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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Scientific Journal of Informatics Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Polinema Kepada Masyarakat Jurnal Pengabdian kepada Masyarakat International Journal of Educational Review, Law And Social Sciences (IJERLAS) JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) International Journal of Social Science, Educational, Economics, Agriculture Research, and Technology (IJSET) International Journal of Health, Engineering and Technology Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Informatika Polinema (JIP)
Batubulan, Kadek Suarjuna
Jurusan Teknologi Informasi, Politeknik Negeri Malang
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DEVELOPMENT OF A PRESENCE SYSTEM WITH FACE RECOGNITION INTEGRATED WITH ONLINE APPLICATIONS USING DEEP LEARNING METHODS TO EXPAND THE TEACHING AND LEARNING PROCESS AT SMKN 9 MALANG Fullchis Nurtjahjani; Galih Putra Riatma; Kadek Suarjuna Batubulan; Novitasari, Ane Fany
International Journal of Educational Review, Law And Social Sciences (IJERLAS) Vol. 4 No. 5 (2024): September
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijerlas.v4i5.1958

Abstract

Attendance systems are needed in various fields such as companies, government agencies, educational agencies, and others. Especially for educational institutions, the attendance system functions to control or determine the presence of students, teaching staff, and educational staff. SMKN 9 Malang City is an educational institution that has the obligation and role to equip its graduates with life skills in an integrative manner, which combines generic and specific potential to solve and overcome life's problems. This school has 5 expertise concentrations from which students can choose. In measuring the presence of the academic community, SMKN 9 Malang City uses an attendance system that includes Finger (for students and PTT and GTT) and the application from the East Java Province BKD e-Presence ASN. However, in its use several weaknesses were found that prevented the application from running efficiently, these weaknesses were 1) the number of locations, 2) a large number of students, 3) Time was less effective because the ratio between tools and students was still not ideal, 4) Sometimes some students have to try several times for less sensitive fingerprints, 5) Not connected with parents so that the school, the students' guardians/committee collaborate in monitoring their son. To follow up on problems with the attendance system used, schools need a more effective and efficient attendance system, namely by using Face Recognition Integrated with Online Applications Using Deep Learning Methods. The system created can make attendance easier for students, teaching staff, and educational staff. It is hoped that this system can improve student discipline and make it easier to monitor the performance of teaching staff and educational staff. Keywords: Face Recognition, Deep Learning, Attendance
THE SELECTION PROCESS MONITORING APPLICATION TO IMPROVE EMPLOYEE PERFORMANCE AT PT MEGA ADIYASA MANDIRI MALANG Fullchis Nurtjahjani; Ane Fany Novitasari; Kadek Suarjuna Batubulan; Vipkas Al Hadid Firdaus
International Journal of Social Science, Educational, Economics, Agriculture Research and Technology (IJSET) Vol. 2 No. 11 (2023): OCTOBER
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijset.v2i11.277

Abstract

As a company engaged in providing human resource services, PT Mega Adiyasa Mandiri needs to improve the quality of the human resources it produces to become a superior company in this field. With the selection process that has been carried out so far. Thus PT Mega Adiyasa Mandiri needs to improve the optimization of selection activities. The data collection techniques used in this study are observation and interviews. The method used for making the selection process monitoring application is the pieces method. After the application development process is complete, a system trial will be carried out using the white box method. PT Mega Adiyasa Mandiri is a provider of human resources services that are superior, insightful and competent in various fields. The use of monitoring applications for the selection process makes a positive contribution to PT Mega Adiyasa Mandiri. Companies can have integrated data between prospective workers and users. Companies can easily obtain input from users regarding the performance of the human resources that have been used. In addition, this application also makes it easy for companies to ensure that prospective workers are of good quality
Time Series Analysis of Tourist Arrivals to Bali Using Data Kusuma, Aniek Suryanti; Batubulan, Kadek Suarjuna
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 7 No 4 (2025): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.216

Abstract

This research performs a time series analysis on the number of tourist arrivals to Bali, using historical data to identify patterns, trends, and potential forecasting models. The tourism sector is crucial to Bali's economy, and understanding visitor trends can assist in planning and resource allocation. Data from 2010 to 2023 is analyzed, focusing on monthly arrival statistics sourced from government tourism departments. Several time series methods are employed, including seasonal decomposition, autocorrelation, and ARIMA (AutoRegressive Integrated Moving Average) modeling. The analysis reveals distinct seasonal patterns, with peaks during holiday periods and off-peak lulls. A significant impact of global events, such as the COVID-19 pandemic, is observed, causing sharp declines in tourist arrivals. By fitting ARIMA models, we forecast future trends in tourist numbers, providing insights into the potential recovery trajectory of Bali's tourism industry post-pandemic. The research concludes with recommendations for stakeholders, including government agencies and businesses, on how to prepare for future fluctuations in tourist arrivals and capitalize on seasonal trends. Understanding these patterns is essential for fostering sustainable growth and minimizing economic disruptions within the tourism sector.
Applying K-Nearest Neighbors Algorithm for Wine Prediction and Classification Pradhana, Anak Agung Surya; Batubulan, Kadek Suarjuna; Kotama, I Nyoman Darma
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 6 No 3 (2024): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.231

Abstract

This study evaluates the performance of a machine learning classification model using a confusion matrix to analyze predictions across three distinct classes. The results show the model achieving a high accuracy of 94.44%, indicating reliable classification performance. The confusion matrix highlights that most instances were classified correctly, with minimal misclassifications observed, particularly in Class 1, where some overlap with other classes was evident. The findings suggest that the model effectively distinguishes between well-separated classes while facing minor challenges with overlapping data distributions. To address these issues, potential improvements such as feature engineering, class balancing, and advanced optimization techniques are recommended. The study underscores the importance of confusion matrix analysis as a diagnostic tool for understanding classification errors and guiding model refinement. Additionally, this research emphasizes the role of high-quality datasets, proper model selection, and hyperparameter tuning in achieving optimal classification accuracy. The outcomes provide a basis for further enhancement of machine learning models in applications requiring multi-class classification. By reducing errors and improving model robustness, this approach can contribute to more accurate and reliable decision-making processes across various domains, including healthcare, finance, and natural language processing.
SOSIALISASI COPING STRESS DI ERA PANDEMI COVID-19 IBU-IBU PKK RW 21 KELURAHAN PURWANTORO MALANG Nurtjahjani, Fullchis; Fadloli, Fadloli; ‘Aini, Yulis Nurul; Novitasari, Ane Fany; Maskan, Mohammad; Batubulan, Kadek Suarjuna
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 2, No 2 (2021)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v2i2.1189

Abstract

 Kebijakan yang ditetapkan selama masa pandemi membuat beberapa pihak mengalami stres, salah satunya adalah ibu rumah tangga. Berdasarkan observasi yang dilakukan di PKK RW 21 Kelurahan Purwantoro Kota Malang diketahui bahwa ibu rumah tangga yang mendapatkan beban terbesar dalam melakukan pekerjaannya. Selain mengerjakan pekerjaan rutin mengurus rumah tangga, ibu juga harus mendampingi anaknya belajar di rumah, dan tidak jarang ibu rumah tangga mengambil peran sebagai guru bagi putra putrinya. Beban yang ditanggung oleh ibu rumah tangga tidak hanya double birden, akan tetapi bisa banyak beban yang ditanggungnya.  Selain itu permasalahan pada sektor keuangan juga memberikan dampak pada tingkat stress yang dirasakan oleh Ibu-Ibu PKK RW 21 Kelurahan Purwantoro Kota Malang. Tujuan dari pengabdian ini adalah memberikan pengetahuan kepada anggota PKK yang mayoritas adalah ibu rumah tangga agar dapat mengatasi stress yang dialami selama masa pandemi. Pelaksanaan pengabdian dilakukan dengan metode alih pengetahuan, diskusi dan tanya jawab, serta pemecahan permasalahan. Jumlah peserta yang hadir sebanyak 37 orang dari total anggota aktif PKK yang berjumlah 40 orang. Selanjutnya, peserta berpartisipasi aktif dalam diskusi dan sharing permasalahan serta saling memberikan solusi. Kemudian terdapat peningkatan pengetahuan dan pemahaman peserta sebelum dan sesudah penyampaian materi dengan beberapa poin yaitu pemahaman definisi stres dari 70% peserta menjadi 80% peserta. Selanjutnya, pemahaman ruang lingkup stres dari 65% peserta menjadi 75% peserta. Sementara untuk pemahaman aspek-aspek strategi coping stress dari 45% menjadi 85%. Dengan adanya peningkatan pemahaman terhadap coping stress maka dapat disimpulkan kegiatan pengabdian terlaksana dengan baik
PELATIHAN KOMUNIKASI YANG EFEKTIF UNTUK MENINGKATKAN KETERAMPILAN IBU PKK RW 20 BUNULREJO MALANG Novitasari, Ane Fany; Adisaksana, Helmy; Batubulan, Kadek Suarjuna; Nurtjahjani, Fullchis; Agustina, Hiqma Nur
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 2, No 2 (2021)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v2i2.947

Abstract

Banyaknya isu kesalahpahaman dalam penyampaian informasi pada perkembangan teknologi yang semakin meningkat menyebabkan terjadi kesalahpahaman dan berujung pada perselisihan membuat perlunya pedoman pergaulan untuk menjaga kepentingan masing-masing pribadi yang berbeda-beda supaya pihak yang berkepentingan senang, tenang, tentram, terlindungi serta tidak merugikan masyarakat yanga lain. Tujuan dari pengabdian ini adalah memberikan pelatihan komunikasi yang efektif untuk mengembangkan keterampilan berkomunikasi agar tidak terjadi kesalahpahaman dalam berorganisasi. Mitra dalam pengabdian ini adalah ibu-ibu anggota PKK RW 20 Kelurahan Bunulrejo kota Malang. Metode yang digunakan dengan transfer pengetahuan, diskusi dan pembahasan permasalahan yang terjadi. Berdasarkan evaluasi selama kegiatan pengabdian, telah terlihat perkembangan pada ibu-ibu PKK RW 20 dalam berkomunikasi, ibu-ibu mulai teliti dan cermat dalam menyampaikan informasi dalam organisas
INFORMATION SYSTEM FOR THE ADMISSION OF NEW STUDENT CANDIDATES FOR THE BIDIKSIBA SCHOLARSHIP PATHWAY POLYTEKNIK NEGERI MALANG Kadek Suarjuna Batubulan; Ratih Indri Hapsari; Budi Harijanto; Ane Fany Novitasari
International Journal of Educational Review, Law And Social Sciences (IJERLAS) Vol. 5 No. 1 (2025): January
Publisher : RADJA PUBLIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijerlas.v5i1.2441

Abstract

The Bidikiba Program (Education Scholarships Around Bukit Asam) is a program of educational scholarships provided by PT Bukit Asam Tbk (PTBA) to students high school graduates or equivalent from underprivileged families around the operational area companies to be able to continue their education at university. Implementation of Bidikiba scholarship acceptance selection is still done manually registration process, selection exams, and ranking of prospective students. Registration This is done by recording prospective students using Excel and if any Changes or errors in prospective students' data must be reported to the admin make edits to the data. The system is expected to help resolve problems in the process of accepting prospective students for the Bidikiba scholarship programat Malang State Polytechnic.
Design And Building Of The Utility Performance Monitoring System At PT. XYZ With Brainstorming Method Kadek Suarjuna Batubulan; Mungki Astiningrum; Dika Rizky Yunianto
International Journal of Health Engineering and Technology Vol. 2 No. 5 (2024): IJHET JANUARY 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v2i5.187

Abstract

In general, utilities in engineering are devices or systems designed to provide basic needs or to help complete certain jobs or processes. In engineering, utilities generally refer to systems or devices designed to provide basic needs such as electricity, water, gas, or telecommunications. At PT. The brainstorming method is used to produce creative ideas that can be applied in developing utility monitoring systems. Various ideas are generated through discussion and debate between brainstorming participants. Then, these ideas are analyzed and selected to select those that best suit PT XYZ's needs. Therefore, the author created a utility performance monitoring system to make it easier for the engineering department to carry out work activities. This utility performance monitoring system was created using a JavaScript framework, namely AngularJS for the frontend and ExpressJS for the backend. Apart from that, the author also tested PT XYZ employees so that the system runs according to needs. Of the 10 respondents, more than 50% of the accumulated respondents stated that the utility performance monitoring system application was running satisfactorily and very satisfactorily, there were 10% to 30% of respondents who stated that it was running well and 10% of respondents said it was not working well. Based on the test results above, it was found that the utility monitoring system at PT XYZ could be categorized as a fairly informative information system for the engineering department.
K-Nearest Neighbors Algorithm for Analyzing Doge Coin Market Behavior Batubulan, Kadek Suarjuna; Pradhana, Anak Agung Surya; Kotama, I Nyoman Darma
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 6 No 4 (2024): June
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.238

Abstract

This study investigates the application of the K-Nearest Neighbors (KNN) algorithm to analyze Dogecoin's market behavior using historical trading data, including daily metrics such as Open, High, Low, Close, and Volume, spanning from November 2017. As a proximity-based machine learning algorithm, KNN effectively captures short-term market patterns, achieving a low Mean Absolute Error (MAE) of 0.0017, demonstrating its capability in identifying general trends during stable periods. However, the model faces challenges in predicting sudden price shifts caused by external factors like social media sentiment and regulatory news, highlighting its limitations in highly volatile cryptocurrency markets. Preprocessing steps, including normalization and outlier handling, improved the algorithm’s performance, yet its scalability and sensitivity to hyperparameters remain issues. Future research directions include integrating external data sources, such as social media sentiment and macroeconomic indicators, and adopting advanced models like Gradient Boosting Machines (GBMs) or Long Short-Term Memory (LSTM) networks to enhance predictive accuracy and adaptability. These improvements aim to provide more robust insights into Dogecoin's market dynamics, aiding traders and financial analysts in navigating the complexities of cryptocurrency markets.
Predicting Wine Quality Based on Features Using Naive Bayes Classifier Pradhana, Anak Agung Surya; Batubulan, Kadek Suarjuna; Kotama, I Nyoman Darma
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 7 No 1 (2024): September
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.244

Abstract

This study explores the application of the Naive Bayes classifier in predicting wine quality based on physicochemical attributes. Leveraging a dataset containing features such as acidity, pH, alcohol content, and sulfur dioxide concentrations, the research aims to address the limitations of traditional sensory evaluation methods, which are often subjective and inconsistent. Data preprocessing, including normalization and feature selection, is performed to ensure the dataset is suitable for machine learning. The Naive Bayes classifier is implemented using Python's scikit-learn library, with hyperparameter tuning conducted to optimize its performance. The model is evaluated on metrics such as accuracy, precision, recall, and F1-score, achieving competitive results compared to other machine learning techniques such as Decision Trees and Support Vector Machines. The findings demonstrate the Naive Bayes classifier’s efficiency in handling high-dimensional data, its computational simplicity, and its potential for real-time quality assessment in the wine industry. This research highlights the role of machine learning in automating and enhancing quality control processes, contributing to the broader integration of data-driven approaches in the agri-food sector. The study underscores the feasibility of using physicochemical features as objective indicators of wine quality, offering a scalable and cost-effective alternative to traditional methods.
Co-Authors Ade Ismail Ade Ismail Adisaksana, Helmi Adisaksana, Helmy Agustina, Hiqma Nur Ahmad Nova Rifki Wildani Aini, Lilies Nur Alifia Zaida Nurmaya Ananta, Ahmadi Yuli Andika Hilmi Hamdani Ane Fany Novitasari Ane Fany Novitasari Ane Fany Novitasari Aniek Suryanti Kusuma, Aniek Suryanti Anisa Taufika Firdausi Annisa Taufika Firdausi Annisa Taufika Firdausi Annisa Taufika Firdausi Astiningrum, Mungki Ayu Febriyanti Puspitasari ‘Aini, Yulis Nurul Banni Satria Andoko Budi Harijanto, Budi Chrisnandari, Rosita Dwi Danang Eko Novianto Dewajani, Heny Dian Hanifudin Subhi Dika Rizky Yunianto Dwi Pribadi, Joni Elisiana, Malia Fadloli Fadloli Fadloli, Fadloli Fauziah, Suci Nur Galih Putra Riatma Hapsari, Ratih Indri Helmi Adisaksana Ilham Ibrahim Imam Fahrur Rozi Irsyad Arif Mashudi Joni Dwi Pribadi Kotama, I Nyoman Darma Lilies Nur Aini Lusiani, Cucuk Evi Malia Elisiana Millenia Rusbandi Mohammad Maskan Mohammad Maskan, Mohammad Noprianto, Noprianto Novianto, Danang Eko Nurtjahjani, Fullchis Pradhana, Anak Agung Surya Putra Prima Arhandi, Putra Prima PUTU SUGIARTAWAN Ridwan Rismanto Rizky Ardiansyah Rosa Andrie Asmara Rusbandi, Millenia Sanita Dhakirah Sanita Dhakirah Shabrina Adani Putri, Shabrina Adani Shoumi, Milyun Ni’ma Sigit Hadiantoro, Sigit Suci Nur Fauziah Ulla Delfana Rosiani Vipkas Al Hadid Firdaus Wardani, Ni Wayan Wildani, Ahmad Nova Rifki Yulis Nurul Aini