelumnya memiliki rata-rata nilai confidence 65% dan error rate 35%, yang dianggap kurang optimal. Pengembangan dilakukan menggunakan OpenCV Python dengan kombinasi algoritma Haar Cascade Classifier dan Local Binary Pattern Histogram (LBPH). Metode yang digunakan meliputi perbaikan UI, peningkatan jumlah capturing image menjadi 100 kali untuk training, dan implementasi sistem konfirmasi setelah 10 kali deteksi pengguna yang sah. Hasil penelitian menunjukkan peningkatan pada tampilan UI dan fungsionalitas aplikasi, termasuk penambahan form konfirmasi untuk menyimpan data presensi. Namun, peningkatan jumlah capturing image tidak menghasilkan perubahan signifikan pada nilai confidence, yang tetap berada di sekitar 65%. Sebagai solusi, sistem konfirmasi otomatis setelah 10 kali deteksi pengguna yang sah diimplementasikan untuk meningkatkan akurasi pengenalan wajah
Model Estimasi Object Measurements untuk Pengukuran Objek Material Otomatis Menggunakan YOLOv5 dan OpenCV Kristianto, Ryan Putranda; Putra, Heristama Anugrerah; Andrian, David; Jati, Yosafat Danang Kukuh Bismoko; Hendra, Hendra
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 14, No 1 (2025): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v14i1.7734

Abstract

Dalam dunia insiyur, presisi dalam perhitungan objek material sangatlah diperlukan, hal ini akan berimplikasi kepada hasil kualitas bangunan yang dibuat. Penerapan Teknologi Informasi dewasa ini yang semakin masif, mampu menjangkau dan mendisrupsi segala bidang lini, termasuk dalam bidang bangunan dan pertukangan. Pengukuran objek material menjadi sorotan utama dalam penelitian ini, bagaimana mengautomasi pekerjaan yang membutuhkan presisi tinggi ini kepada teknologi informasi khususnya artificial intelligence merupakan tantangan – tantangan para peneliti artificial intelligence. Penelitian ini secara komprehensif membahas penggunaan YOLOv5 dan OpenCV untuk pengukuran ruang dimensi objek material secara otomatis. Dari hasil penelitian dan pengujian yang dilakukan menunjukkan akurasi tertinggi mencapai 90.28%. Dari penelitian ini diharapkan bahwa Teknologi Informasi dapat bekerjasama dengan semua bidang lini dan disiplin, dimana dalam penelitian ini ditunjukkan kolaborasinya dengan bidang arsitektur dan pertukangan.
PERFORM COMPARATION OF DEEP LEARNING METHODS IN GENDER CLASSIFICATION FROM FACIAL IMAGES Yosefina Finsensia Riti; Ryan Putranda Kristianto; Dionisius Reinaldo Ananda Setiawan
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 4 (2025): JITK Issue May 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i4.4717

Abstract

Identifying gender through facial images is a crucial aspect in various life contexts. Biometric technology, such as facial recognition, has become an integral part of various applications, including fraud detection, cybersecurity protection, and consumer behavior analysis.  With the advancement of technology and the progress in artificial intelligence, especially through the use of Convolutional Neural Networks (CNNs), computers can now identify gender from facial images with a high level of accuracy. Although there are still some challenges, such as variations in pose, facial expressions, and different lighting conditions, CNNs can overcome these obstacles. This study uses the CelebA dataset, which consists of 122,000 facial images of both men and women. The dataset has been processed to maintain a balanced number of samples for each gender class, resulting in a total of 101,568 samples. The data is divided into training, validation, and test sets, with 80% used for training, and the remaining 20% split between validation and testing. Eight different CNN architectures are applied, including VGG16, VGG19, MobileNetV2, ResNet-50, ResNet-50 V2, Inception V3, Inception ResNet V2, and AlexNet. Although previous research has shown the potential of CNN architectures for various classification tasks, these studies often encounter issues of overfitting on large datasets, which can reduce model accuracy. This study applies dropout techniques and hyperparameter tuning to address overfitting issues and optimize model performance. The training results indicate that ResNet-50, ResNet-50 V2, and Inception V3 achieved the highest accuracy of 98%, while VGG16, VGG19, MobileNetV2, and AlexNet achieved accuracies of 95% and 97%, respectively. Performance evaluation using confusion matrices, precision, recall, and F1-score demonstrates excellent performance.
Analisis History Forensics untuk Deteksi Akses Situs Judi Pada Smartphone Tanuwijaya, Padmavati Darma Putri; Kristianto, Ryan Putranda
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.28646

Abstract

Penelitian ini membahas permasalahan meningkatnya risiko akses anak terhadap situs perjudian daring melalui perangkat smartphone, khususnya Android. Tujuan utama dari penelitian ini adalah untuk menjawab bagaimana aktivitas mencurigakan seperti akses ke situs judi dapat dideteksi melalui artefak histori browser pada perangkat yang digunakan anak. Penelitian dilakukan dengan pendekatan forensik digital menggunakan skenario simulasi, di mana perangkat digunakan untuk mengakses beberapa situs perjudian secara nyata. Artefak berupa file histori browser diekstraksi dan dikonversi menjadi format database untuk memudahkan proses analisis. Pencocokan kata kunci dilakukan untuk mendeteksi jejak akses terhadap konten perjudian. Hasilnya menunjukkan terdapat enam entri yang sesuai dengan pola pencarian, lima di antaranya valid dan satu merupakan false positive akibat pencocokan berbasis substring. Temuan ini menunjukkan efektivitas pendekatan pencocokan kata kunci dalam tahap penyaringan awal, namun tetap memerlukan validasi manual guna menghindari kesalahan klasifikasi. Penelitian ini memberikan kontribusi dalam bentuk pemanfaatan data histori sebagai bukti digital awal yang akurat dalam mendukung investigasi forensik terhadap aktivitas daring yang melibatkan anak, serta dapat dijadikan rujukan dalam pengembangan alat pemantauan aktivitas digital yang lebih responsif terhadap ancaman konten berisiko.
Co-Authors Agustinus Yovi Siang Adi Setiawan Alvinus Yodi Anas Hidayat Andre Hartanto Andrian, David Angelicha Yuspitasari Suwignyo Banu Santoso Brina Oktafiana David Andrian Dionisius Reinaldo Ananda Setiawan Edwin Alexander Edwin Alexander Fianindra Riezca Augusty Firdausi Gobryas Sapeibu Hargiani, Fransisca Xaveria Heristama Anugerah Putra Heristama Putra Jati, Yosafat Danang Kukuh Bismoko Jhonatan Laurensius Tjahjadi Jonathan Steven Iskandar Kyan Dillan Verado Leonardo Dandy Lucia Ina Trisjanti Mario Anugraha Nantu , Gregorius nathanael, audi Nick Engelbert Mongkol Nur Widjiyati Nurwijayanti Odo Grean Kaesar Putra Wardhana Oktaviani, Yohana Christela Onny Priskila Padmavati Darma Putri Tanuwijaya Prizhelius Anzhelmus Boli Purba, Lasman Parulian Putra, Heristama Anugrerah Subhagia, Andreas Andika Putra Tandjung, Stephanus Surijadarma Tanuwijaya, Padmavati Darma Putri Thomas Dalton Greg Daud Wildwina Wildwina Wildwina Yohana Christela Oktaviani Yosefina Finsensia Riti Yulia Wahyuningsi Yulia Wahyuningsih Yulius Dani Eko Saputro