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All Journal Jurnal Ilmiah Informatika Komputer Teknika Bulletin of Electrical Engineering and Informatics 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 ABDINE Jurnal Pengabdian 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 Computer Journal
Tundo, Tundo
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Penerapan IoT dalam Sistem Monitoring Suhu dan Kelembapan pada Lahan Bawah Tanah (Basement) Masjid Al-Barkah Tundo; Azhar, Anisah Nurul; Setiawan, Kiki; Aula, Raisah Fajri
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.v9i1.3199

Abstract

Underground areas, commonly referred to as basements, are often used for essential functions such as parking and electrical distribution spaces. However, unstable temperature and humidity levels due to poor air circulation can affect comfort and safety. Therefore, a system capable of automatically monitoring and controlling temperature and humidity is needed to optimize comfort and energy efficiency. This research employs an Internet of Things (IoT) approach using a DHT11 sensor to detect temperature and humidity in the basement. The data collected by the sensor is processed using a NodeMCU ESP32 microcontroller and then displayed in real-time on a web-based application via the cloud. The system also automatically controls the fan/blower to maintain ideal conditions in the basement. The results of this research show that the implemented IoT system demonstrates high effectiveness in monitoring temperature and humidity in real-time, providing accurate data, enabling energy savings by automatically regulating the fan/blower, and improving air quality and user comfort in the basement.
K-Means Clustering of Social Studies Performance at Junior High School Tundo; Raihanah, Syifa; Wahyudi, Tri; Sugiyono
IJID (International Journal on Informatics for Development) Vol. 13 No. 2 (2024): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2024.4632

Abstract

This study aims to optimize the use of technology in evaluating student performance by grouping students based on their abilities. The main issues include the underutilization of technology, the absence of an appropriate evaluation system for different levels of student ability, and ineffective methods for grouping students. The K-Means Clustering algorithm was chosen because it has proven effective in grouping academic data in various studies. The data used includes Daily Knowledge Scores (DKS), Daily skill scores (DSS), Mid-term Summative Scores (MSS), End-of-Year Summative Scores (ESS), and Grade Report (GR). The data was analyzed using the CRISP-DM methodology with the help of RapidMiner. The results showed that 28.63% of students were classified as having excellent performance, 50.21% as having good performance, and 21.16% as having moderate performance. The Davies-Bouldin Index score of 1.713 for K=3 was considered sufficient for distinguishing the different student performance groups. The results of this study are expected to help schools provide learning support that better aligns with student needs. Future research is recommended to focus on optimizing the number of clusters (K), applying this method to other subjects, and integrating it with e-learning platforms for real-time student performance monitoring.
Comparison of Single Exponential Smoothing and Double Moving Average Algorithms to Forecast Beef Production Tundo; Rachmat Hidayat Insani; Rasiban; Untung Suropati
IJID (International Journal on Informatics for Development) Vol. 13 No. 1 (2024): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2024.4663

Abstract

Beef is considered a high-value commodity as it is an important source of protein. Interest in beef continues to rise. Beef production has risen sharply in the past decade, but declined by 7,240.68 tons in 2020 amid coronavirus lockdowns. After that, in 2021, production reached 16,381.81 tons and continued to increase in 2022 and 2023. A precise method is required to forecast beef production. One way to predict beef production in Jakarta is using the Single Exponential Smoothing and Double Moving Average methods. The two algorithms are compared to get the lowest error rate. The methodology used in this research is the SEMMA (Sample, Explore, Modify, Model, and Assess) methodology. According to SAS Institute Inc., there are five stages in developing a system using the SEMMA methodology. After analyzing using MAPE, it is found that the algorithm with the smallest error value is the Single Exponential Smoothing algorithm with a percentage in the monthly period of 16% while for the annual period, it is 27% compared to other algorithms. The forecasting is quite accurate because the MAPE value for each algorithm used has an error of less than 31%.
Seasonal meat stock demand used comparison of performance smoothing-average forecasting Tundo, Tundo; Saifullah, Shoffan; Dharmawan, Tio; Junaidi, Junaidi; Devia, Elmi
Indonesian Journal of Electrical Engineering and Computer Science Vol 37, No 1: January 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v37.i1.pp425-433

Abstract

Seasonal patterns significantly influence the demand for beef stock, especially in rural areas that rely on natural feed. Accurate forecasting is essential for managing this demand due to beef's status as a government-regulated nutritional commodity. Food production, consumption, and income levels affect the demand for beef stocks. This research aims to identify the most precise forecasting method for predicting future beef stock needs. We evaluated multiple techniques, including single exponential smoothing (SES), double exponential smoothing (DES), single moving average (SMA), and double moving average (DMA), using the mean absolute percentage error (MAPE) metric, focusing specifically on beef supplies in Pemalang. The results indicated that the DMA method achieved the highest accuracy with a MAPE value of 5.993% at the 4th -order parameter. Additionally, increasing the data volume improved forecasting accuracy, demonstrating the effectiveness of the DMA method for beef stock prediction.
Penentuan Penerima BSM Secara Objektiv Berdasarkan Metode Decision Support System VIKOR Tundo, Tundo; Akbar, Riolandi; Nugroho, Agung Yuliyanto; Saidah, Andi
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 2 (2024): September
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i2.10434

Abstract

This research was conducted because of complaints from several parents regarding the BSM decision at SDN Kalanganyar ABC, however there were several students who were less well off because the choice of BSM was still subjective. SDN Kalanganyar ABC always holds activities related to BSM admissions once a year. It is hoped that this activity can also provide benefits for students who are poor but have excellent grades so they can carry out activities without being burdened by financial needs. In reality, there are still many students who do not receive BSM, even though according to the requirements, these students should be entitled to receive BSM. Therefore, there is a very irrational subjectivity in the ongoing elections. To overcome this problem, researchers tried to develop an application that applies the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, namely a method that makes decisions based on a rational compromise of criteria. These criteria include student reports, parents' income, academic achievement, dependents, home conditions, parents' relatives, and activity. From the results of the analysis and application of the VIKOR decision support system, subjective results were obtained for students whose evaluation standards and final decisions were lower than several other students, but the school provided BSM recommendations. To prevent the recurrence of this incident, VIKOR was able to answer objective findings with results of 76.57% with subjective findings of 23.43% in the previous system.
Prototipe Sistem Monitoring Kelembapan Tanah pada Tanaman Cabai Berbasis Internet of Things dengan Metode Fuzzy Logic Menggunakan NodeMCU Esp8266, Blynk dan Thingspeak: Prototype of Soil Moisture Monitoring System for Chili Plants Based on Internet of Things Using Fuzzy Logic Method with NodeMCU ESP8266, Blynk, and ThingSpeak Romadan, Diva Putra; Arinal, Veri; Sarimole, Frencis Matheos; Tundo, Tundo
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 1 (2025): MALCOM January 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i1.1600

Abstract

Pengelolaan kelembapan tanah yang optimal sangat penting untuk pertumbuhan tanaman cabai, namun sering kali menjadi tantangan bagi petani, terutama dalam memastikan irigasi yang efisien. Masalah utama yang dihadapi adalah kesulitan dalam memantau dan mengontrol kondisi tanah secara real-time, yang sering kali menyebabkan penyiraman berlebihan atau kurang. Penelitian ini bertujuan untuk mengembangkan prototipe sistem monitoring kelembapan tanah berbasis Internet of Things (IoT) dengan menggunakan NodeMCU ESP8266. Sistem ini mengintegrasikan sensor tanah, suhu, dan kelembapan udara, di mana data dikirimkan secara real-time ke aplikasi Blynk untuk pemantauan dan kontrol jarak jauh. Metode Fuzzy Logic diterapkan untuk mengoptimalkan irigasi secara otomatis berdasarkan data sensor, sementara ThingSpeak digunakan untuk penyimpanan dan analisis data jangka panjang. Hasil pengujian menunjukkan bahwa sistem ini efektif menjaga kelembapan tanah pada tingkat ideal dan menghemat penggunaan air. Kesimpulannya, sistem ini memberikan solusi praktis dan efisien bagi petani dalam mengelola irigasi tanaman cabai secara berkelanjutan.
Analisis Tingkat Kepuasan Mahasiswa dalam Kegiatan UKM di Stikom CKI Menggunakan Algoritma Naive Bayes Arvianto, Ramdani; Tundo, Tundo; Tresia, Eflin; Januarsyah, Firly
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp206-214

Abstract

The main problem in increasing the level of student satisfaction in UKM activities at STIKOM CKI is caused by various factors, including the rare frequency of meetings and the multiplication of material without significant development. This dissatisfaction can reduce students' interest in actively participating in UKM activities, which should be a source of positive experiences and skills development. Well-managed SME activities can be an important means of developing soft skills such as leadership, team collaboration and communication skills. However, when these activities are not managed well, the results can be counterproductive, causing frustration and dissatisfaction among students. Based on these problems, an application of the Naive Bayes algorithm will be carried out to determine the satisfaction level of STIKOM CKI students with 80 training data and 6 test data. After calculating, an accuracy rate of 83.33%, recall of 33.33%, and precision are obtained. 100%. Therefore, it is important to manage student satisfaction levels to avoid being counterproductive. One of the appropriate data mining algorithms to solve the case above is to use the Naive Bayes algorithm.
Penerapan Data Mining Menggunakan Algoritma Apriori pada Brand Milenials Cafe Gunawan, Hadi; Tundo, Tundo; Ramadhani, Devika Azahra; Waloeya, Farhan Adriansyah
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp215-221

Abstract

Millennials Café is a cafe that just opened in March 2024, in an effort to stay relevant and competitive in this field, Millennials Café needs to continue to innovate and adjust to customer preferences. One way is to utilize data mining technology. The Apriori algorithm is one of the data mining technologies that can be used. The application of the apriori algorithm to the Milenials Café transaction data aims to find association rules to be able to generate frequencies and relationships between one or more items in the transaction data in the Milenials Café. This research produces 33 association rules that can help the sales strategy at Milenials Café. The following are the association rules with the highest confidence value, namely the Thai Tea menu, Milo Dinasourus, 100% Millennials Pizza, Hezelnut Chocolate, Oreo Cookies and Cream Shake 97%. Millennials Pizza, Fried Potatoes 96%. The 33 rules that already exist can be used as a reference for the owner of Millennials Café to create a sales strategy that can increase cafe revenue.
Penerapan dan Kontribusi Kecerdasan Buatan ChatGPT Untuk Menafsir Teks Hukum (Studi Kasus Penafsiran Pasal 10, Pasal 13, Permenkes No.889 Tahun 2011) Wijonarko, Panji; Wagiman, Wagiman; Khana, Rajes; Tundo, Tundo; Salam, Abdus; James, Bobby; tampubolon, parlindungan
Jurnal Kajian Teknik Elektro Vol 8, No 2 (2023): JKTE VOL 8 NO 2 (SEPTEMBER 2023)
Publisher : Universitas 17 Agustus 1945 Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52447/jkte.v8i2.7061

Abstract

ChatGPT adalah model bahasa berbasis kecerdasan buatan yang dikembangkan oleh OpenAI. Salah satu aspek kritis dalam penerapan ChatGPT adalah kemampuannya untuk memahami, menafsirkan, dan memanfaatkan informasi yang terdapat dalam peraturan atau sebuah pedoman resmi. Hal ini tentunya sangat membantu dalam melakukan pekerjaan, salah satunya pada bidang Hukum, yaitu kemungkinan melakukan analisis interpretasi hukum, mengeksplorasi kemampuan ChatGPT untuk menafsir, memberikan interpretasi atau penjelasan tentang peraturan atau klausal hukum tertentu berdasarkan fakta-fakta atau skenario yang diberikan. Penelitian ini membahas mengenai Penerapan Dan Kontribusi Kecerdasan Buatan ChatGPT Untuk Menafsir Teks Hukum (Studi Kasus: Pasal 10, Pasal 13 Permenkes No.889 Tahun 2011). Penelitian akan difokuskan pada apakah ChatGPT dapat melakukan penafsiran pada kata “dianggap” pada bunyi Pasal 10 Ayat (1) yang menyebutkan Apoteker yang baru lulus pendidikan profesi: “dianggap telah lulus uji kompetensi”. Eksplorasi ChatGPT juga dilakukan dalam menafsir kata “dapat memperoleh”, pada Pasal 13 Ayat (1) “dapat memperoleh STRA (Surat Tanda Registrasi Apoteker) secara langsung”. Kedua pasal di atas dianggap ambigu karena penafsiran yang dilakukan bisa saja menjadi subjektif terlebih jika memiliki kepentingan tertentu di dalam mengambil keputusan. Eksplorasi dilakukan dengan memasukkan skenario pertanyaan tentang kedua pasal tersebut ke dalam GPT-3.5 dan juga GPT-4. Hasil eksplorasi menunjukkan bahwa ChatGPT memiliki kemampuan untuk melakukan penafsiran terhadap teks hukum. ChatGPT dapat memberikan kontribusi dan menjadi opsi masukan bagi praktisi hukum terhadap ketentuan yang ambigu ataupun sulit ditafsir oleh manusia, hal ini karena ChatGPT dianggap sebuah mesin yang netral dan tidak terpengaruh terhadap perasaan ataupun kepentingan. Kontribusi ChatGPT juga dapat memberikan efesiensi, baik dari aspek waktu maupun sumber daya manusia dalam lingkup praktisi hukum.
Sebuah Komparasi Metode WASPAS dan WP: untuk Penentuan Kandidat Lurah Pondok Tundo, Tundo; Gatra, Rahmadhan; Wijonarko, Panji; Salam, Abdus; James, Bobby Arvian; Tampubolon, Parlindungan
Jurnal Kajian Teknik Elektro Vol 8, No 2 (2023): JKTE VOL 8 NO 2 (SEPTEMBER 2023)
Publisher : Universitas 17 Agustus 1945 Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52447/jkte.v8i2.6995

Abstract

Penelitian ini menerangkan perbandingan metode Decision Support System Weighted Aggregated Sum Product Assesment (WASPAS) dan Weighted Product (WP) dalam menentukan kandidat lurah pondok di Pondok Pesantren Al-Munawwir Krapyak L Yogyakarta, dengan tujuan untuk mengurangi adanya pemilihan kandidat lurah pondok yang bersifat subjektif, serta untuk mengetahui perbedaan dari kedua metode dalam menangani kasus penentuan kandidat lurah pondok. Setelah dilakukan penelitian, hasil tiga kandidat lurah pondok yang layak menurut metode WASPAS adalah RdS menempati peringkat pertama, AhL menempati peringkat kedua, dan ChZ menempati peringkat ketiga, sedangkan menurut metode WP adalah AhL menempati peringkat pertama, RdS menempati peringkat kedua, dan ChZ menempati peringkat ketiga, dari beberapa pilihan alternatif santri yang ada. Hasil peringkat kandidat lurah pondok yang menempati peringkat tiga terbesar dengan menggunakan metode WASPAS dan WP adalah sama, hanya bertukar peringkat. Maka kedua metode ini dapat digunakan dalam menentukan kandidat lurah pondok di Pondok Pesantren Al-Munawwir Krapyak Komplek L Yogyakarta.
Co-Authors Abdus Salam, Abdus Ahmad Satria Rizqi Maula Akbar, Rasyan Akbar, Riolandi Akbar, Yuma Alief Prima Gani Amelia, Ika Arinal, Veri Arvianto, Ramdani Aryanti, Putri Gea 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 Dewantara, Rizki Dewanti, Elsa Mayorita Dharmawan, Tio Doni Kurniawan Doni Kurniawan Eldina, Ratih Enny Itje Sela Fakhrurrofi Fakhrurrofi Fakhrurrofi, Fakhrurrofi Faldo Satria Faridatun Nisa Gatra, Rahmadhan Hadi Gunawan, Hadi Haryati Heri Mahyuzar Heri Mahyuzar James, Bobby James, Bobby Arvian Januarsyah, Firly Joko Sutopo Julianda, Rindy Junaidi Junaidi Kasiono, Roy Kastum Kastum Kastum, Kastum Kevin Arya Josaphat Sitompul Khafid Nurohman Khana, Rajes Laras Sitoayu Lutfi Nugrahaini M. A. Burhanuddin Maharani, Delia Maharani, Shinta Aulia Mahardika, Fajar Mahyuzar, Heri Marliani, Tiara Marthy, Nicola Mohd Khanapi Abd Ghani Mubarak, Zulfikar Yusya Muhammad Nurdin Muhammad Syazidan Nabilah, Laila Nandang Sutisna Nisa, Faridatun Nizar, Amin Nugraha, Pramudya Nugrahaini, Lutfi Nugroho, Agung Yuliyanto Nugroho, Wisnu Dwi Nuradi, Fahmi Nurohman, Khafid Opi Irawansah, Opi Paidi, Imam Prayogo, Fadillah Abi Priyanto, Imansyah Purnasiwi, Rona Guines Purwasih, Intan Putri Wibowo, Salsabila Qolbi, Rofika Rachmat Hidayat Insani Rachmawati, Dea Noer Raden Dewa Saktia Purnama Raffiudin, Muhammad Raihanah, Syifa Ramadhan, Abhirama Huga Ramadhani, Devika Azahra Rasiban Ridho Akbar Rizki Maulana, Rizki Romadan, Diva Putra Saidah, Andi Saifullah, Shoffan Saktia Purnama, Raden Dewa Sarimole, Frencis Matheos Setiawan, Kiki Shofwatul ‘Uyun Sodik Sopan Adrianto SOPAN ADRIANTO Sri Lestari Sugeng Sugiono Sugiono Sugiyono Sugiyono Sugiyono Suropati, Untung Sutisna, Nandang Syani, Muhammad Tampubolon, Parlindungan Tasti, Andi Thalita Tiara Ratu Alifia Tresia, Eflin Tri Wahyudi Tundo Tundo Untung Suropati Wafiqi, Achmad Ulul Azmi Wagiman, Wagiman Waloeya, Farhan Adriansyah Wijonarko, Panji Yacob, Galih Satria