Interpretation Verse of Religious Moderation: Systematic Library Review Meaning of Ummatan Wasathan in Qs. 2: 143

This study focuses on examining the interpretation of the verse on religious moderation, related to the term wastahan ummatan in QS.Al Baqarah (2): 143. This research is important in knowing the views of commentators on the Qur'anic verse regarding religious moderation and related to the contemporary context. This research uses a qualitative traditional approach, using a literature review through a systematic review method of references (Systematic Library Research) related to the focus of this study. The data analysis technique used in this study is descriptive, interpretive and deductive analysis which is carried out in stagesfformulation, search, inspection/selection, analysis-synthesis, quality control mainstreaming, and report preparation.

Kajian Literatur: Internalisasi Nilai-nilai Tasawuf dalam Ajaran Tarekat

The aim of this research is to conduct a theoretical study of the internalization of Sufism values that are applied to the teachings of the tarekat. This study uses an in-depth systematic literature focusing on looking at the concept of internalizing Sufism values applied in the tarekat. In this research process, there are several stages consisting of the literature collection process, literature selection, analysis, and finally combining all the analyzes into a unified whole. The results of this study indicate that the ability of the salik to accept, understand, and carry out the teachings of the tarekat given by the mursyid can be directly through the internalization of Sufism values. Sufism values can be implemented as a form of mental or mental development in the form of patience, tawakkal, sincerity, taubah, qona'ah, zuhud and others so that these values require serious training (riyadho) so that the form of application can be maximized. by experiencing it as a whole.

Estimation of Tool Wear and Surface Roughness Development Using Deep Learning and Sensors Fusion

This paper proposes an estimation approach for tool wear and surface roughness using deep learning and sensor fusion. The one-dimensional convolutional neural network (1D-CNN) is utilized as the estimation model with X- and Y-coordinate vibration signals and sound signal fusion using sensor influence analysis. First, machining experiments with computer numerical control (CNC) parameters are designed using a uniform experimental design (UED) method to guarantee the variety of collected data. The vibration, sound, and spindle current signals are collected and labeled according to the machining parameters. To speed up the degree of tool wear, an accelerated experiment is designed, and the corresponding tool wear and surface roughness are measured. An influential sensor selection analysis is proposed to preserve the estimation accuracy and to minimize the number of sensors. After sensor selection analysis, the sensor signals with better estimation capability are selected and combined using the sensor fusion method. The proposed estimation system combined with sensor selection analysis performs well in terms of accuracy and computational effort. Finally, the proposed approach is applied for on-line monitoring of tool wear with an alarm, which demonstrates the effectiveness of our approach.