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PENERAPAN PEMBELAJARAN BIOLOGI BERBASIS NILAI IMTAQ PADA KONSEP SISTEM REPRODUKSI MANUSIA UNTUK MENINGKATKAN HASIL BELAJAR SISWA KELAS XI – IPA SMA NEGERI 1 MANDIRANCAN Sutisna Sutisna; Eka Fitriah; Anda Juanda
Scientiae Educatia: Jurnal Pendidikan Sains Vol. 3 No. 1 (2014)
Publisher : Tadris Biologi Fakultas Ilmu Tarbiyah dan Keguruan IAIN SYEKH NURJATI CIREBON

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/sc.educatia.v3i1.548

Abstract

Bangsa indonesia saat ini sedang mengalami krisis akhlak khususnya dikalangan pelajar seperti tawuran antar pelajar, tindak kekerasan, perilaku seks yang tidak normal, seks bebas dikalangan pelajar dan lain-lain sepertinya sudah menjadi penghias rutin setiap berita dimedia massa. Peran guru sebagai agent of change (agen perubahan) sangatlah penting dalam pendidikan dan pembelajaran. Guru merupakan salah satu penentu keberhasilan siswa mendapatkan pengalaman belajar dalam membangun kecerdasan intelektual (IQ), kecerdasan emosional (EQ), dan kecerdasan spiritual (SQ) untuk mencapai puncak prestasi. Penelitian ini dilakukan di SMA Negeri 1 Mandirancan, tepatnya dikelas XI IPA 1 (Kelas eksperimen) dengan jumlah siswa 27 siswa dan kelas XI IPA 3 (kelas kontrol) dengan jumlah siswa 27 siswa. Penelitian menggunakan desain Pre test Post test Control Group Design. Teknik pengumpulan data yang digunakan adalah lembar observasi, tes dan angket. Data yang diperoleh dianalisis dengan menggunakan uji statistik meliputi uji normalitas, uji homogenitas dan uji t (hipotesis). Hasil penelitian ini menunjukkan peningkatan hasil belajar siswa setelah diterapkannya pembelajaran biologi berbasis nilai imtaq. Peningkatan hasil belajar siswa kelas eksperimen lebih tinggi daripada kelas kontrol hal ini dibuktikan dengan hasil rata-rata N-Gain 0,61 dengan kriteria  sedang pada kelas ekperimen dan 0,43 pada kelas kontrol dengan kriteria  sedang. Aktivitas on task siswa pada kegiatan awal, kegiatan pembelajaran dan kegiatan evaluasi sebesar 72,48% dengan off task sebesar 27,52% pada kelas eksperimen dan respon siswa terhadap penerapan pembelajaran biologi berbasis nilai imtaq sangat baik dengan rata-rata pernyataan positif memperoleh persentase 68,79% dengan kriteria kuat, sedangkan rata-rata pernyataan negatif memperoleh presentase 64,31% dengan kriteria kuat. Kata Kunci : Penerapan Pembelajaran Biologi Berbasis Nilai Imtaq, Hasil Belajar
Sentiment Analysis of the Kabur Aja Dulu Trend on X as a Basis for Designing a Public Sentiment Monitoring System Using Naïve Bayes and SVM Sutisna Sutisna; Tri Wahyudi; Dwi Swasono Rachmad; Fachrur Rozi
International Journal of Information Engineering and Science Vol. 2 No. 3 (2025): August : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i3.79

Abstract

Social media X (Twitter) has become the main platform for the Indonesian public to express opinions, including on the trend of 'kabur aja dulu' (let's just run away for a bit). This research aims to classify the sentiments of the public using the Naïve Bayes and Support Vector Machine (SVM) methods, and to compare the accuracy of both in sentiment analysis. Data was collected via the Twitter API with the hashtag #kaburajadulu, resulting in 2,067 tweets, which, after the cleansing process and manual labeling, left 385 data points. The analysis process followed the CRISP-DM stages, which include business understanding, data understanding, data preparation, modeling, evaluation, and deployment. Model evaluation was conducted using a confusion matrix with accuracy, precision, and recall metrics. The classification results show that 82% of tweets have a positive sentiment and 18% negative. The Naïve Bayes algorithm achieved an accuracy of 86.49%, slightly lower than SVM, which reached 88.05%. In conclusion, Support Vector Machine is more effective in sentiment classification on public opinion data. This research contributes to the digital mapping of public opinion and recommends the development of automatic labeling methods as well as the exploration of advanced algorithms in the future.
Implementation of the YOLO Algorithm for Detecting Bullying Behavior at Pesantren Bisnis SMK Skill Village Islamic School Jonggol Bogor Sutisna Sutisna; Rizki Ananda Pratama; Nandang Sutisna; Jundi Kariman Husni
International Journal of Information Engineering and Science Vol. 2 No. 4 (2025): November : International Journal of Information Engineering and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijies.v2i4.346

Abstract

Bullying is a serious problem that can disrupt the learning process and mental development of students, including in Islamic boarding schools. Early detection of bullying is essential to creating a safe and conducive learning environment. This study aims to apply the You Only Look Once (YOLO) algorithm to automatically detect bullying through video recordings in the environment of the SMK Skill Village Islamic School Business Boarding School. The method used involves collecting a video dataset representing various types of bullying behavior, labeling the data, and training an object detection model using the YOLOv5 algorithm. The developed system is capable of detecting and classifying bullying behavior in real- time with detection accuracy reaching [accuracy value if known]. The implementation of this system is expected to assist school authorities and boarding school administrators in monitoring, preventing, and addressing bullying incidents more quickly and effectively, while also serving as an initial step in leveraging artificial intelligence technology to create a safer and more comfortable educational environment.
Effectiveness of Face Recognition-Based Security System on CCTV with Raspberry Pi and Esp32-Cam Using Face Recognition Method Frencis Matheos Sarimole; Satria Wira Yudha; Sutisna Sutisna; Ahas Eko Septianto
Journal of Engineering, Electrical and Informatics Vol. 2 No. 2 (2022): Juni: Journal of Engineering, Electrical and Informatics:
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i2.205

Abstract

Current technological advances, such as the internet of things (IOT), have a very broad scope. Especially in the security sector. The fact is that there are many robots that have been made by humans to do jobs that can help humans beyond their abilities. CCTV is very important to protect the house from various types of threats, such as burglary and other hazards. However, a security system that only uses CCTV cameras is no longer secure enough because someone is needed to monitor activities in the CCTV area for 24 hours. As for CCTV that provides facial recognition features, the price is arguably quite expensive. Therefore, we need home security with a more modern, affordable, and effective version of CCTV that utilizes the technology that has been developed to date. In this context, I propose a prototype of a sophisticated, low-cost, Raspberry-PI-based home security system that is integrated with a mobile real-time application. This intelligent robot can monitor the surrounding area by detecting people who are within the range of the camera. notification if a stranger enters the area and is not recognized by the robot to a mobile application that can be installed. The author uses Raspberry Pi hardware as the main control center, OpenCV to perform motion detection and facial recognition, a webserver to make it easier for users to access data and control the system remotely, mobile applications as notification recipients, and real-time monitoring of CCTV. In the tests carried out, the developed IOT-based security system has succeeded in detecting motion and facial recognition with good accuracy and is able to send notifications to smart phones in a short time when suspicious events occur in the house. Thus, this IOT-based home security system can help improve security and comfort by integrating technology and providing more effective and efficient solutions for protecting homes and buildings from various types of threats
Classification of Favorite Book Borrowing Data at the STIKOM CKI Library Using the Decision Tree Algorithm Yuma Akbar; Untung Surapati; Sutisna Sutisna; Yansen Yansen
Journal of Engineering, Electrical and Informatics Vol. 2 No. 1 (2022): Februari : Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i1.3663

Abstract

The library on the STIKOM CKI campus as a means of providing information and has a complete collection of learning media books, but the data processing system for borrowing and returning favorite books in the library is currently still manual, that is, all data collection processes are written on book cards, although it is quite good but the process is rather slow and requires quite a long time because in the process of searching the data must be checked per page one by one so that the data processing is less effective and efficient. To overcome this, it is necessary to develop an application using the decision tree algorithm method which can make it easier to collect borrowing data and return favorite books that are more effective and efficient and display integrated output of student reports that have not returned so that data processing is more accurate and can speed up officer performance. library. Submitting a favorite book lending classification application can make it easier to access loans and returns anywhere and anytime. So that data processing is more accurate and can speed up librarian performance.
Application of Data Mining for Talent Performance Analysis Using The C.45 Method In A Case Study of The Human Resource Department of PT. Xyz Sutisna Sutisna; Tri Wahyudi; Dedi Gunawan; Ivan Pradana
Journal of Engineering, Electrical and Informatics Vol. 2 No. 3 (2022): Oktober: Journal of Engineering, Electrical and Informatics:
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v2i3.3710

Abstract

Human resource management plays a critical role in supporting organizational performance, particularly in identifying employees with high competency and leadership potential. The process of evaluating employee performance is often conducted manually, which may lead to subjectivity and inconsistencies in decision-making. This study aims to implement the C4.5 decision tree algorithm for talent performance analysis within the Human Resource Department of PT. XYZ. The research utilized employee performance data collected during the 2022–2023 period, including variables such as attendance, achievement, assessment results, service period, and other competency-related indicators. The study adopted the Cross Industry Standard Process for Data Mining (CRISP-DM) framework, consisting of business understanding, data understanding, data preparation, modeling, evaluation, and deployment stages. The C4.5 algorithm was employed to classify employee competencies and generate decision rules based on entropy and information gain calculations. The results indicate that the algorithm successfully identified the most influential attributes affecting employee performance classification, with achievement, assessment, and service period emerging as key determinants. The resulting decision tree provides a systematic and interpretable classification model that supports objective employee evaluation and talent identification. The study demonstrates that the application of data mining techniques can assist organizations in improving the effectiveness of employee performance assessment and human resource decision-making processes.
Co-Authors Abdillah, Gipari Pradina Abdul Chobir Abrar Abrar Adicandra, M. Dicky Adnan, Kemal Afifah, Hafshah Nur Agustian, Doni Ahas Eko Septianto Ahmad Mulyadi Kosim Akbar, Yuma Al Islam, Hanif Mufti Ali Akbar Allwar Allwar Ameruddin, Amira Saryati Aminarti, Dhiny Amrullah, Wahyu Anak Agung Istri Sri Wiadnyani Anas, Sahrun Anda Juanda Anggraeni, Dwi Retno Annisa, Annisa Destiana Anto Purwanto Ari Handayani Arinal, Veri Aripin Aripin Aryanto, Rudi Asep Andang, Asep Asep Mulyana Asih Handayanti Azizah, Faridah Nafa Azyumardi, Muhammad Maliki Bachrudin Bachrudin, Bachrudin BAHITS, ABDUL Betty Yel, Mesra Busaeri, Nundang Cahyono, Bowo Eko Dadang Iskandar Mulyana` Dalillah, Assyifa Dani Ahmad Ramdani Dayan Hakim Natigor Dedi Gunawan Dempo, Sri Rahayu Sangra Deni Hamdani Deny Saputra Dini Afriani Dodie Tricahyono Dwi Swasono Rachmad Dwiarso Rubiyanto Edvin Priatna Edy Wibowo Egi Arvian Firmansyah Eka Fitriah Empung Empung Endah Djuwendah Endang Sri Utami, Endang Evan Edo Prasetya Fachrur Rozi Fachry Abda El Rahman Fadiliah, M. Ilyan Fajar, Andriyana Fallah, Ahlan Nur Faridah, Linda Febiantoro, Muhamad Rony firmansyah maualana sugiartana nursuwars Fitriyah, Nusaibah Hafiduddin, Fata Hambari, Hambari Hamidah . Hanif, Ibrahim Hasim As'ari Hazazi, Muhammad Hafizhuddin Hazbullah, Rifaldi Helvantriyudo, Whibatsu Herawati, Upi Hidayat, Selamet Hilman Hakiem Hofi, Abdul I Komang Wahyu Wiguna Ibdalsyah Ibdalsyah Ida Ayu Putu Sri Widnyani Ifkar Usrah Ikhwan Hamdani Indriya, Indriya Irfan Firdaus, Irfan Firdaus Ismudiati Puri Handayani Istiqlal, Muhammad Farisha Ivan Pradana Jaka Wijaya Kusuma Jundi Kariman Husni Juwita Juwita, Juwita Kholil, Moh. Laksana, Angga Lutfi Rohman Malik, Ibnu Mamat Rokhmat Mamay Komarudin Manggala, R. Simo Seto Bagoes Patra Maulana, Rija Rizqi miftahul khairani Milah, Milah Miransyah, Giri Gintang Mochamad Saefullah, Mochamad Moerdyanto, Adjie Wongso Muchtar, Nouval Hidayat Muhammad Zikri Muhyani, Muhyani Mukhammad Fauzi Mukhtar Mukhtar Mulyadi Mulyadi Muttaqina, Hikmah Mi’raj Nana, Nana nanda, afri Nandang Sutisna Nauval, Kurniawan Irfan Nawawi, Kholil Nawawi, M. Kholil Nawawi, Muhammad Kholil Neni Yulianita Nindha Ayu Berlianti Nopiansyah, Eko Novita Andarini Nugraha, Asep Tri Mulyana Nugroho, Tulus Setyo Nundang Busaeri Nunung Ayu Sofiati (Efi) NUR KHOLIFAH Nur Mala Hayati Nur Widiyasono, Nur Nurprayasha, Veisya Afra Nurul Hiron Nurul Hiron, Nurul Nurwulan Fitriyanti Otniel, Fredo Pangestu, Hadi Baku Paryadi Permana, Muhammad Alwi Permana, Rizki Aditya Pratomo, Tommy Wahyu Prinantin Saputra, Dimas Purbayu, Faisal Purnama, Anggit Purtiningtyas, Lilis Rahayu, Reza Ajeng Rahmaddeni Rahmaddeni Rahman, Sulaeman Rahmayanti Kiram Ramdani, Dani Ahmad Rara Genta Munggarani Basri Rasiban Ratih, Nala Ratna Safitri Rendy, Pras Rhini Fatmasari, Rhini Rinaldi Rinaldi Risnandar, Muhammad Aris Rizki Ananda Pratama Rossa, Annisa Destiana Rully Setiawan Rustandi, Tata Sahroni, Sahroni Saifullah, Firman Sanjaya, Abe Sanjaya, Ikhwan Muliana Sanusi, Muhammad Samsul Hidayatullah Sari, Gema Ika Sarimole, Frencis Matheos Saryati Saryati Satria Wira Yudha Sayani, Ayi Abdurahman Shafira Zahra Nur Ghifari Sholichah, Inti Ulfi Simanungkalit, Giraldi Freddy Siti Mardiah, Siti Siti Suprapti Slamet Suyanto Soni Sisbudi Harsono, Soni Sisbudi SOPAN ADRIANTO Sri Nurul Milla Sudarmadi Sudarmadi SUDARYANTO SUDARYANTO Sugiyono Sugiyono Sujito Sujito Sulaeman Rahman Nidar Sulaiman, Dede Sumardjo suryana, Dede Suryana, Dede Suseno, Bambang Dwi Suwardiyanto Suwardiyanto Suyud, Suyud Syahroni, Mukhamad Faizal Syahrul, Ramadhan Syamsul Hidayat Syarifah Gustiawati Mukri Tahir, Arib Nawwar Tanti Haryati Tri Wahyudi Udin Suadma Ulya, Naily Umalihayati Umalihayati Untung Surapati Wa Ode Zusnita, Wa Ode wahyu, haditya Wahyudi, Ahmad Arif Wenny Maulina, Wenny Widiasih, Widiasih Wijayanti, Intan Dwi Wirawan, Shafwan Abiyu Yansen Yansen Yono Yono Yoyo Sudaryo Yudi Aris Sulistiyo, Yudi Aris Yulistia, Zahrah Nazhifah Yuniar, Mirsandi Nazar Yunizar Yunizar, Yunizar YUYUN ELIZABETH PATRAS, YUYUN ELIZABETH Zahid Mubarok Zakaria, Helmy Ahmad